Scheduled Commit

data/retrieval_battle-f62bcad9-19c4-430b-a7ba-aa2bfeba99dc.jsonl

@@ -76,3 +76,4 @@
 {"tstamp": 1722433570.3218, "task_type": "retrieval", "type": "rightvote", "models": ["", ""], "ip": "", "0_conv_id": "c9ba77f275f5475c8f33498115e1dab9", "0_model_name": "embed-english-v3.0", "0_prompt": "ontological agnosticism", "0_output": [["ontological agnosticism", "Agnostic theism\n\nViews of agnostic theism There are numerous beliefs that can be included in agnostic theism, such as fideism, the doctrine that knowledge depends on faith or revelation; not all agnostic theists are fideists. Since agnosticism is in the philosophical rather than religious sense an epistemological position on knowledge regarding the divine and does not forbid belief in the existence of one or more deities, it is considered to be compatible with both atheistic and theistic positions.\nThe classical philosophical understanding of knowledge is that knowledge is justified true belief. The founder of logotherapy, Viktor Frankl, may have well exemplified this definition. Seidner expands upon this example and stresses Frankl's characterization of unconscious. Agnostic theism could be interpreted as an admission that it is not possible to justify one's belief in a god sufficiently for it to be considered known. This may be because they consider faith a requirement of their religion, or because of the influence of plausible-seeming scientific or philosophical criticism.\nChristian agnostics practice a distinct form of agnosticism that applies only to the attributes of the Christian god. They hold that it is difficult or impossible to be sure of anything beyond the basic tenets of the Christian faith. They believe that the Christian god exists, that Jesus has a special relationship with him and is in some way divine, and that God might perhaps be worshipped. This belief system has deep roots in Judaism and the early days of the Christian Church."]], "0_corpus": "wikipedia", "1_conv_id": "ccfc1e7539f34690b9f698a2a0cb8ff4", "1_model_name": "jinaai/jina-embeddings-v2-base-en", "1_prompt": "ontological agnosticism", "1_output": [["ontological agnosticism", "Agnosticism\n\nAgnosticism is the view or belief that the existence of God, the divine, or the supernatural is either unknowable in principle or currently unknown in fact. It can also mean an apathy towards such religious belief and refer to personal limitations rather than a worldview. Another definition is the view that \"human reason is incapable of providing sufficient rational grounds to justify either the belief that God exists or the belief that God does not exist.\""]], "1_corpus": "wikipedia"}
 {"tstamp": 1722433617.2108, "task_type": "retrieval", "type": "bothbadvote", "models": ["", ""], "ip": "", "0_conv_id": "73769c4977e94ec3b25bfdfd7ac03f4b", "0_model_name": "mixedbread-ai/mxbai-embed-large-v1", "0_prompt": "experimental metaphysics", "0_output": [["experimental metaphysics", "Metaphilosophy\n\nRecently, some philosophers have cast doubt about intuition as a basic tool in philosophical inquiry, from Socrates up to contemporary philosophy of language. In Rethinking Intuition various thinkers discard intuition as a valid source of knowledge and thereby call into question 'a priori' philosophy. Experimental philosophy is a form of philosophical inquiry that makes at least partial use of empirical research—especially opinion polling—in order to address persistent philosophical questions. This is in contrast with the methods found in analytic philosophy, whereby some say a philosopher will sometimes begin by appealing to his or her intuitions on an issue and then form an argument with those intuitions as premises. However, disagreement about what experimental philosophy can accomplish is widespread and several philosophers have offered criticisms. One claim is that the empirical data gathered by experimental philosophers can have an indirect effect on philosophical questions by allowing for a better understanding of the underlying psychological processes which lead to philosophical intuitions. Some analytic philosophers like Timothy Williamson have rejected such a move against 'armchair' philosophy–i.e., philosophical inquiry that is undergirded by intuition–by construing 'intuition' (which they believe to be a misnomer) as merely referring to common cognitive faculties: If one is calling into question 'intuition', one is, they would say, harboring a skeptical attitude towards common cognitive faculties–a consequence that seems philosophically unappealing. For Williamson, instances of intuition are instances of our cognitive faculties processing counterfactuals (or subjunctive conditionals) that are specific to the thought experiment or example in question.\nProgress\nA prominent question in metaphilosophy is that of whether or not philosophical progress occurs and more so, whether such progress in philosophy is even possible.\nDavid Chalmers divides inquiry into philosophical progress in metaphilosophy into three questions.