Scheduled Commit

data/retrieval_individual-ffd1dcbf-aab7-4cd1-bfa8-5b0d8404144b.jsonl

@@ -62,3 +62,6 @@
 {"tstamp": 1732689039.1721, "task_type": "retrieval", "type": "chat", "model": "nomic-ai/nomic-embed-text-v1.5", "gen_params": {}, "start": 1732689038.823, "finish": 1732689039.1721, "ip": "", "conv_id": "e96927232584469d9d3c3c3fe9884700", "model_name": "nomic-ai/nomic-embed-text-v1.5", "prompt": "Who is Albert Einstein?", "output": [["Who is Albert Einstein?", "Albert Einstein\n\nAlbert Einstein ( ; ; 14 March 1879 – 18 April 1955) was a German-born theoretical physicist who is widely held as one of the most influential scientists. Best known for developing the theory of relativity, Einstein also made important contributions to quantum mechanics. His mass–energy equivalence formula , which arises from relativity theory, has been called \"the world's most famous equation\". He received the 1921 Nobel Prize in Physics \"for his services to theoretical physics, and especially for his discovery of the law of the photoelectric effect\", a pivotal step in the development of quantum theory. His intellectual achievements and originality have made the word Einstein broadly synonymous with genius."]], "corpus": "wikipedia"}
 {"tstamp": 1732689146.7535, "task_type": "retrieval", "type": "chat", "model": "Alibaba-NLP/gte-Qwen2-7B-instruct", "gen_params": {}, "start": 1732689144.5718, "finish": 1732689146.7535, "ip": "", "conv_id": "b8382d8ce29642dea0ed258fbc081ad0", "model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "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": 1732689146.7535, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1732689144.5718, "finish": 1732689146.7535, "ip": "", "conv_id": "e9e9e65907474740a0797bc424efa332", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "Which test was devised to determine whether robots can think?", "output": [["Which test was devised to determine whether robots can think?", "Artificial general intelligence\n\nMany interdisciplinary approaches (e.g. cognitive science, computational intelligence, and decision making) consider additional traits such as imagination (the ability to form novel mental images and concepts) and autonomy.\nComputer-based systems that exhibit many of these capabilities exist (e.g. see computational creativity, automated reasoning, decision support system, robot, evolutionary computation, intelligent agent). However, no consensus holds that modern AI systems possess them to an adequate degree.\nPhysical traits\nOther capabilities are considered desirable in intelligent systems, as they may affect intelligence or aid in its expression. These include:\nthe ability to sense (e.g. see, hear, etc.), and\nthe ability to act (e.g. move and manipulate objects, change location to explore, etc.)\nThis includes the ability to detect and respond to hazard.\nTests for human-level AGI\nSeveral tests meant to confirm human-level AGI have been considered, including:\nThe Turing Test (Turing)\nA machine and a human both converse unseen with a second human, who must evaluate which of the two is the machine, which passes the test if it can fool the evaluator a significant fraction of the time. Note: Turing does not prescribe what should qualify as intelligence, only that knowing that it is a machine should disqualify it. The AI Eugene Goostman, imitating a 13-year-old boy, achieved Turing's estimate of convincing 33% of judges that it was human in 2014.\nThe Robot College Student Test (Goertzel)"]], "corpus": "wikipedia"}
+{"tstamp": 1732689237.6226, "task_type": "retrieval", "type": "chat", "model": "Alibaba-NLP/gte-Qwen2-7B-instruct", "gen_params": {}, "start": 1732689237.4473, "finish": 1732689237.6226, "ip": "", "conv_id": "4d55591f656c4ae1900477c7504df8dd", "model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "prompt": "哪个测试能够决定机器人是否能思考", "output": [["哪个测试能够决定机器人是否能思考", "Turing test\n\nThe Chinese room John Searle's 1980 paper Minds, Brains, and Programs proposed the \"Chinese room\" thought experiment and argued that the Turing test could not be used to determine if a machine could think. Searle noted that software (such as ELIZA) could pass the Turing test simply by manipulating symbols of which they had no understanding. Without understanding, they could not be described as \"thinking\" in the same sense people did. Therefore, Searle concluded, the Turing test could not prove that machines could think. Much like the Turing test itself, Searle's argument has been both widely criticised and endorsed.\nArguments such as Searle's and others working on the philosophy of mind sparked off a more intense debate about the nature of intelligence, the possibility of machines with a conscious mind and the value of the Turing test that continued through the 1980s and 1990s.\nLoebner Prize\nThe Loebner Prize provides an annual platform for practical Turing tests with the first competition held in November 1991. It is underwritten by Hugh Loebner. The Cambridge Center for Behavioral Studies in Massachusetts, United States, organised the prizes up to and including the 2003 contest. As Loebner described it, one reason the competition was created is to advance the state of AI research, at least in part, because no one had taken steps to implement the Turing test despite 40 years of discussing it."]], "corpus": "wikipedia"}
