Scheduled Commit

data/retrieval_battle-f36c9f97-e795-4522-8eb7-7dee254b42c7.jsonl

@@ -88,3 +88,8 @@
 {"tstamp": 1723725611.3436, "task_type": "retrieval", "type": "tievote", "models": ["", ""], "ip": "", "0_conv_id": "15df5739a8a94a79b276fd0c742b31c8", "0_model_name": "embed-english-v3.0", "0_prompt": "I am looking for a paper to help me deal with data constraints as I scale up my language model.", "0_output": [["I am looking for a paper to help me deal with data constraints as I scale up my language model.", "Title: Scaling Data-Constrained Language Models\n\nAbstract: The current trend of scaling language models involves increasing both parameter count and training dataset size. Extrapolating this trend suggests that training dataset size may soon be limited by the amount of text data available on the internet. Motivated by this limit, we investigate scaling language models in data-constrained regimes. Specifically, we run a large set of experiments varying the extent of data repetition and compute budget, ranging up to 900 billion training tokens and 9 billion parameter models. We find that with constrained data for a fixed compute budget, training with up to 4 epochs of repeated data yields negligible changes to loss compared to having unique data. However, with more repetition, the value of adding compute eventually decays to zero. We propose and empirically validate a scaling law for compute optimality that accounts for the decreasing value of repeated tokens and excess parameters. Finally, we experiment with approaches mitigating data scarcity, including augmenting the training dataset with code data or removing commonly used filters. Models and datasets from our 400 training runs are freely available at https://github.com/huggingface/datablations."]], "0_corpus": "arxiv", "1_conv_id": "d67244c71dff47dd8578f0ae183983d6", "1_model_name": "intfloat/multilingual-e5-large-instruct", "1_prompt": "I am looking for a paper to help me deal with data constraints as I scale up my language model.", "1_output": [["I am looking for a paper to help me deal with data constraints as I scale up my language model.", "Title: Scaling Data-Constrained Language Models\n\nAbstract: The current trend of scaling language models involves increasing both parameter count and training dataset size. Extrapolating this trend suggests that training dataset size may soon be limited by the amount of text data available on the internet. Motivated by this limit, we investigate scaling language models in data-constrained regimes. Specifically, we run a large set of experiments varying the extent of data repetition and compute budget, ranging up to 900 billion training tokens and 9 billion parameter models. We find that with constrained data for a fixed compute budget, training with up to 4 epochs of repeated data yields negligible changes to loss compared to having unique data. However, with more repetition, the value of adding compute eventually decays to zero. We propose and empirically validate a scaling law for compute optimality that accounts for the decreasing value of repeated tokens and excess parameters. Finally, we experiment with approaches mitigating data scarcity, including augmenting the training dataset with code data or removing commonly used filters. Models and datasets from our 400 training runs are freely available at https://github.com/huggingface/datablations."]], "1_corpus": "arxiv"}
 {"tstamp": 1723732221.0731, "task_type": "retrieval", "type": "bothbadvote", "models": ["", ""], "ip": "", "0_conv_id": "6467739d19d74bd18b68bb92509e39f4", "0_model_name": "GritLM/GritLM-7B", "0_prompt": "Employee disengagement in an organisation", "0_output": [["Employee disengagement in an organisation", "Employee engagement\n\nEmployee engagement is a fundamental concept in the effort to understand and describe, both qualitatively and quantitatively, the nature of the relationship between an organization and its employees. An \"engaged employee\" is defined as one who is fully absorbed by and enthusiastic about their work and so takes positive action to further the organization's reputation and interests. An engaged employee has a positive attitude towards the organization and its values. In contrast, a disengaged employee may range from someone doing the bare minimum at work (aka 'coasting'), up to an employee who is actively damaging the company's work output and reputation.\nAn organization with \"high\" employee engagement might therefore be expected to outperform those with \"low\" employee engagement.\nEmployee engagement first appeared as a concept in management theory in the 1990s,\nbecoming widespread in management practice in the 2000s, but it remains contested. Despite academic critiques, employee engagement practices are well established in the management of human resources and of internal communications.\nEmployee engagement today has become synonymous with terms like 'employee experience' and 'employee satisfaction', although satisfaction is a different concept. Whereas engagement refers to work motivation, satisfaction is an employee's attitude about the job--whether they like it or not. The relevance is much more due to the vast majority of new generation professionals in the workforce who have a higher propensity to be 'distracted' and 'disengaged' at work. A recent survey by StaffConnect suggests that an overwhelming number of enterprise organizations today (74.24%) were planning to improve employee experience in 2018."]], "0_corpus": "wikipedia", "1_conv_id": "93a566743f014d7fabae868780558a84", "1_model_name": "BM25", "1_prompt": "Employee disengagement in an organisation", "1_output": [["Employee disengagement in an organisation", "Diffusion of responsibility\n\nMoral disengagement Diffusion of responsibility can negatively affect personal morals. With diffusion of responsibility, it has been found that people feel less accountable for their work. This lack of accountability can be due to the fact that labour is divided amongst members in a group and so no one member feels an overwhelming amount of responsibility for their organisation or their overall project. It has been found that many members get narrowed into focusing on their individual work, that they eventually forget about any moral aspects. Purely focusing on the functional aspects of their jobs is a result of division of labour, which is a mechanism for diffusion of responsibility. This can be highly concerning for organisations since division of labour is a common practice amongst many.