\nThe Existence Question: is there progress in philosophy?\nThe Comparison Question: is there as much progress in philosophy as in science?\nThe Explanation Question: why isn't there more progress in philosophy?"]], "0_corpus": "wikipedia", "1_conv_id": "18e7e82f152d4ab4bfdea463925d23a6", "1_model_name": "text-embedding-3-large", "1_prompt": "experimental metaphysics", "1_output": [["experimental metaphysics", "Metaphysics\n\nA priori approaches often rely on intuitions, that is, non-inferential impressions about the correctness of specific claims or general principles. For example, arguments for the A-theory of time, which states that time flows from the past through the present and into the future, often rely on pre-theoretical intuitions associated with the sense of the passage of time. Some approaches use intuitions to establish a small set of self-evident fundamental principles, known as axioms, and employ deductive reasoning to build complex metaphysical systems by drawing conclusions from these axioms. Intuition-based approaches can be combined with thought experiments, which help evoke and clarify intuitions by linking them to imagined situations while using counterfactual thinking to assess the possible consequences of these situations. To explore the relation between matter and consciousness, some theorists compare humans to philosophical zombies, that is, hypothetical creatures identical to humans but without conscious experience. A related method relies on commonly accepted beliefs instead of intuitions to formulate arguments and theories. The common-sense approach is often used to criticize metaphysical theories that deviate a lot from how the average person thinks about an issue. For example, common-sense philosophers have argued that mereological nihilism is false since it implies that commonly accepted things, like tables, do not exist."]], "1_corpus": "wikipedia"}
 {"tstamp": 1722433650.4248, "task_type": "retrieval", "type": "leftvote", "models": ["", ""], "ip": "", "0_conv_id": "81fd0c894f194fcfa36ed75bd2d83aca", "0_model_name": "BAAI/bge-large-en-v1.5", "0_prompt": "Study analyzing the multitask accuracy of text models including GPT-3 on academic and professional knowledge areas.", "0_output": [["Study analyzing the multitask accuracy of text models including GPT-3 on academic and professional knowledge areas.", "Title: Measuring Massive Multitask Language Understanding\n\nAbstract: We propose a new test to measure a text model's multitask accuracy. The test covers 57 tasks including elementary mathematics, US history, computer science, law, and more. To attain high accuracy on this test, models must possess extensive world knowledge and problem solving ability. We find that while most recent models have near random-chance accuracy, the very largest GPT-3 model improves over random chance by almost 20 percentage points on average. However, on every one of the 57 tasks, the best models still need substantial improvements before they can reach expert-level accuracy. Models also have lopsided performance and frequently do not know when they are wrong. Worse, they still have near-random accuracy on some socially important subjects such as morality and law. By comprehensively evaluating the breadth and depth of a model's academic and professional understanding, our test can be used to analyze models across many tasks and to identify important shortcomings."]], "0_corpus": "arxiv", "1_conv_id": "a07d495a636249d889895f7e399d41b3", "1_model_name": "sentence-transformers/all-MiniLM-L6-v2", "1_prompt": "Study analyzing the multitask accuracy of text models including GPT-3 on academic and professional knowledge areas.", "1_output": [["Study analyzing the multitask accuracy of text models including GPT-3 on academic and professional knowledge areas.", "Title: There are no two non-real conjugates of a Pisot number with the same imaginary part\n\nAbstract: We show that the number $\\alpha=(1+\\sqrt{3+2\\sqrt{5}})/2$ with minimal polynomial $x^4-2x^3+x-1$ is the only Pisot number whose four distinct conjugates $\\alpha_1,\\alpha_2,\\alpha_3,\\alpha_4$ satisfy the additive relation $\\alpha_1+\\alpha_2=\\alpha_3+\\alpha_4$. This implies that there exists no two non-real conjugates of a Pisot number with the same imaginary part and also that at most two conjugates of a Pisot number can have the same real part. On the other hand, we prove that similar four term equations $\\alpha_1 = \\alpha_2 + \\alpha_3+\\alpha_4$ or $\\alpha_1 + \\alpha_2 + \\alpha_3 + \\alpha_4 =0$ cannot be solved in conjugates of a Pisot number $\\alpha$. We also show that the roots of the Siegel's polynomial $x^3-x-1$ are the only solutions to the three term equation $\\alpha_1+\\alpha_2+\\alpha_3=0$ in conjugates of a Pisot number. Finally, we prove that there exists no Pisot number whose conjugates satisfy the relation $\\alpha_1=\\alpha_2+\\alpha_3$."]], "1_corpus": "arxiv"}