+{"tstamp": 1732689237.6226, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1732689237.4473, "finish": 1732689237.6226, "ip": "", "conv_id": "2c9727365bec4b1ebed12241f1df823f", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "哪个测试能够决定机器人是否能思考", "output": [["哪个测试能够决定机器人是否能思考", "List of airports by IATA airport code: S\n\nS"]], "corpus": "wikipedia"}
+{"tstamp": 1732689410.9514, "task_type": "retrieval", "type": "chat", "model": "Alibaba-NLP/gte-Qwen2-7B-instruct", "gen_params": {}, "start": 1732689410.7068, "finish": 1732689410.9514, "ip": "", "conv_id": "f9fc09e69c4d4b4187b274c83a40a132", "model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "prompt": "I am looking for a paper to help me deal with data constraints as I scale up my language model.", "output": [["I am looking for a paper to help me deal with data constraints as I scale up my language model.", "Title: Scaling Laws for Neural Language Models\n\nAbstract: We study empirical scaling laws for language model performance on the cross-entropy loss. The loss scales as a power-law with model size, dataset size, and the amount of compute used for training, with some trends spanning more than seven orders of magnitude. Other architectural details such as network width or depth have minimal effects within a wide range. Simple equations govern the dependence of overfitting on model/dataset size and the dependence of training speed on model size. These relationships allow us to determine the optimal allocation of a fixed compute budget. Larger models are significantly more sample-efficient, such that optimally compute-efficient training involves training very large models on a relatively modest amount of data and stopping significantly before convergence."]], "corpus": "arxiv"}

data/retrieval_side_by_side-ffd1dcbf-aab7-4cd1-bfa8-5b0d8404144b.jsonl

@@ -1,3 +1,4 @@
 {"tstamp": 1732670639.2808, "task_type": "retrieval", "type": "rightvote", "models": ["text-embedding-004", "text-embedding-3-large"], "ip": "", "0_conv_id": "8406316360bf4f38b060381254c59aad", "0_model_name": "text-embedding-004", "0_prompt": "O que é direito constitucional?", "0_output": [["O que é direito constitucional?", "Constitutional right\n\nA constitutional right can be a prerogative or a duty, a power or a restraint of power, recognized and established by a sovereign state or union of states. Constitutional rights may be expressly stipulated in a national constitution, or they may be inferred from the language of a national constitution, which is the supreme law of the land, meaning that laws that contradict it are considered unconstitutional and invalid. Usually any constitution defines the structure, functions, powers, and limits of the national government and the individual freedoms, rights, and obligations which will be protected and enforced when needed by the national authorities. Nowadays, most countries have a written constitution comprising similar or distinct constitutional rights."]], "0_corpus": "wikipedia", "1_conv_id": "5f4c1b224da4430d8e267054408a5e3c", "1_model_name": "text-embedding-3-large", "1_prompt": "O que é direito constitucional?", "1_output": [["O que é direito constitucional?", "Constitutional law\n\nConstitutional law is a body of law which defines the role, powers, and structure of different entities within a state, namely, the executive, the parliament or legislature, and the judiciary; as well as the basic rights of citizens and, in federal countries such as the United States and Canada, the relationship between the central government and state, provincial, or territorial governments.\nNot all nation states have codified constitutions, though all such states have a , or law of the land, that may consist of a variety of imperative and consensual rules. These may include customary law, conventions, statutory law, judge-made law, or international rules and norms. Constitutional law deals with the fundamental principles by which the government exercises its authority. In some instances, these principles grant specific powers to the government, such as the power to tax and spend for the welfare of the population. Other times, constitutional principles act to place limits on what the government can do, such as prohibiting the arrest of an individual without sufficient cause."]], "1_corpus": "wikipedia"}