\nMoral disengagement is likely to be particularly important in organisations because bureaucratic structures and the division of labour seem to lend themselves to moral disengagement mechanisms such as the diffusion and displacement of responsibility. Euphemistic labelling is also common in organisations, such as when managers refer to layoffs as “rightsizing.” Also, with victims out of sight, globalization makes it easier to ignore or distort the harmful consequences of business actions. Thus, moral disengagement seems highly relevant to understanding unethical behaviour in 21st century organizations."]], "1_corpus": "wikipedia"}
 {"tstamp": 1723737549.4338, "task_type": "retrieval", "type": "tievote", "models": ["", ""], "ip": "", "0_conv_id": "5285a62124c842ce8f1998b25d873cb5", "0_model_name": "intfloat/multilingual-e5-large-instruct", "0_prompt": "is faculty a plural noun?", "0_output": [["is faculty a plural noun?", "Ell Stackexchange\n\nQ: Faculty vs Faculties According to this site, faculty can be expressed in both singular and plural \nforms depending on which one you use. Then when I search up faculties, it exists. Why? Why is there the need of faculties when faculty does the job of being both a plural and singular form?\n\nA: Faculty has two meanings (from Google):\n\n\n*\n\n*an inherent mental or physical power.\n\n*the teaching staff of a university or college, or of one of its departments or divisions, viewed as a body.\nIf meaning 2 is intended, plural verbs even when talking about one faculty, because the noun refers to a collection of multiple people.\nIf meaning 1 is intended, you'd use a singular noun/verb if the subject is one faculty, and a plural noun/verb if the subject is multiple faculties.  \nWhen you see faculties, it's very likely meaning 1, although it's possible the word could be used to refer to multiple separate \"teaching staffs of universities or colleges.\"\n"]], "0_corpus": "stackexchange", "1_conv_id": "07fe63405be345f3a5fac699519e85e4", "1_model_name": "BAAI/bge-large-en-v1.5", "1_prompt": "is faculty a plural noun?", "1_output": [["is faculty a plural noun?", "Ell Stackexchange\n\nQ: Faculty vs Faculties According to this site, faculty can be expressed in both singular and plural \nforms depending on which one you use. Then when I search up faculties, it exists. Why? Why is there the need of faculties when faculty does the job of being both a plural and singular form?\n\nA: Faculty has two meanings (from Google):\n\n\n*\n\n*an inherent mental or physical power.\n\n*the teaching staff of a university or college, or of one of its departments or divisions, viewed as a body.\nIf meaning 2 is intended, plural verbs even when talking about one faculty, because the noun refers to a collection of multiple people.\nIf meaning 1 is intended, you'd use a singular noun/verb if the subject is one faculty, and a plural noun/verb if the subject is multiple faculties.  \nWhen you see faculties, it's very likely meaning 1, although it's possible the word could be used to refer to multiple separate \"teaching staffs of universities or colleges.\"\n"]], "1_corpus": "stackexchange"}
+{"tstamp": 1723745969.3412, "task_type": "retrieval", "type": "leftvote", "models": ["", ""], "ip": "", "0_conv_id": "9c2f558f2e10450595e54efcd2be6874", "0_model_name": "BAAI/bge-large-en-v1.5", "0_prompt": "BERT-based model improving Chinese NLP tasks using character and n-gram pre-training.", "0_output": [["BERT-based model improving Chinese NLP tasks using character and n-gram pre-training.", "Title: Chinese Grammatical Correction Using BERT-based Pre-trained Model\n\nAbstract: In recent years, pre-trained models have been extensively studied, and several downstream tasks have benefited from their utilization. In this study, we verify the effectiveness of two methods that incorporate a BERT-based pre-trained model developed by Cui et al. (2020) into an encoder-decoder model on Chinese grammatical error correction tasks. We also analyze the error type and conclude that sentence-level errors are yet to be addressed."]], "0_corpus": "arxiv", "1_conv_id": "16827c26d1db49ed96f9aed64b5a7fd1", "1_model_name": "sentence-transformers/all-MiniLM-L6-v2", "1_prompt": "BERT-based model improving Chinese NLP tasks using character and n-gram pre-training.", "1_output": [["BERT-based model improving Chinese NLP tasks using character and n-gram pre-training.", "Title: Chaos or Noise - Difficulties of a Distinction\n\nAbstract: In experiments, the dynamical behavior of systems is reflected in time series. Due to the finiteness of the observational data set it is not possible to reconstruct the invariant measure up to arbitrary fine resolution and arbitrary high embedding dimension. These restrictions limit our ability to distinguish between signals generated by different systems, such as regular, chaotic or stochastic ones, when analyzed from a time series point of view. We propose to classify the signal behavior, without referring to any specific model, as stochastic or deterministic on a certain scale of the resolution $\\epsilon$, according to the dependence of the $(\\epsilon,\\tau)$-entropy, $h(\\epsilon, \\tau)$, and of the finite size Lyapunov exponent, $\\lambda(\\epsilon)$, on $\\epsilon$."]], "1_corpus": "arxiv"}