+{"tstamp": 1722433984.3307, "task_type": "retrieval", "type": "rightvote", "models": ["", ""], "ip": "", "0_conv_id": "e93de447a5a24fa494ff1d3829debaa8", "0_model_name": "BM25", "0_prompt": "What is the first probe we sent to space?", "0_output": [["What is the first probe we sent to space?", "Pioneer program\n\nThe Pioneer programs were two series of United States lunar and planetary space probes exploration. The first program, which ran from 1958 to 1960, unsuccessfully attempted to send spacecraft to orbit the Moon, successfully sent one spacecraft to fly by the Moon, and successfully sent one spacecraft to investigate interplanetary space between the orbits of Earth and Venus. The second program, which ran from 1965 to 1992, sent four spacecraft to measure interplanetary space weather, two to explore Jupiter and Saturn, and two to explore Venus. The two outer planet probes, Pioneer 10 and Pioneer 11, became the first two of five artificial objects to achieve the escape velocity that will allow them to leave the Solar System, and carried a golden plaque each depicting a man and a woman and information about the origin and the creators of the probes, in case any extraterrestrials find them someday.\nNaming\nCredit for naming the first probe has been attributed to Stephen A. Saliga, who had been assigned to the Air Force Orientation Group, Wright-Patterson AFB, as chief designer of Air Force exhibits. While he was at a briefing, the spacecraft was described to him, as, a \"lunar-orbiting vehicle, with an infrared scanning device.\" Saliga thought the title too long, and lacked theme for an exhibit design. He suggested, \"Pioneer\", as the name of the probe, since \"the Army had already launched and orbited the Explorer satellite, and their Public Information Office was identifying the Army, as, 'Pioneers in Space,'\" and, by adopting the name, the Air Force would \"make a 'quantum jump' as to who, really, [were] the 'Pioneers' in space.'\""]], "0_corpus": "wikipedia", "1_conv_id": "53b85fd89d2b4f02b5d77aedc69d0628", "1_model_name": "intfloat/e5-mistral-7b-instruct", "1_prompt": "What is the first probe we sent to space?", "1_output": [["What is the first probe we sent to space?", "Sputnik 1\n\nSputnik 1 (, , Satellite 1) was the first artificial Earth satellite. It was launched into an elliptical low Earth orbit by the Soviet Union on 4 October 1957 as part of the Soviet space program. It sent a radio signal back to Earth for three weeks before its three silver-zinc batteries became depleted. Aerodynamic drag caused it to fall back into the atmosphere on 4 January 1958. The world's first observation was made at the school observatory in Rodewisch (Saxony).\nIt was a polished metal sphere  in diameter with four external radio antennas to broadcast radio pulses. Its radio signal was easily detectable by amateur radio operators, and the 65° orbital inclination made its flight path cover virtually the entire inhabited Earth."]], "1_corpus": "wikipedia"}

data/retrieval_individual-f62bcad9-19c4-430b-a7ba-aa2bfeba99dc.jsonl

@@ -288,3 +288,9 @@
 {"tstamp": 1722433594.6328, "task_type": "retrieval", "type": "chat", "model": "text-embedding-3-large", "gen_params": {}, "start": 1722433594.0628, "finish": 1722433594.6328, "ip": "", "conv_id": "18e7e82f152d4ab4bfdea463925d23a6", "model_name": "text-embedding-3-large", "prompt": "experimental metaphysics", "output": [["experimental metaphysics", "Metaphysics\n\nA priori approaches often rely on intuitions, that is, non-inferential impressions about the correctness of specific claims or general principles. For example, arguments for the A-theory of time, which states that time flows from the past through the present and into the future, often rely on pre-theoretical intuitions associated with the sense of the passage of time. Some approaches use intuitions to establish a small set of self-evident fundamental principles, known as axioms, and employ deductive reasoning to build complex metaphysical systems by drawing conclusions from these axioms. Intuition-based approaches can be combined with thought experiments, which help evoke and clarify intuitions by linking them to imagined situations while using counterfactual thinking to assess the possible consequences of these situations. To explore the relation between matter and consciousness, some theorists compare humans to philosophical zombies, that is, hypothetical creatures identical to humans but without conscious experience. A related method relies on commonly accepted beliefs instead of intuitions to formulate arguments and theories. The common-sense approach is often used to criticize metaphysical theories that deviate a lot from how the average person thinks about an issue. For example, common-sense philosophers have argued that mereological nihilism is false since it implies that commonly accepted things, like tables, do not exist."]], "corpus": "wikipedia"}
