Scheduled Commit

data/retrieval_battle-112c1ce1-fe57-41e6-8919-4f1859b89f91.jsonl

@@ -13,3 +13,4 @@
 {"tstamp": 1723830601.9384, "task_type": "retrieval", "type": "leftvote", "models": ["", ""], "ip": "", "0_conv_id": "0dd7707bcde94e079d00bdae3be37352", "0_model_name": "mixedbread-ai/mxbai-embed-large-v1", "0_prompt": "what is the difference between do you and did you?", "0_output": [["what is the difference between do you and did you?", "Ell Stackexchange\n\nQ: DIfferentiating between \"do\" \"does\" and \"did\" I have difficulties using do, does and did for interrogative phrases. \nIn this phrase, \n\nDoes anyone of you speaks fluently English? \n\nI want to ask if someone inside a group of people speak fluently English. Or would it be,  \n\nDo anyone of you speak English fluently? \n\nWhich one is better? How do I ask?\n\nA: A matrix of issues\nCorrect versions\n\nDoes anyone of you speak fluent English?\nDo any of you speak English fluently?\n\n"]], "0_corpus": "stackexchange", "1_conv_id": "6a894707123d495fb9820e00732d4050", "1_model_name": "jinaai/jina-embeddings-v2-base-en", "1_prompt": "what is the difference between do you and did you?", "1_output": [["what is the difference between do you and did you?", "Stackoverflow Stackexchange\n\nQ: Scala speed test and profiler I'm interested in speed test and performance of my application. For example how much time was spent to db query (I use squeryl ORM).\nAre there any plugins for Intellij-Idea IDE?\n\nA: If you are looking for plugins for Intellij-IDEA, then the YourKit profiler can be integrated into this IDE. YourKit profilers might be difficult to use to measure the exact time in a specific part of code.\nYou should consider using a microbenchmarking framework such as ScalaMeter for this. In this framework you write tests similar to unit tests, that can be run selectively to verify that the performance hasn't changed. It can be neatly integrated with SBT -- you can run it as a test.\n"]], "1_corpus": "stackexchange"}
 {"tstamp": 1723830618.0973, "task_type": "retrieval", "type": "leftvote", "models": ["", ""], "ip": "", "0_conv_id": "386c1dfe801340879423e76ae37959fd", "0_model_name": "BM25", "0_prompt": "my right click is not working in kali?", "0_output": [["my right click is not working in kali?", "Unix Stackexchange\n\nQ: Kali Linux USB Live Boot Not Working I downloaded the Kali Linux ISO 64-bit off of this page:\n\n\n*\n\n*http://www.kali.org/downloads\nThen, I used the Kali Linux Live USB Install Procedure on this page for Windows. I boot my computer from my USB drive, and I get the following screen:\n    \nI click Live (amd64), the first option. Sorry it's not the best picture. Boots well and lo and behold I get to the main screen, and for a second it appears to work:\n     \nAll is going well, but after a second my computer just reboots, and I'm back to the first picture. I do not understand what is going on! So, how do I fix this issue?\n"]], "0_corpus": "stackexchange", "1_conv_id": "d6f56f5528b44322946f88edfdd2d932", "1_model_name": "Salesforce/SFR-Embedding-2_R", "1_prompt": "my right click is not working in kali?", "1_output": [["my right click is not working in kali?", "Askubuntu Stackexchange\n\nQ: Right mouse click not working on Kubuntu 17.10 After upgrading from Kubuntu 17.04 to 17.10 I cannot right mouse click anymore on my touchpad (Lenovo T460s). Left mouse click still works.\nI have reviewed the touchpad/mouse settings, but nothing seems to relevant.\nAny idea what could cause this?\n\nA: I have the same issue on my lenovo ideapad 320e. Previously, editing /usr/share/X11/xorg.conf.d/50-synaptic.conf worked but the file is missing here altogether in ubuntu 17.10. \nAlternate solution:\nSimulate a right mouse click.\nGo to Universal Access in Settings > Go to Click assist > Switch on Simulated Secondary Click > Adjust the primary click duration to trigger right click and you're set.\nHope, it helps for the time being.\nEDIT:\nBTW Did you try double finger right click?\nJust tap on trackpad using two fingers.\n"]], "1_corpus": "stackexchange"}
 {"tstamp": 1723830637.8924, "task_type": "retrieval", "type": "leftvote", "models": ["", ""], "ip": "", "0_conv_id": "a64b1d8caf9e491cabea1c8107554598", "0_model_name": "intfloat/e5-mistral-7b-instruct", "0_prompt": "the neoclassical growth theory says in part that", "0_output": [["the neoclassical growth theory says in part that", "Endogenous growth theory\n\nVersus exogenous growth theory In neo-classical growth models, the long-run rate of growth is exogenously determined by either the savings rate (the Harrod–Domar model) or the rate of technical progress (Solow model). However, the savings rate and rate of technological progress remain unexplained. Endogenous growth theory tries to overcome this shortcoming by building macroeconomic models out of microeconomic foundations. Households are assumed to maximize utility subject to budget constraints while firms maximize profits. Crucial importance is usually given to the production of new technologies and human capital. The engine for growth can be as simple as a constant return to scale production function (the AK model) or more complicated set ups with spillover effects (spillovers are positive externalities, benefits that are attributed to costs from other firms), increasing numbers of goods, increasing qualities, etc.