+{"tstamp": 1723746061.6491, "task_type": "retrieval", "type": "tievote", "models": ["", ""], "ip": "", "0_conv_id": "57c46e9488fe450cb2a38320ff9fa47b", "0_model_name": "text-embedding-3-large", "0_prompt": "Which test was devised to determine whether robots can think?", "0_output": [["Which test was devised to determine whether robots can think?", "Turing test\n\nThe test was introduced by Turing in his 1950 paper \"Computing Machinery and Intelligence\" while working at the University of Manchester. It opens with the words: \"I propose to consider the question, 'Can machines think? Because \"thinking\" is difficult to define, Turing chooses to \"replace the question by another, which is closely related to it and is expressed in relatively unambiguous words.\" Turing describes the new form of the problem in terms of a three-person game called the \"imitation game\", in which an interrogator asks questions of a man and a woman in another room in order to determine the correct sex of the two players. Turing's new question is: \"Are there imaginable digital computers which would do well in the imitation game?\" This question, Turing believed, was one that could actually be answered. In the remainder of the paper, he argued against all the major objections to the proposition that \"machines can think\".\nSince Turing introduced his test, it has been both highly influential and widely criticized, and has become an important concept in the philosophy of artificial intelligence. Philosopher John Searle would comment on the Turing test in his Chinese room argument, a thought experiment that stipulates that a machine cannot have a \"mind\", \"understanding\", or \"consciousness\", regardless of how intelligently or human-like the program may make the computer behave. Searle criticizes Turing's test and claims it is insufficient to detect the presence of consciousness.\nHistory"]], "0_corpus": "wikipedia", "1_conv_id": "73c17b7ae70141b69ada3cdfdfe0f4ea", "1_model_name": "text-embedding-004", "1_prompt": "Which test was devised to determine whether robots can think?", "1_output": [["Which test was devised to determine whether robots can think?", "Turing test\n\nThe Turing test, originally called the imitation game by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation was a machine, and all participants would be separated from one another. The conversation would be limited to a text-only channel, such as a computer keyboard and screen, so the result would not depend on the machine's ability to render words as speech. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test. The test results would not depend on the machine's ability to give correct answers to questions, only on how closely its answers resembled those a human would give. Since the Turing test is a test of indistinguishability in performance capacity, the verbal version generalizes naturally to all of human performance capacity, verbal as well as nonverbal (robotic)."]], "1_corpus": "wikipedia"}
+{"tstamp": 1723746096.2088, "task_type": "retrieval", "type": "rightvote", "models": ["", ""], "ip": "", "0_conv_id": "b12478cb353241f8a67fa56e6b709e01", "0_model_name": "jinaai/jina-embeddings-v2-base-en", "0_prompt": "when did they start 3 pointers in basketball", "0_output": [["when did they start 3 pointers in basketball", "Triple point\n\nIn thermodynamics, the triple point of a substance is the temperature and pressure at which the three phases (gas, liquid, and solid) of that substance coexist in thermodynamic equilibrium. It is that temperature and pressure at which the sublimation, fusion, and vaporisation curves meet. For example, the triple point of mercury occurs at a temperature of  and a pressure of 0.165 mPa."]], "0_corpus": "wikipedia", "1_conv_id": "c316a9a16b324dc090e90be5cc248cf3", "1_model_name": "intfloat/multilingual-e5-large-instruct", "1_prompt": "when did they start 3 pointers in basketball", "1_output": [["when did they start 3 pointers in basketball", "Three-point field goal\n\nThree years later in June 1979, the NBA adopted the three-point line (initially on a one-year trial) for the   despite the view of many that it was a gimmick. Chris Ford of the Boston Celtics is credited with making the first three-point shot in NBA history on October 12, 1979. The season opener at Boston Garden was more remarkable for the debut of Larry Bird (and two new  Rick Barry of the Houston Rockets, in his final season, also made one in the same game, and Kevin Grevey of the Washington Bullets made one that Friday night  Barry would later set the original 3-point record at 8 in a single game on February 9, 1980 against the Utah Jazz.  The three-point field goal was slow to be adopted by teams in the NBA. In the 1980 NBA Finals, Julius Erving made the only three of the series (and first in Finals history) in Game 3, and in Game 4, neither team attempted a single shot beyond the arc. Danny Ainge was the first player to make over 100 three-pointers in a season in 1988, draining 148 that season.\nThe sport's international governing body, FIBA, introduced the three-point line in 1984,  and it made its Olympic debut in 1988 in Seoul, South Korea.\nThe NCAA's Southern Conference became the first collegiate conference to use the three-point rule, adopting a  line for the 1980–81 season. Ronnie Carr of Western Carolina was the first to score a three-point field goal in college basketball history on November 29, 1980. Over the following five years, NCAA conferences differed in their use of the rule and distance required for a three-pointer. The line was as close as  in the Atlantic Coast Conference, and as far away as  in the"]], "1_corpus": "wikipedia"}