 {"tstamp": 1722433637.6696, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722433637.5031, "finish": 1722433637.6696, "ip": "", "conv_id": "81fd0c894f194fcfa36ed75bd2d83aca", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "Study analyzing the multitask accuracy of text models including GPT-3 on academic and professional knowledge areas.", "output": [["Study analyzing the multitask accuracy of text models including GPT-3 on academic and professional knowledge areas.", "Title: Measuring Massive Multitask Language Understanding\n\nAbstract: We propose a new test to measure a text model's multitask accuracy. The test covers 57 tasks including elementary mathematics, US history, computer science, law, and more. To attain high accuracy on this test, models must possess extensive world knowledge and problem solving ability. We find that while most recent models have near random-chance accuracy, the very largest GPT-3 model improves over random chance by almost 20 percentage points on average. However, on every one of the 57 tasks, the best models still need substantial improvements before they can reach expert-level accuracy. Models also have lopsided performance and frequently do not know when they are wrong. Worse, they still have near-random accuracy on some socially important subjects such as morality and law. By comprehensively evaluating the breadth and depth of a model's academic and professional understanding, our test can be used to analyze models across many tasks and to identify important shortcomings."]], "corpus": "arxiv"}
 {"tstamp": 1722433637.6696, "task_type": "retrieval", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1722433637.5031, "finish": 1722433637.6696, "ip": "", "conv_id": "a07d495a636249d889895f7e399d41b3", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": "Study analyzing the multitask accuracy of text models including GPT-3 on academic and professional knowledge areas.", "output": [["Study analyzing the multitask accuracy of text models including GPT-3 on academic and professional knowledge areas.", "Title: There are no two non-real conjugates of a Pisot number with the same imaginary part\n\nAbstract: We show that the number $\\alpha=(1+\\sqrt{3+2\\sqrt{5}})/2$ with minimal polynomial $x^4-2x^3+x-1$ is the only Pisot number whose four distinct conjugates $\\alpha_1,\\alpha_2,\\alpha_3,\\alpha_4$ satisfy the additive relation $\\alpha_1+\\alpha_2=\\alpha_3+\\alpha_4$. This implies that there exists no two non-real conjugates of a Pisot number with the same imaginary part and also that at most two conjugates of a Pisot number can have the same real part. On the other hand, we prove that similar four term equations $\\alpha_1 = \\alpha_2 + \\alpha_3+\\alpha_4$ or $\\alpha_1 + \\alpha_2 + \\alpha_3 + \\alpha_4 =0$ cannot be solved in conjugates of a Pisot number $\\alpha$. We also show that the roots of the Siegel's polynomial $x^3-x-1$ are the only solutions to the three term equation $\\alpha_1+\\alpha_2+\\alpha_3=0$ in conjugates of a Pisot number. Finally, we prove that there exists no Pisot number whose conjugates satisfy the relation $\\alpha_1=\\alpha_2+\\alpha_3$."]], "corpus": "arxiv"}
+{"tstamp": 1722433948.721, "task_type": "retrieval", "type": "chat", "model": "BM25", "gen_params": {}, "start": 1722433948.3906, "finish": 1722433948.721, "ip": "", "conv_id": "e93de447a5a24fa494ff1d3829debaa8", "model_name": "BM25", "prompt": "What is the first probe we sent to space?", "output": [["What is the first probe we sent to space?", "Pioneer program\n\nThe Pioneer programs were two series of United States lunar and planetary space probes exploration. The first program, which ran from 1958 to 1960, unsuccessfully attempted to send spacecraft to orbit the Moon, successfully sent one spacecraft to fly by the Moon, and successfully sent one spacecraft to investigate interplanetary space between the orbits of Earth and Venus. The second program, which ran from 1965 to 1992, sent four spacecraft to measure interplanetary space weather, two to explore Jupiter and Saturn, and two to explore Venus. The two outer planet probes, Pioneer 10 and Pioneer 11, became the first two of five artificial objects to achieve the escape velocity that will allow them to leave the Solar System, and carried a golden plaque each depicting a man and a woman and information about the origin and the creators of the probes, in case any extraterrestrials find them someday.\nNaming\nCredit for naming the first probe has been attributed to Stephen A. Saliga, who had been assigned to the Air Force Orientation Group, Wright-Patterson AFB, as chief designer of Air Force exhibits. While he was at a briefing, the spacecraft was described to him, as, a \"lunar-orbiting vehicle, with an infrared scanning device.\" Saliga thought the title too long, and lacked theme for an exhibit design. He suggested, \"Pioneer\", as the name of the probe, since \"the Army had already launched and orbited the Explorer satellite, and their Public Information Office was identifying the Army, as, 'Pioneers in Space,'\" and, by adopting the name, the Air Force would \"make a 'quantum jump' as to who, really, [were] the 'Pioneers' in space.'\""]], "corpus": "wikipedia"}