\nOften endogenous growth theory assumes constant marginal product of capital at the aggregate level, or at least that the limit of the marginal product of capital does not tend towards zero. This does not imply that larger firms will be more productive than small ones, because at the firm level the marginal product of capital is still diminishing. Therefore, it is possible to construct endogenous growth models with perfect competition. However, in many endogenous growth models the assumption of perfect competition is relaxed, and some degree of monopoly power is thought to exist. Generally monopoly power in these models comes from the holding of patents. These are models with two sectors, producers of final output and an R&D sector: the R&D sector develops ideas which grant them monopoly power. R&D firms are assumed to be able to make monopoly profits selling ideas to production firms, but the free entry condition means that these profits are dissipated on R&D spending."]], "0_corpus": "wikipedia", "1_conv_id": "4487003eba92422ebb0769563737b845", "1_model_name": "text-embedding-004", "1_prompt": "the neoclassical growth theory says in part that", "1_output": [["the neoclassical growth theory says in part that", "Economic growth\n\nHowever, the reinforcing interaction between the rate of technological progress and the size and composition of the population has gradually increased the pace of technological progress, enhancing the importance of education in the ability of individuals to adapt to the changing technological environment.The rise in the allocation of resources towards education triggered a fertility decline enabling economies to allocate a larger share of the fruits of technological progress to a steady increase in income per capita, rather than towards the growth of population, paving the way for the emergence of sustained economic growth. The theory further suggests that variations in biogeographical characteristics, as well as cultural and institutional characteristics, have generated a differential pace of transition from stagnation to growth across countries and consequently divergence in their income per capita over the past two centuries. Inequality and growth\nTheories\nThe prevailing views about the role of inequality in the growth process has radically shifted in the past century. The classical perspective, as expressed by Adam Smith, and others, suggests that inequality fosters the growth process. "]], "1_corpus": "wikipedia"}
+{"tstamp": 1723835653.9947, "task_type": "retrieval", "type": "rightvote", "models": ["", ""], "ip": "", "0_conv_id": "f985dd54db3741639850f2bbf7a4a6e6", "0_model_name": "nomic-ai/nomic-embed-text-v1.5", "0_prompt": "what I want to learn more about the intersection of parallel infinites and np-hard problems", "0_output": [["what I want to learn more about the intersection of parallel infinites and np-hard problems", "NP-hardness\n\nIn computational complexity theory, a computational problem H is called NP-hard if, for  every problem L which can be solved in non-deterministic polynomial-time, there is a polynomial-time reduction from L to H. That is, assuming a solution for H takes 1 unit time, Hs solution can be used to solve L in polynomial time. As a consequence, finding a polynomial time algorithm to solve a single NP-hard problem would give polynomial time algorithms for all the problems in the complexity class NP. As it is suspected, but unproven, that P≠NP, it is unlikely that any polynomial-time algorithms for NP-hard problems exist.\nA simple example of an NP-hard problem is the subset sum problem.\nInformally, if H is NP-hard, then it is at least as difficult to solve as the problems in NP. However, the opposite direction is not true: some problems are undecidable, and therefore even more difficult to solve than all problems in NP, but they are provably not NP-hard (unless P=NP)."]], "0_corpus": "wikipedia", "1_conv_id": "87ee16bd3ee44846a9022579d0e11189", "1_model_name": "intfloat/multilingual-e5-large-instruct", "1_prompt": "what I want to learn more about the intersection of parallel infinites and np-hard problems", "1_output": [["what I want to learn more about the intersection of parallel infinites and np-hard problems", "Computational complexity theory\n\nProblems in NP not known to be in P or NP-complete\nIt was shown by Ladner that if P ≠ NP then there exist problems in NP that are neither in P nor NP-complete. Such problems are called NP-intermediate problems. The graph isomorphism problem, the discrete logarithm problem and the integer factorization problem are examples of problems believed to be NP-intermediate. They are some of the very few NP problems not known to be in P or to be NP-complete.