 {"tstamp": 1732670781.2397, "task_type": "retrieval", "type": "share", "models": ["BM25", "nomic-ai/nomic-embed-text-v1.5"], "ip": "", "0_conv_id": "a253e97d3da742b484a9844394c0fec9", "0_model_name": "BM25", "0_prompt": "o que é direito constitucional?", "0_output": [["o que é direito constitucional?", "José Sócrates\n\nAdministrative reforms The XVII Governo Constitucional government, headed by Prime Minister José Sócrates, tried to create new rules and implement reforms aiming at better efficiency and rationalized resource allocation in the public sector, fighting civil servant overcapacity (excedentários) and reducing bureaucracy for both citizens and companies (e.g.: empresa na hora, PRACE – Programa de Reestruturação da Administração Central do Estado, and SIMPLEX – Programa de Simplificação Administrativa e Legislativa), among others. Since the XVII Governo Constitucional government (with José Sócrates as prime minister and Teixeira dos Santos as minister of finance) Portugal's fiscal policy improved with a steady increase of the number of taxpayers and the growth of the receipt amount from State taxation. However these policies had little effect, and the country's public debt and deficit were both out of control by 2010, along with a record high unemployment rate. João Bilhim directed in 2005 the committee responsible for the Programme for Restructuring the State's Central Administration (PRACE) but was said to be disappointed with the results. Several reforms and measures implemented in 2006/2007 by the government (XVII Governo Constitucional – headed by Prime Minister José Sócrates), resulted in improved welfare system financial sustainability but reduced income expectations of future pensioners up to 40%. In addition, economically active people must work for more years before retirement than formerly. A sustainability factor was also introduced, giving employees the option of working longer or receiving slightly lower pensions, as life expectancy forecasts increase. After the Portuguese regionalization referendum of 1998 where the \"No\" to regionalization of the mainland into eight administrative regions was victorious, the XVII Governo Constitucional government announced in January 2009 its firm intention of starting again a regionalization process for Portugal. According to this governmental project, mainland Portugal was to be regionalized into five regions with a wide range of administrative autonomy, using the already established NUTS II system: Alentejo, Algarve, Lisbon and Tagus Valley, Central Portugal and Northern Portugal. The transformation of the Portuguese public administration from a traditional one to an information technology-based multiplatform service, was praised by the European Commission through its European Union benchmark for the sector, that consecutively placed Portugal in the first position of the ranking in 2009 and 2010."]], "0_corpus": "wikipedia", "1_conv_id": "e8584951a3294d20b2dc8d7ba59ad5c2", "1_model_name": "nomic-ai/nomic-embed-text-v1.5", "1_prompt": "o que é direito constitucional?", "1_output": [["o que é direito constitucional?", "Constitution of Brazil\n\nThe Constitution of the Federative Republic of Brazil () is the supreme law of Brazil. It is the foundation and source of the legal authority underlying the existence of Brazil and the federal government of Brazil. It replaced the autocratic 1967 constitution capping 21 years of military dictatorship and establishing Brazil's 6th republic, also known as the New Republic (Nova República). Made in the light of the Brazilian transition to democracy, it resignified the role of the state in the citizens' lives, providing a vast system of human and individual rights protection, social welfare, and democratic tools.\nOverview\nThe  1988 Brazilian Constitution is the seventh enacted since the country's independence in 1822, and the sixth since the proclamation of the republic in 1889.  It was promulgated on 5 October 1988, after a two-year process in which it was written from scratch. It was revised in 2017.\nHistory\nThe current Constitution of Brazil was drafted as a reaction to the period of military dictatorship, and sought to guarantee individual rights and restrict the state's ability to limit freedom, to punish offences and to regulate individual life. Among the new constitutional guarantees are the errand of injunction and the habeas data. It also anticipated the existence of a Consumers' Defence Code (enacted in 1990), of a Children's and Youth Code (1990) and of a new Civil Code (2002)."]], "1_corpus": "wikipedia"}