+{"tstamp": 1722433948.721, "task_type": "retrieval", "type": "chat", "model": "intfloat/e5-mistral-7b-instruct", "gen_params": {}, "start": 1722433948.3906, "finish": 1722433948.721, "ip": "", "conv_id": "53b85fd89d2b4f02b5d77aedc69d0628", "model_name": "intfloat/e5-mistral-7b-instruct", "prompt": "What is the first probe we sent to space?", "output": [["What is the first probe we sent to space?", "Sputnik 1\n\nSputnik 1 (, , Satellite 1) was the first artificial Earth satellite. It was launched into an elliptical low Earth orbit by the Soviet Union on 4 October 1957 as part of the Soviet space program. It sent a radio signal back to Earth for three weeks before its three silver-zinc batteries became depleted. Aerodynamic drag caused it to fall back into the atmosphere on 4 January 1958. The world's first observation was made at the school observatory in Rodewisch (Saxony).\nIt was a polished metal sphere  in diameter with four external radio antennas to broadcast radio pulses. Its radio signal was easily detectable by amateur radio operators, and the 65° orbital inclination made its flight path cover virtually the entire inhabited Earth."]], "corpus": "wikipedia"}
+{"tstamp": 1722434006.2573, "task_type": "retrieval", "type": "chat", "model": "mixedbread-ai/mxbai-embed-large-v1", "gen_params": {}, "start": 1722434004.1172, "finish": 1722434006.2573, "ip": "", "conv_id": "92d6ea56d02d400797b34378bfcc7b1d", "model_name": "mixedbread-ai/mxbai-embed-large-v1", "prompt": "what does it mean when someone says everything is relative?", "output": [["what does it mean when someone says everything is relative?", "Physics Stackexchange\n\nQ: What does relative to something mean? I just started learning about vector components and relative motion. I don't understand what relative to something means. I looked online but none of the explanations are helpful. \nIf someone could give me a very simple explanation, it would be appreciated.\n\nA: Imagine that you are on a train, traveling at a steady speed of 50 miles per hour (mph). Your physics textbook on the table in front of you.\nNow, you and the textbook (and the train) are all moving at the same speed.  To an outside observer standing next to the train tracks, you and the book are each rushing by at 50mph.  But, from your point of view, the book isn't moving at all.  That is, it's not getting closer to or farther from you.\n\n\n*\n\n*You are moving at 50mph relative to the observer next to the tracks.\n\n*You are not moving, relative to the textbook.\n\n*The book, the train, and yourself are not moving at all, relative to each other.\n\n*Relative to the train, the ground is moving by at 50mph.\n\n"]], "corpus": "stackexchange"}
+{"tstamp": 1722434006.2573, "task_type": "retrieval", "type": "chat", "model": "voyage-multilingual-2", "gen_params": {}, "start": 1722434004.1172, "finish": 1722434006.2573, "ip": "", "conv_id": "e2c9c86dbfc94f23bd227a9fc821d46d", "model_name": "voyage-multilingual-2", "prompt": "what does it mean when someone says everything is relative?", "output": [["what does it mean when someone says everything is relative?", "Physics Stackexchange\n\nQ: What does relative to something mean? I just started learning about vector components and relative motion. I don't understand what relative to something means. I looked online but none of the explanations are helpful. \nIf someone could give me a very simple explanation, it would be appreciated.\n\nA: Imagine that you are on a train, traveling at a steady speed of 50 miles per hour (mph). Your physics textbook on the table in front of you.\nNow, you and the textbook (and the train) are all moving at the same speed.  To an outside observer standing next to the train tracks, you and the book are each rushing by at 50mph.  But, from your point of view, the book isn't moving at all.  That is, it's not getting closer to or farther from you.\n\n\n*\n\n*You are moving at 50mph relative to the observer next to the tracks.\n\n*You are not moving, relative to the textbook.\n\n*The book, the train, and yourself are not moving at all, relative to each other.\n\n*Relative to the train, the ground is moving by at 50mph.\n\n"]], "corpus": "stackexchange"}