\nThe graph isomorphism problem is the computational problem of determining whether two finite graphs are isomorphic. An important unsolved problem in complexity theory is whether the graph isomorphism problem is in P, NP-complete, or NP-intermediate. The answer is not known, but it is believed that the problem is at least not NP-complete. If graph isomorphism is NP-complete, the polynomial time hierarchy collapses to its second level. Since it is widely believed that the polynomial hierarchy does not collapse to any finite level, it is believed that graph isomorphism is not NP-complete. The best algorithm for this problem, due to László Babai and Eugene Luks has run time  for graphs with n vertices, although some recent work by Babai offers some potentially new perspectives on this."]], "1_corpus": "wikipedia"}

data/retrieval_individual-112c1ce1-fe57-41e6-8919-4f1859b89f91.jsonl

@@ -52,3 +52,5 @@
 {"tstamp": 1723830607.6817, "task_type": "retrieval", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1723830606.0979, "finish": 1723830607.6817, "ip": "", "conv_id": "d6f56f5528b44322946f88edfdd2d932", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": "my right click is not working in kali?", "output": [["my right click is not working in kali?", "Askubuntu Stackexchange\n\nQ: Right mouse click not working on Kubuntu 17.10 After upgrading from Kubuntu 17.04 to 17.10 I cannot right mouse click anymore on my touchpad (Lenovo T460s). Left mouse click still works.\nI have reviewed the touchpad/mouse settings, but nothing seems to relevant.\nAny idea what could cause this?\n\nA: I have the same issue on my lenovo ideapad 320e. Previously, editing /usr/share/X11/xorg.conf.d/50-synaptic.conf worked but the file is missing here altogether in ubuntu 17.10. \nAlternate solution:\nSimulate a right mouse click.\nGo to Universal Access in Settings > Go to Click assist > Switch on Simulated Secondary Click > Adjust the primary click duration to trigger right click and you're set.\nHope, it helps for the time being.\nEDIT:\nBTW Did you try double finger right click?\nJust tap on trackpad using two fingers.\n"]], "corpus": "stackexchange"}
 {"tstamp": 1723830624.2744, "task_type": "retrieval", "type": "chat", "model": "intfloat/e5-mistral-7b-instruct", "gen_params": {}, "start": 1723830621.962, "finish": 1723830624.2744, "ip": "", "conv_id": "a64b1d8caf9e491cabea1c8107554598", "model_name": "intfloat/e5-mistral-7b-instruct", "prompt": "the neoclassical growth theory says in part that", "output": [["the neoclassical growth theory says in part that", "Endogenous growth theory\n\nVersus exogenous growth theory In neo-classical growth models, the long-run rate of growth is exogenously determined by either the savings rate (the Harrod–Domar model) or the rate of technical progress (Solow model). However, the savings rate and rate of technological progress remain unexplained. Endogenous growth theory tries to overcome this shortcoming by building macroeconomic models out of microeconomic foundations. Households are assumed to maximize utility subject to budget constraints while firms maximize profits. Crucial importance is usually given to the production of new technologies and human capital. The engine for growth can be as simple as a constant return to scale production function (the AK model) or more complicated set ups with spillover effects (spillovers are positive externalities, benefits that are attributed to costs from other firms), increasing numbers of goods, increasing qualities, etc.\nOften endogenous growth theory assumes constant marginal product of capital at the aggregate level, or at least that the limit of the marginal product of capital does not tend towards zero. This does not imply that larger firms will be more productive than small ones, because at the firm level the marginal product of capital is still diminishing. Therefore, it is possible to construct endogenous growth models with perfect competition. However, in many endogenous growth models the assumption of perfect competition is relaxed, and some degree of monopoly power is thought to exist. Generally monopoly power in these models comes from the holding of patents. These are models with two sectors, producers of final output and an R&D sector: the R&D sector develops ideas which grant them monopoly power. R&D firms are assumed to be able to make monopoly profits selling ideas to production firms, but the free entry condition means that these profits are dissipated on R&D spending."]], "corpus": "wikipedia"}