+{"tstamp": 1723746141.7943, "task_type": "retrieval", "type": "rightvote", "models": ["", ""], "ip": "", "0_conv_id": "be1edeb0d6c94547bcfe682b745d4589", "0_model_name": "sentence-transformers/all-MiniLM-L6-v2", "0_prompt": "A model leveraging T5 for text ranking with direct output ranking scores", "0_output": [["A model leveraging T5 for text ranking with direct output ranking scores", "Title: Far-Infrared Line Imaging of the Starburst Ring in NGC 1097 with the Herschel/PACS Spectrometer\n\nAbstract: NGC 1097 is a nearby SBb galaxy with a Seyfert nucleus and a bright starburst ring. We study the physical properties of the interstellar medium (ISM) in the ring using spatially resolved far-infrared spectral maps of the circumnuclear starburst ring of NGC 1097, obtained with the PACS spectrometer on board the Herschel Space Telescope. In particular, we map the important ISM cooling and diagnostic emission lines of [OI] 63 $\\mu$m, [OIII] 88 $\\mu$m, [NII] 122 $\\mu$m, [CII] 158 $\\mu$m and [NII] 205 $\\mu$m. We observe that in the [OI] 63 $\\mu$m, [OIII] 88 $\\mu$m, and [NII] 122 $\\mu$m line maps, the emission is enhanced in clumps along the NE part of the ring. We observe evidence of rapid rotation in the circumnuclear ring, with a rotation velocity of ~220$ km s$^{-1}$ (inclination uncorrected) measured in all lines. The [OI] 63 $\\mu$m/[CII] 158 $\\mu$m ratio varies smoothly throughout the central region, and is enhanced on the northeastern part of the ring, which may indicate a stronger radiation field. This enhancement coincides with peaks in the [OI] 63 $\\mu$m and [OIII] 88 $\\mu$m maps. Variations of the [NII] 122 $\\mu$m/[NII] 205 $\\mu$m ratio correspond to a range in the ionized gas density between 150 and 400 cm$^{-3}$."]], "0_corpus": "arxiv", "1_conv_id": "5a415e5e5fcc4382ac937a6efdd43204", "1_model_name": "intfloat/multilingual-e5-large-instruct", "1_prompt": "A model leveraging T5 for text ranking with direct output ranking scores", "1_output": [["A model leveraging T5 for text ranking with direct output ranking scores", "Title: RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses\n\nAbstract: Recently, substantial progress has been made in text ranking based on pretrained language models such as BERT. However, there are limited studies on how to leverage more powerful sequence-to-sequence models such as T5. Existing attempts usually formulate text ranking as classification and rely on postprocessing to obtain a ranked list. In this paper, we propose RankT5 and study two T5-based ranking model structures, an encoder-decoder and an encoder-only one, so that they not only can directly output ranking scores for each query-document pair, but also can be fine-tuned with \"pairwise\" or \"listwise\" ranking losses to optimize ranking performances. Our experiments show that the proposed models with ranking losses can achieve substantial ranking performance gains on different public text ranking data sets. Moreover, when fine-tuned with listwise ranking losses, the ranking model appears to have better zero-shot ranking performance on out-of-domain data sets compared to the model fine-tuned with classification losses."]], "1_corpus": "arxiv"}
+{"tstamp": 1723746175.1632, "task_type": "retrieval", "type": "leftvote", "models": ["", ""], "ip": "", "0_conv_id": "1e563a28a5b74247874fa87902ff9fbd", "0_model_name": "sentence-transformers/all-MiniLM-L6-v2", "0_prompt": "when did the term sustainability start to be used", "0_output": [["when did the term sustainability start to be used", "Sustainability\n\nIn the past, sustainability referred to environmental sustainability. It meant using natural resources so that people in the future could continue to rely on them in the long term. The concept of sustainability, or Nachhaltigkeit in German, goes back to Hans Carl von Carlowitz (1645–1714), and applied to forestry. The term for this now would be sustainable forest management. He used this term to mean the long-term responsible use of a natural resource. In his 1713 work Silvicultura oeconomica, he wrote that \"the highest art/science/industriousness [...] will consist in such a conservation and replanting of timber that there can be a continuous, ongoing and sustainable use\". The shift in use of \"sustainability\" from preservation of forests (for future wood production) to broader preservation of environmental resources (to sustain the world for future generations) traces to a 1972 book by Ernst Basler, based on a series of lectures at M.I.T.\nThe idea itself goes back a very long time: Communities have always worried about the capacity of their environment to sustain them in the long term. Many ancient cultures, traditional societies, and indigenous peoples have restricted the use of natural resources.\nComparison to sustainable development\nThe terms sustainability and sustainable development are closely related. In fact, they are often used to mean the same thing. Both terms are linked with the \"three dimensions of sustainability\" concept. One distinction is that sustainability is a general concept, while sustainable development can be a policy or organizing principle. Scholars say sustainability is a broader concept because sustainable development focuses mainly on human well-being.\nSustainable development has two linked goals. It aims to meet human development goals. It also aims to enable natural systems to provide the natural resources and ecosystem services needed for economies and society. The concept of sustainable development has come to focus on economic development, social development and environmental protection for future generations.\nDimensions"]], "0_corpus": "wikipedia", "1_conv_id": "01ce705051244319b81038a310907f0c", "1_model_name": "BM25", "1_prompt": "when did the term sustainability start to be used", "1_output": [["when did the term sustainability start to be used", "Sustainable design\n\nThese activities are an indication that the concept of sustainable design is being supported on a global and interprofessional scale and that the ultimate goal is to become more environmentally responsive. The world needs facilities that are more energy-efficient and that promote conservation and recycling of natural and economic resources.