+{"tstamp": 1722434028.2123, "task_type": "retrieval", "type": "chat", "model": "jinaai/jina-embeddings-v2-base-en", "gen_params": {}, "start": 1722434027.7592, "finish": 1722434028.2123, "ip": "", "conv_id": "1163ab9a31844f4cab143efdd5a4f55e", "model_name": "jinaai/jina-embeddings-v2-base-en", "prompt": "What's the first probe we sent to space?", "output": [["What's the first probe we sent to space?", "Interstellar probe\n\nProject Orion (1958–1965) Project Orion was a proposed nuclear pulse propulsion craft that would have used fission or fusion bombs to apply motive force. The design was studied during the 1950s and 1960s in the United States of America, with one variant of the craft capable of interstellar travel.Bracewell probe (1960)\nInterstellar communication via a probe, as opposed to sending an electromagnetic signal.Sanger Photon Rocket (1950s-1964)\nEugene Sanger proposed a spacecraft powered by antimatter in the 1950s. Thrust was intended to come from reflected gamma-rays produced by electron-positron annihilation.\nEnzmann starship (1964/1973)\nProposed by 1964 and examined in an October 1973 issue of Analog, the Enzmann Starship proposed using a 12,000 ton ball of frozen deuterium to power thermonuclear powered pulse propulsion. About twice as long as the Empire State Building and assembled in-orbit, the spacecraft was part of a larger project preceded by large interstellar probes and telescopic observation of target star systems.\nProject Daedalus (1973–1978)\nProject Daedalus was a proposed nuclear pulse propulsion craft that used inertial confinement fusion of small pellets within a magnetic field nozzle to provide motive force. The design was studied during the 1970s by the British Interplanetary Society, and was meant to flyby Barnard's Star in under a century from launch. Plans included mining Helium-3 from Jupiter and a pre-launch mass of over 50 thousand metric tonnes from orbit."]], "corpus": "wikipedia"}
+{"tstamp": 1722434028.2123, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722434027.7592, "finish": 1722434028.2123, "ip": "", "conv_id": "750a9e22a9a2458f9764755b4068b5b6", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "What's the first probe we sent to space?", "output": [["What's the first probe we sent to space?", "Voyager 1\n\nVoyager 1 is a space probe launched by NASA on September 5, 1977, as part of the Voyager program to study the outer Solar System and the interstellar space beyond the Sun's heliosphere. It was launched 16 days after its twin, Voyager 2. It communicates through the NASA Deep Space Network (DSN) to receive routine commands and to transmit data to Earth. Real-time distance and velocity data are provided by NASA and JPL. At a distance of  from Earth , it is the most distant human-made object from Earth. The probe made flybys of Jupiter, Saturn, and Saturn's largest moon, Titan. NASA had a choice of either doing a Pluto or Titan flyby; exploration of the moon took priority because it was known to have a substantial atmosphere. Voyager 1 studied the weather, magnetic fields, and rings of the two gas giants and was the first probe to provide detailed images of their moons."]], "corpus": "wikipedia"}

data/retrieval_side_by_side-f62bcad9-19c4-430b-a7ba-aa2bfeba99dc.jsonl

@@ -3,3 +3,4 @@
 {"tstamp": 1722410176.2348, "task_type": "retrieval", "type": "tievote", "models": ["GritLM/GritLM-7B", "BAAI/bge-large-en-v1.5"], "ip": "", "0_conv_id": "f7cba7820d484a6e9a535e25f2e59795", "0_model_name": "GritLM/GritLM-7B", "0_prompt": "what is a cuticle", "0_output": [["what is a cuticle", "Cuticle\n\nA cuticle (), or cuticula, is any of a variety of tough but flexible, non-mineral outer coverings of an organism, or parts of an organism, that provide protection. Various types of \"cuticle\" are non-homologous, differing in their origin, structure, function, and chemical composition.\nHuman anatomy\nIn human anatomy, \"cuticle\" can refer to several structures, but it is used in general parlance, and even by medical professionals, to refer to the thickened layer of skin surrounding fingernails and toenails (the eponychium), and to refer to the superficial layer of overlapping cells covering the hair shaft (cuticula pili), consisting of dead cells, that locks the hair into its follicle. It can also be used as a synonym for the epidermis, the outer layer of skin.\nCuticle of invertebrates\nIn zoology, the invertebrate cuticle or cuticula is a multi-layered structure outside the epidermis of many invertebrates, notably arthropods and roundworms, in which it forms an exoskeleton (see arthropod exoskeleton).\nThe main structural components of the nematode cuticle are proteins, highly cross-linked collagens and specialised insoluble proteins known as \"cuticlins\", together with glycoproteins and lipids."]], "0_corpus": "wikipedia", "1_conv_id": "502b1819fb7448ee91f9932a135d2bc2", "1_model_name": "BAAI/bge-large-en-v1.5", "1_prompt": "what is a cuticle", "1_output": [["what is a cuticle", "Cuticle\n\nA cuticle (), or cuticula, is any of a variety of tough but flexible, non-mineral outer coverings of an organism, or parts of an organism, that provide protection. Various types of \"cuticle\" are non-homologous, differing in their origin, structure, function, and chemical composition.\nHuman anatomy\nIn human anatomy, \"cuticle\" can refer to several structures, but it is used in general parlance, and even by medical professionals, to refer to the thickened layer of skin surrounding fingernails and toenails (the eponychium), and to refer to the superficial layer of overlapping cells covering the hair shaft (cuticula pili), consisting of dead cells, that locks the hair into its follicle. It can also be used as a synonym for the epidermis, the outer layer of skin.\nCuticle of invertebrates\nIn zoology, the invertebrate cuticle or cuticula is a multi-layered structure outside the epidermis of many invertebrates, notably arthropods and roundworms, in which it forms an exoskeleton (see arthropod exoskeleton).\nThe main structural components of the nematode cuticle are proteins, highly cross-linked collagens and specialised insoluble proteins known as \"cuticlins\", together with glycoproteins and lipids."]], "1_corpus": "wikipedia"}