 {"tstamp": 1732689195.7089, "task_type": "retrieval", "type": "tievote", "models": ["Alibaba-NLP/gte-Qwen2-7B-instruct", "BAAI/bge-large-en-v1.5"], "ip": "", "0_conv_id": "b8382d8ce29642dea0ed258fbc081ad0", "0_model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "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 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)."]], "0_corpus": "wikipedia", "1_conv_id": "e9e9e65907474740a0797bc424efa332", "1_model_name": "BAAI/bge-large-en-v1.5", "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 general intelligence\n\nMany interdisciplinary approaches (e.g. cognitive science, computational intelligence, and decision making) consider additional traits such as imagination (the ability to form novel mental images and concepts) and autonomy.\nComputer-based systems that exhibit many of these capabilities exist (e.g. see computational creativity, automated reasoning, decision support system, robot, evolutionary computation, intelligent agent). However, no consensus holds that modern AI systems possess them to an adequate degree.\nPhysical traits\nOther capabilities are considered desirable in intelligent systems, as they may affect intelligence or aid in its expression. These include:\nthe ability to sense (e.g. see, hear, etc.), and\nthe ability to act (e.g. move and manipulate objects, change location to explore, etc.)\nThis includes the ability to detect and respond to hazard.\nTests for human-level AGI\nSeveral tests meant to confirm human-level AGI have been considered, including:\nThe Turing Test (Turing)\nA machine and a human both converse unseen with a second human, who must evaluate which of the two is the machine, which passes the test if it can fool the evaluator a significant fraction of the time. Note: Turing does not prescribe what should qualify as intelligence, only that knowing that it is a machine should disqualify it. The AI Eugene Goostman, imitating a 13-year-old boy, achieved Turing's estimate of convincing 33% of judges that it was human in 2014.\nThe Robot College Student Test (Goertzel)"]], "1_corpus": "wikipedia"}
+{"tstamp": 1732689249.1193, "task_type": "retrieval", "type": "leftvote", "models": ["Alibaba-NLP/gte-Qwen2-7B-instruct", "BAAI/bge-large-en-v1.5"], "ip": "", "0_conv_id": "4d55591f656c4ae1900477c7504df8dd", "0_model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "0_prompt": "哪个测试能够决定机器人是否能思考", "0_output": [["哪个测试能够决定机器人是否能思考", "Turing test\n\nThe Chinese room John Searle's 1980 paper Minds, Brains, and Programs proposed the \"Chinese room\" thought experiment and argued that the Turing test could not be used to determine if a machine could think. Searle noted that software (such as ELIZA) could pass the Turing test simply by manipulating symbols of which they had no understanding. Without understanding, they could not be described as \"thinking\" in the same sense people did. Therefore, Searle concluded, the Turing test could not prove that machines could think. Much like the Turing test itself, Searle's argument has been both widely criticised and endorsed.\nArguments such as Searle's and others working on the philosophy of mind sparked off a more intense debate about the nature of intelligence, the possibility of machines with a conscious mind and the value of the Turing test that continued through the 1980s and 1990s.\nLoebner Prize\nThe Loebner Prize provides an annual platform for practical Turing tests with the first competition held in November 1991. It is underwritten by Hugh Loebner. The Cambridge Center for Behavioral Studies in Massachusetts, United States, organised the prizes up to and including the 2003 contest. As Loebner described it, one reason the competition was created is to advance the state of AI research, at least in part, because no one had taken steps to implement the Turing test despite 40 years of discussing it."]], "0_corpus": "wikipedia", "1_conv_id": "2c9727365bec4b1ebed12241f1df823f", "1_model_name": "BAAI/bge-large-en-v1.5", "1_prompt": "哪个测试能够决定机器人是否能思考", "1_output": [["哪个测试能够决定机器人是否能思考", "List of airports by IATA airport code: S\n\nS"]], "1_corpus": "wikipedia"}

data/retrieval_single_choice-ffd1dcbf-aab7-4cd1-bfa8-5b0d8404144b.jsonl

@@ -0,0 +1 @@
+{"tstamp": 1732689478.0167, "task_type": "retrieval", "type": "upvote", "models": "Alibaba-NLP/gte-Qwen2-7B-instruct", "ip": "", "conv_id": "f9fc09e69c4d4b4187b274c83a40a132", "model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "prompt": "I am looking for a paper to help me deal with data constraints as I scale up my language model.", "output": [["I am looking for a paper to help me deal with data constraints as I scale up my language model.", "Title: Scaling Laws for Neural Language Models\n\nAbstract: We study empirical scaling laws for language model performance on the cross-entropy loss. The loss scales as a power-law with model size, dataset size, and the amount of compute used for training, with some trends spanning more than seven orders of magnitude. Other architectural details such as network width or depth have minimal effects within a wide range. Simple equations govern the dependence of overfitting on model/dataset size and the dependence of training speed on model size. These relationships allow us to determine the optimal allocation of a fixed compute budget. Larger models are significantly more sample-efficient, such that optimally compute-efficient training involves training very large models on a relatively modest amount of data and stopping significantly before convergence."]], "corpus": "arxiv"}