\nEconomically and socially sustainable design\nEnvironmentally sustainable design is most beneficial when it works hand-in-hand with the other two counterparts of sustainable design – the economic and socially sustainable designs. These three terms are often coined under the title \"triple bottom line.\" In addition to financial terms, value can also be measured in relation to natural capital (the biosphere and earth's resources), social capital (the norms and networks that enable collective action), and human capital (the sum total of knowledge, experience, intellectual property, and labor available to society).\nIn some countries the term sustainable design is known as ecodesign, green design or environmental design. Victor Papanek, embraced social design and social quality and ecological quality, but did not explicitly combine these areas of design concern in one term. Sustainable design and design for sustainability are more common terms, including the triple bottom line (people, planet and profit). Advocates like Ecothis.EU campaign urge all three considerations be taken into account when designing a circular economy.\nAspects of environmentally sustainable design"]], "1_corpus": "wikipedia"}

data/retrieval_individual-f36c9f97-e795-4522-8eb7-7dee254b42c7.jsonl

@@ -406,3 +406,13 @@
 {"tstamp": 1723737534.1035, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1723737531.8966, "finish": 1723737534.1035, "ip": "", "conv_id": "07fe63405be345f3a5fac699519e85e4", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "is faculty a plural noun?", "output": [["is faculty a plural noun?", "Ell Stackexchange\n\nQ: Faculty vs Faculties According to this site, faculty can be expressed in both singular and plural \nforms depending on which one you use. Then when I search up faculties, it exists. Why? Why is there the need of faculties when faculty does the job of being both a plural and singular form?\n\nA: Faculty has two meanings (from Google):\n\n\n*\n\n*an inherent mental or physical power.\n\n*the teaching staff of a university or college, or of one of its departments or divisions, viewed as a body.\nIf meaning 2 is intended, plural verbs even when talking about one faculty, because the noun refers to a collection of multiple people.\nIf meaning 1 is intended, you'd use a singular noun/verb if the subject is one faculty, and a plural noun/verb if the subject is multiple faculties.  \nWhen you see faculties, it's very likely meaning 1, although it's possible the word could be used to refer to multiple separate \"teaching staffs of universities or colleges.\"\n"]], "corpus": "stackexchange"}
 {"tstamp": 1723737578.2239, "task_type": "retrieval", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1723737575.9326, "finish": 1723737578.2239, "ip": "", "conv_id": "99c5cd7c2e17478487d019d2f576f9c8", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": "Find me a planet near α 23h 06m 29.368s and δ −05° 02′ 29.04″ that could be habitable.", "output": [["Find me a planet near α 23h 06m 29.368s and δ −05° 02′ 29.04″ that could be habitable.", "List of nearest exoplanets\n\nMost known nearby exoplanets orbit close to their stars. A majority are significantly larger than Earth, but a few have similar masses, including planets around YZ Ceti, Gliese 367, and Proxima Centauri which may be less massive than Earth. Several confirmed exoplanets are hypothesized to be potentially habitable, with Proxima Centauri b and GJ 1002 b (15.8 ly) considered among the most likely candidates. The International Astronomical Union has assigned proper names to some known extrasolar bodies, including nearby exoplanets, through the NameExoWorlds project. Planets named in the 2015 event include the planets around Epsilon Eridani (10.5 ly) and Fomalhaut, while planets named in the 2022 event include those around Gliese 436, Gliese 486, and Gliese 367.\nExoplanets within 10 parsecs\nExcluded objects\nUnlike for bodies within the Solar System, there is no clearly established method for officially recognizing an exoplanet. According to the International Astronomical Union, an exoplanet should be considered confirmed if it has not been disputed for five years after its discovery. There have been examples where the existence of exoplanets has been proposed, but even after follow-up studies their existence is still considered doubtful by some astronomers. Such cases include Wolf 359 (7.9 ly, in 2019), LHS 288 (15.8 ly, in 2007),\nand Gliese 682 (16.3 ly, in 2014).\nThere are also several instances where proposed exoplanets were later disproved by subsequent studies, including candidates around Alpha Centauri B (4.36 ly),\nBarnard's Star (5.96 ly),\nKapteyn's Star (12.8 ly),\nVan Maanen 2 (14.1 ly),\nGroombridge 1618 (15.9 ly),\nAD Leonis (16.2 ly),\n40 Eridani A (16.3 ly),\nVB 10 (19.3 ly), and Fomalhaut (25.1 ly)."]], "corpus": "wikipedia"}