 {"tstamp": 1722413597.7439, "task_type": "retrieval", "type": "rightvote", "models": ["jinaai/jina-embeddings-v2-base-en", "voyage-multilingual-2"], "ip": "", "0_conv_id": "c46babe33e3c40fba0b1cc820ca8384a", "0_model_name": "jinaai/jina-embeddings-v2-base-en", "0_prompt": "Which test was devised to determine whether robots can think?", "0_output": [["Which test was devised to determine whether robots can think?", "Cognitive test\n\nCognitive tests are assessments of the cognitive capabilities of humans and other animals. Tests administered to humans include various forms of IQ tests; those administered to animals include the mirror test (a test of visual self-awareness) and the T maze test (which tests learning ability). Such testing is used in psychology and psychometrics, as well as other fields studying human and animal intelligence."]], "0_corpus": "wikipedia", "1_conv_id": "b5e90ef4f21148029ef2fc7495e295fb", "1_model_name": "BM25", "1_prompt": "Which test was devised to determine whether robots can think?", "1_output": [["Which test was devised to determine whether robots can think?", "Artificial intelligence\n\nIn the late teens and early 2020s, AGI companies began to deliver programs that created enormous interest. In 2015, AlphaGo, developed by DeepMind, beat the world champion Go player. The program was taught only the rules of the game and developed strategy by itself. GPT-3 is a large language model that was released in 2020 by OpenAI and is capable of generating high-quality human-like text. These programs, and others, inspired an aggressive AI boom, where large companies began investing billions in AI research. According to AI Impacts, about $50 billion annually was invested in \"AI\" around 2022 in the U.S. alone and about 20% of the new U.S. Computer Science PhD graduates have specialized in \"AI\".\nAbout 800,000 \"AI\"-related U.S. job openings existed in 2022.\nPhilosophy\nDefining artificial intelligence\nAlan Turing wrote in 1950 \"I propose to consider the question 'can machines think'?\" He advised changing the question from whether a machine \"thinks\", to \"whether or not it is possible for machinery to show intelligent behaviour\". He devised the Turing test, which measures the ability of a machine to simulate human conversation. Since we can only observe the behavior of the machine, it does not matter if it is \"actually\" thinking or literally has a \"mind\". Turing notes that we can not determine these things about other people but \"it is usual to have a polite convention that everyone thinks.\""]], "1_corpus": "wikipedia"}
 {"tstamp": 1722432375.9194, "task_type": "retrieval", "type": "tievote", "models": ["jinaai/jina-embeddings-v2-base-en", "BAAI/bge-large-en-v1.5"], "ip": "", "0_conv_id": "16bc3d67d1af469a9cc0ee66d974af5a", "0_model_name": "jinaai/jina-embeddings-v2-base-en", "0_prompt": "What is cosine similarity?", "0_output": [["What is cosine similarity?", "Cosine similarity\n\nIn data analysis, cosine similarity is a measure of similarity between two non-zero vectors defined in an inner product space. Cosine similarity is the cosine of the angle between the vectors; that is, it is the dot product of the vectors divided by the product of their lengths. It follows that the cosine similarity does not depend on the magnitudes of the vectors, but only on their angle. The cosine similarity always belongs to the interval  For example, two proportional vectors have a cosine similarity of 1, two orthogonal vectors have a similarity of 0, and two opposite vectors have a similarity of -1. In some contexts, the component values of the vectors cannot be negative, in which case the cosine similarity is bounded in .\nFor example, in information retrieval and text mining, each word is assigned a different coordinate and a document is represented by the vector of the numbers of occurrences of each word in the document. Cosine similarity then gives a useful measure of how similar two documents are likely to be, in terms of their subject matter, and independently of the length of the documents.\nThe technique is also used to measure cohesion within clusters in the field of data mining.\nOne advantage of cosine similarity is its low complexity, especially for sparse vectors: only the non-zero coordinates need to be considered.