 {"tstamp": 1723737578.2239, "task_type": "retrieval", "type": "chat", "model": "nomic-ai/nomic-embed-text-v1.5", "gen_params": {}, "start": 1723737575.9326, "finish": 1723737578.2239, "ip": "", "conv_id": "f6daa8e6f91f4ff7a7d74639cdc9bb2e", "model_name": "nomic-ai/nomic-embed-text-v1.5", "prompt": "Find me a planet near α 23h 06m 29.368s and δ −05° 02′ 29.04″ that could be habitable.", "output": [["Find me a planet near α 23h 06m 29.368s and δ −05° 02′ 29.04″ that could be habitable.", "Habitable zone\n\nGliese 163 c, discovered in September 2012 in orbit around the red dwarf Gliese 163 is located 49 light years from Earth. The planet has 6.9 Earth masses and 1.8–2.4 Earth radii, and with its close orbit receives 40 percent more stellar radiation than Earth, leading to surface temperatures of about ° C. HD 40307 g, a candidate planet tentatively discovered in November 2012, is in the circumstellar habitable zone of HD 40307. In December 2012, Tau Ceti e and Tau Ceti f were found in the circumstellar habitable zone of Tau Ceti, a Sun-like star 12 light years away. Although more massive than Earth, they are among the least massive planets found to date orbiting in the habitable zone; however, Tau Ceti f, like HD 85512 b, did not fit the new circumstellar habitable zone criteria established by the 2013 Kopparapu study. It is now considered as uninhabitable.\nNear Earth-sized planets and Solar analogs\nRecent discoveries have uncovered planets that are thought to be similar in size or mass to Earth. \"Earth-sized\" ranges are typically defined by mass. The lower range used in many definitions of the super-Earth class is 1.9 Earth masses; likewise, sub-Earths range up to the size of Venus (~0.815 Earth masses). An upper limit of 1.5 Earth radii is also considered, given that above  the average planet density rapidly decreases with increasing radius, indicating these planets have a significant fraction of volatiles by volume overlying a rocky core. A genuinely Earth-like planet – an Earth analog or \"Earth twin\" – would need to meet many conditions beyond size and mass; such properties are not observable using current technology."]], "corpus": "wikipedia"}
+{"tstamp": 1723745955.9979, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1723745953.809, "finish": 1723745955.9979, "ip": "", "conv_id": "9c2f558f2e10450595e54efcd2be6874", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "BERT-based model improving Chinese NLP tasks using character and n-gram pre-training.", "output": [["BERT-based model improving Chinese NLP tasks using character and n-gram pre-training.", "Title: Chinese Grammatical Correction Using BERT-based Pre-trained Model\n\nAbstract: In recent years, pre-trained models have been extensively studied, and several downstream tasks have benefited from their utilization. In this study, we verify the effectiveness of two methods that incorporate a BERT-based pre-trained model developed by Cui et al. (2020) into an encoder-decoder model on Chinese grammatical error correction tasks. We also analyze the error type and conclude that sentence-level errors are yet to be addressed."]], "corpus": "arxiv"}
+{"tstamp": 1723745955.9979, "task_type": "retrieval", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1723745953.809, "finish": 1723745955.9979, "ip": "", "conv_id": "16827c26d1db49ed96f9aed64b5a7fd1", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": "BERT-based model improving Chinese NLP tasks using character and n-gram pre-training.", "output": [["BERT-based model improving Chinese NLP tasks using character and n-gram pre-training.", "Title: Chaos or Noise - Difficulties of a Distinction\n\nAbstract: In experiments, the dynamical behavior of systems is reflected in time series. Due to the finiteness of the observational data set it is not possible to reconstruct the invariant measure up to arbitrary fine resolution and arbitrary high embedding dimension. These restrictions limit our ability to distinguish between signals generated by different systems, such as regular, chaotic or stochastic ones, when analyzed from a time series point of view. We propose to classify the signal behavior, without referring to any specific model, as stochastic or deterministic on a certain scale of the resolution $\\epsilon$, according to the dependence of the $(\\epsilon,\\tau)$-entropy, $h(\\epsilon, \\tau)$, and of the finite size Lyapunov exponent, $\\lambda(\\epsilon)$, on $\\epsilon$."]], "corpus": "arxiv"}
+{"tstamp": 1723745994.3794, "task_type": "retrieval", "type": "chat", "model": "text-embedding-3-large", "gen_params": {}, "start": 1723745991.7743, "finish": 1723745994.3794, "ip": "", "conv_id": "57c46e9488fe450cb2a38320ff9fa47b", "model_name": "text-embedding-3-large", "prompt": "Which test was devised to determine whether robots can think?", "output": [["Which test was devised to determine whether robots can think?", "Turing test\n\nThe test was introduced by Turing in his 1950 paper \"Computing Machinery and Intelligence\" while working at the University of Manchester. It opens with the words: \"I propose to consider the question, 'Can machines think? Because \"thinking\" is difficult to define, Turing chooses to \"replace the question by another, which is closely related to it and is expressed in relatively unambiguous words.\" Turing describes the new form of the problem in terms of a three-person game called the \"imitation game\", in which an interrogator asks questions of a man and a woman in another room in order to determine the correct sex of the two players. Turing's new question is: \"Are there imaginable digital computers which would do well in the imitation game?\" This question, Turing believed, was one that could actually be answered. In the remainder of the paper, he argued against all the major objections to the proposition that \"machines can think\".\nSince Turing introduced his test, it has been both highly influential and widely criticized, and has become an important concept in the philosophy of artificial intelligence. Philosopher John Searle would comment on the Turing test in his Chinese room argument, a thought experiment that stipulates that a machine cannot have a \"mind\", \"understanding\", or \"consciousness\", regardless of how intelligently or human-like the program may make the computer behave. Searle criticizes Turing's test and claims it is insufficient to detect the presence of consciousness.\nHistory"]], "corpus": "wikipedia"}