\nOther names for cosine similarity include Orchini similarity and Tucker coefficient of congruence; the Otsuka–Ochiai similarity (see below) is cosine similarity applied to binary data."]], "0_corpus": "wikipedia", "1_conv_id": "2ee5241754c8451bb390c3a4c4064166", "1_model_name": "BAAI/bge-large-en-v1.5", "1_prompt": "What is cosine similarity?", "1_output": [["What is cosine similarity?", "Cosine similarity\n\nIn data analysis, cosine similarity is a measure of similarity between two non-zero vectors defined in an inner product space. Cosine similarity is the cosine of the angle between the vectors; that is, it is the dot product of the vectors divided by the product of their lengths. It follows that the cosine similarity does not depend on the magnitudes of the vectors, but only on their angle. The cosine similarity always belongs to the interval  For example, two proportional vectors have a cosine similarity of 1, two orthogonal vectors have a similarity of 0, and two opposite vectors have a similarity of -1. In some contexts, the component values of the vectors cannot be negative, in which case the cosine similarity is bounded in .\nFor example, in information retrieval and text mining, each word is assigned a different coordinate and a document is represented by the vector of the numbers of occurrences of each word in the document. Cosine similarity then gives a useful measure of how similar two documents are likely to be, in terms of their subject matter, and independently of the length of the documents.\nThe technique is also used to measure cohesion within clusters in the field of data mining.\nOne advantage of cosine similarity is its low complexity, especially for sparse vectors: only the non-zero coordinates need to be considered.\nOther names for cosine similarity include Orchini similarity and Tucker coefficient of congruence; the Otsuka–Ochiai similarity (see below) is cosine similarity applied to binary data."]], "1_corpus": "wikipedia"}
+{"tstamp": 1722434050.2945, "task_type": "retrieval", "type": "leftvote", "models": ["jinaai/jina-embeddings-v2-base-en", "BAAI/bge-large-en-v1.5"], "ip": "", "0_conv_id": "1163ab9a31844f4cab143efdd5a4f55e", "0_model_name": "jinaai/jina-embeddings-v2-base-en", "0_prompt": "What's the first probe we sent to space?", "0_output": [["What's the first probe we sent to space?", "Interstellar probe\n\nProject Orion (1958–1965) Project Orion was a proposed nuclear pulse propulsion craft that would have used fission or fusion bombs to apply motive force. The design was studied during the 1950s and 1960s in the United States of America, with one variant of the craft capable of interstellar travel.Bracewell probe (1960)\nInterstellar communication via a probe, as opposed to sending an electromagnetic signal.Sanger Photon Rocket (1950s-1964)\nEugene Sanger proposed a spacecraft powered by antimatter in the 1950s. Thrust was intended to come from reflected gamma-rays produced by electron-positron annihilation.\nEnzmann starship (1964/1973)\nProposed by 1964 and examined in an October 1973 issue of Analog, the Enzmann Starship proposed using a 12,000 ton ball of frozen deuterium to power thermonuclear powered pulse propulsion. About twice as long as the Empire State Building and assembled in-orbit, the spacecraft was part of a larger project preceded by large interstellar probes and telescopic observation of target star systems.\nProject Daedalus (1973–1978)\nProject Daedalus was a proposed nuclear pulse propulsion craft that used inertial confinement fusion of small pellets within a magnetic field nozzle to provide motive force. The design was studied during the 1970s by the British Interplanetary Society, and was meant to flyby Barnard's Star in under a century from launch. Plans included mining Helium-3 from Jupiter and a pre-launch mass of over 50 thousand metric tonnes from orbit."]], "0_corpus": "wikipedia", "1_conv_id": "750a9e22a9a2458f9764755b4068b5b6", "1_model_name": "BAAI/bge-large-en-v1.5", "1_prompt": "What's the first probe we sent to space?", "1_output": [["What's the first probe we sent to space?", "Voyager 1\n\nVoyager 1 is a space probe launched by NASA on September 5, 1977, as part of the Voyager program to study the outer Solar System and the interstellar space beyond the Sun's heliosphere. It was launched 16 days after its twin, Voyager 2. It communicates through the NASA Deep Space Network (DSN) to receive routine commands and to transmit data to Earth. Real-time distance and velocity data are provided by NASA and JPL. At a distance of  from Earth , it is the most distant human-made object from Earth. The probe made flybys of Jupiter, Saturn, and Saturn's largest moon, Titan. NASA had a choice of either doing a Pluto or Titan flyby; exploration of the moon took priority because it was known to have a substantial atmosphere. Voyager 1 studied the weather, magnetic fields, and rings of the two gas giants and was the first probe to provide detailed images of their moons."]], "1_corpus": "wikipedia"}