+{"tstamp": 1723745994.3794, "task_type": "retrieval", "type": "chat", "model": "text-embedding-004", "gen_params": {}, "start": 1723745991.7743, "finish": 1723745994.3794, "ip": "", "conv_id": "73c17b7ae70141b69ada3cdfdfe0f4ea", "model_name": "text-embedding-004", "prompt": "Which test was devised to determine whether robots can think?", "output": [["Which test was devised to determine whether robots can think?", "Turing test\n\nThe Turing test, originally called the imitation game by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation was a machine, and all participants would be separated from one another. The conversation would be limited to a text-only channel, such as a computer keyboard and screen, so the result would not depend on the machine's ability to render words as speech. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test. The test results would not depend on the machine's ability to give correct answers to questions, only on how closely its answers resembled those a human would give. Since the Turing test is a test of indistinguishability in performance capacity, the verbal version generalizes naturally to all of human performance capacity, verbal as well as nonverbal (robotic)."]], "corpus": "wikipedia"}
+{"tstamp": 1723746079.3393, "task_type": "retrieval", "type": "chat", "model": "jinaai/jina-embeddings-v2-base-en", "gen_params": {}, "start": 1723746077.1255, "finish": 1723746079.3393, "ip": "", "conv_id": "b12478cb353241f8a67fa56e6b709e01", "model_name": "jinaai/jina-embeddings-v2-base-en", "prompt": "when did they start 3 pointers in basketball", "output": [["when did they start 3 pointers in basketball", "Triple point\n\nIn thermodynamics, the triple point of a substance is the temperature and pressure at which the three phases (gas, liquid, and solid) of that substance coexist in thermodynamic equilibrium. It is that temperature and pressure at which the sublimation, fusion, and vaporisation curves meet. For example, the triple point of mercury occurs at a temperature of  and a pressure of 0.165 mPa."]], "corpus": "wikipedia"}
+{"tstamp": 1723746079.3393, "task_type": "retrieval", "type": "chat", "model": "intfloat/multilingual-e5-large-instruct", "gen_params": {}, "start": 1723746077.1255, "finish": 1723746079.3393, "ip": "", "conv_id": "c316a9a16b324dc090e90be5cc248cf3", "model_name": "intfloat/multilingual-e5-large-instruct", "prompt": "when did they start 3 pointers in basketball", "output": [["when did they start 3 pointers in basketball", "Three-point field goal\n\nThree years later in June 1979, the NBA adopted the three-point line (initially on a one-year trial) for the   despite the view of many that it was a gimmick. Chris Ford of the Boston Celtics is credited with making the first three-point shot in NBA history on October 12, 1979. The season opener at Boston Garden was more remarkable for the debut of Larry Bird (and two new  Rick Barry of the Houston Rockets, in his final season, also made one in the same game, and Kevin Grevey of the Washington Bullets made one that Friday night  Barry would later set the original 3-point record at 8 in a single game on February 9, 1980 against the Utah Jazz.  The three-point field goal was slow to be adopted by teams in the NBA. In the 1980 NBA Finals, Julius Erving made the only three of the series (and first in Finals history) in Game 3, and in Game 4, neither team attempted a single shot beyond the arc. Danny Ainge was the first player to make over 100 three-pointers in a season in 1988, draining 148 that season.\nThe sport's international governing body, FIBA, introduced the three-point line in 1984,  and it made its Olympic debut in 1988 in Seoul, South Korea.\nThe NCAA's Southern Conference became the first collegiate conference to use the three-point rule, adopting a  line for the 1980–81 season. Ronnie Carr of Western Carolina was the first to score a three-point field goal in college basketball history on November 29, 1980. Over the following five years, NCAA conferences differed in their use of the rule and distance required for a three-pointer. The line was as close as  in the Atlantic Coast Conference, and as far away as  in the"]], "corpus": "wikipedia"}
+{"tstamp": 1723746131.0942, "task_type": "retrieval", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1723746130.9754, "finish": 1723746131.0942, "ip": "", "conv_id": "be1edeb0d6c94547bcfe682b745d4589", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": "A model leveraging T5 for text ranking with direct output ranking scores", "output": [["A model leveraging T5 for text ranking with direct output ranking scores", "Title: Far-Infrared Line Imaging of the Starburst Ring in NGC 1097 with the Herschel/PACS Spectrometer\n\nAbstract: NGC 1097 is a nearby SBb galaxy with a Seyfert nucleus and a bright starburst ring. We study the physical properties of the interstellar medium (ISM) in the ring using spatially resolved far-infrared spectral maps of the circumnuclear starburst ring of NGC 1097, obtained with the PACS spectrometer on board the Herschel Space Telescope. In particular, we map the important ISM cooling and diagnostic emission lines of [OI] 63 $\\mu$m, [OIII] 88 $\\mu$m, [NII] 122 $\\mu$m, [CII] 158 $\\mu$m and [NII] 205 $\\mu$m. We observe that in the [OI] 63 $\\mu$m, [OIII] 88 $\\mu$m, and [NII] 122 $\\mu$m line maps, the emission is enhanced in clumps along the NE part of the ring. We observe evidence of rapid rotation in the circumnuclear ring, with a rotation velocity of ~220$ km s$^{-1}$ (inclination uncorrected) measured in all lines. The [OI] 63 $\\mu$m/[CII] 158 $\\mu$m ratio varies smoothly throughout the central region, and is enhanced on the northeastern part of the ring, which may indicate a stronger radiation field. This enhancement coincides with peaks in the [OI] 63 $\\mu$m and [OIII] 88 $\\mu$m maps. Variations of the [NII] 122 $\\mu$m/[NII] 205 $\\mu$m ratio correspond to a range in the ionized gas density between 150 and 400 cm$^{-3}$."]], "corpus": "arxiv"}
+{"tstamp": 1723746131.0942, "task_type": "retrieval", "type": "chat", "model": "intfloat/multilingual-e5-large-instruct", "gen_params": {}, "start": 1723746130.9754, "finish": 1723746131.0942, "ip": "", "conv_id": "5a415e5e5fcc4382ac937a6efdd43204", "model_name": "intfloat/multilingual-e5-large-instruct", "prompt": "A model leveraging T5 for text ranking with direct output ranking scores", "output": [["A model leveraging T5 for text ranking with direct output ranking scores", "Title: RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses\n\nAbstract: Recently, substantial progress has been made in text ranking based on pretrained language models such as BERT. However, there are limited studies on how to leverage more powerful sequence-to-sequence models such as T5. Existing attempts usually formulate text ranking as classification and rely on postprocessing to obtain a ranked list. In this paper, we propose RankT5 and study two T5-based ranking model structures, an encoder-decoder and an encoder-only one, so that they not only can directly output ranking scores for each query-document pair, but also can be fine-tuned with \"pairwise\" or \"listwise\" ranking losses to optimize ranking performances. Our experiments show that the proposed models with ranking losses can achieve substantial ranking performance gains on different public text ranking data sets. Moreover, when fine-tuned with listwise ranking losses, the ranking model appears to have better zero-shot ranking performance on out-of-domain data sets compared to the model fine-tuned with classification losses."]], "corpus": "arxiv"}
+{"tstamp": 1723746162.7402, "task_type": "retrieval", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1723746161.7284, "finish": 1723746162.7402, "ip": "", "conv_id": "1e563a28a5b74247874fa87902ff9fbd", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": "when did the term sustainability start to be used", "output": [["when did the term sustainability start to be used", "Sustainability\n\nIn the past, sustainability referred to environmental sustainability. It meant using natural resources so that people in the future could continue to rely on them in the long term. The concept of sustainability, or Nachhaltigkeit in German, goes back to Hans Carl von Carlowitz (1645–1714), and applied to forestry. The term for this now would be sustainable forest management. He used this term to mean the long-term responsible use of a natural resource. In his 1713 work Silvicultura oeconomica, he wrote that \"the highest art/science/industriousness [...] will consist in such a conservation and replanting of timber that there can be a continuous, ongoing and sustainable use\". The shift in use of \"sustainability\" from preservation of forests (for future wood production) to broader preservation of environmental resources (to sustain the world for future generations) traces to a 1972 book by Ernst Basler, based on a series of lectures at M.I.T.\nThe idea itself goes back a very long time: Communities have always worried about the capacity of their environment to sustain them in the long term. Many ancient cultures, traditional societies, and indigenous peoples have restricted the use of natural resources.\nComparison to sustainable development\nThe terms sustainability and sustainable development are closely related. In fact, they are often used to mean the same thing. Both terms are linked with the \"three dimensions of sustainability\" concept. One distinction is that sustainability is a general concept, while sustainable development can be a policy or organizing principle. Scholars say sustainability is a broader concept because sustainable development focuses mainly on human well-being.\nSustainable development has two linked goals. It aims to meet human development goals. It also aims to enable natural systems to provide the natural resources and ecosystem services needed for economies and society. The concept of sustainable development has come to focus on economic development, social development and environmental protection for future generations.\nDimensions"]], "corpus": "wikipedia"}
+{"tstamp": 1723746162.7402, "task_type": "retrieval", "type": "chat", "model": "BM25", "gen_params": {}, "start": 1723746161.7284, "finish": 1723746162.7402, "ip": "", "conv_id": "01ce705051244319b81038a310907f0c", "model_name": "BM25", "prompt": "when did the term sustainability start to be used", "output": [["when did the term sustainability start to be used", "Sustainable design\n\nThese activities are an indication that the concept of sustainable design is being supported on a global and interprofessional scale and that the ultimate goal is to become more environmentally responsive. The world needs facilities that are more energy-efficient and that promote conservation and recycling of natural and economic resources.\nEconomically and socially sustainable design\nEnvironmentally sustainable design is most beneficial when it works hand-in-hand with the other two counterparts of sustainable design – the economic and socially sustainable designs. These three terms are often coined under the title \"triple bottom line.\" In addition to financial terms, value can also be measured in relation to natural capital (the biosphere and earth's resources), social capital (the norms and networks that enable collective action), and human capital (the sum total of knowledge, experience, intellectual property, and labor available to society).\nIn some countries the term sustainable design is known as ecodesign, green design or environmental design. Victor Papanek, embraced social design and social quality and ecological quality, but did not explicitly combine these areas of design concern in one term. Sustainable design and design for sustainability are more common terms, including the triple bottom line (people, planet and profit). Advocates like Ecothis.EU campaign urge all three considerations be taken into account when designing a circular economy.\nAspects of environmentally sustainable design"]], "corpus": "wikipedia"}