 {"tstamp": 1723830624.2744, "task_type": "retrieval", "type": "chat", "model": "text-embedding-004", "gen_params": {}, "start": 1723830621.962, "finish": 1723830624.2744, "ip": "", "conv_id": "4487003eba92422ebb0769563737b845", "model_name": "text-embedding-004", "prompt": "the neoclassical growth theory says in part that", "output": [["the neoclassical growth theory says in part that", "Economic growth\n\nHowever, the reinforcing interaction between the rate of technological progress and the size and composition of the population has gradually increased the pace of technological progress, enhancing the importance of education in the ability of individuals to adapt to the changing technological environment.The rise in the allocation of resources towards education triggered a fertility decline enabling economies to allocate a larger share of the fruits of technological progress to a steady increase in income per capita, rather than towards the growth of population, paving the way for the emergence of sustained economic growth. The theory further suggests that variations in biogeographical characteristics, as well as cultural and institutional characteristics, have generated a differential pace of transition from stagnation to growth across countries and consequently divergence in their income per capita over the past two centuries. Inequality and growth\nTheories\nThe prevailing views about the role of inequality in the growth process has radically shifted in the past century. The classical perspective, as expressed by Adam Smith, and others, suggests that inequality fosters the growth process. "]], "corpus": "wikipedia"}
+{"tstamp": 1723835630.4795, "task_type": "retrieval", "type": "chat", "model": "nomic-ai/nomic-embed-text-v1.5", "gen_params": {}, "start": 1723835628.2544, "finish": 1723835630.4795, "ip": "", "conv_id": "f985dd54db3741639850f2bbf7a4a6e6", "model_name": "nomic-ai/nomic-embed-text-v1.5", "prompt": "what I want to learn more about the intersection of parallel infinites and np-hard problems", "output": [["what I want to learn more about the intersection of parallel infinites and np-hard problems", "NP-hardness\n\nIn computational complexity theory, a computational problem H is called NP-hard if, for  every problem L which can be solved in non-deterministic polynomial-time, there is a polynomial-time reduction from L to H. That is, assuming a solution for H takes 1 unit time, Hs solution can be used to solve L in polynomial time. As a consequence, finding a polynomial time algorithm to solve a single NP-hard problem would give polynomial time algorithms for all the problems in the complexity class NP. As it is suspected, but unproven, that P≠NP, it is unlikely that any polynomial-time algorithms for NP-hard problems exist.\nA simple example of an NP-hard problem is the subset sum problem.\nInformally, if H is NP-hard, then it is at least as difficult to solve as the problems in NP. However, the opposite direction is not true: some problems are undecidable, and therefore even more difficult to solve than all problems in NP, but they are provably not NP-hard (unless P=NP)."]], "corpus": "wikipedia"}
+{"tstamp": 1723835630.4795, "task_type": "retrieval", "type": "chat", "model": "intfloat/multilingual-e5-large-instruct", "gen_params": {}, "start": 1723835628.2544, "finish": 1723835630.4795, "ip": "", "conv_id": "87ee16bd3ee44846a9022579d0e11189", "model_name": "intfloat/multilingual-e5-large-instruct", "prompt": "what I want to learn more about the intersection of parallel infinites and np-hard problems", "output": [["what I want to learn more about the intersection of parallel infinites and np-hard problems", "Computational complexity theory\n\nProblems in NP not known to be in P or NP-complete\nIt was shown by Ladner that if P ≠ NP then there exist problems in NP that are neither in P nor NP-complete. Such problems are called NP-intermediate problems. The graph isomorphism problem, the discrete logarithm problem and the integer factorization problem are examples of problems believed to be NP-intermediate. They are some of the very few NP problems not known to be in P or to be NP-complete.\nThe graph isomorphism problem is the computational problem of determining whether two finite graphs are isomorphic. An important unsolved problem in complexity theory is whether the graph isomorphism problem is in P, NP-complete, or NP-intermediate. The answer is not known, but it is believed that the problem is at least not NP-complete. If graph isomorphism is NP-complete, the polynomial time hierarchy collapses to its second level. Since it is widely believed that the polynomial hierarchy does not collapse to any finite level, it is believed that graph isomorphism is not NP-complete. The best algorithm for this problem, due to László Babai and Eugene Luks has run time  for graphs with n vertices, although some recent work by Babai offers some potentially new perspectives on this."]], "corpus": "wikipedia"}

data/retrieval_side_by_side-112c1ce1-fe57-41e6-8919-4f1859b89f91.jsonl

@@ -1 +1,3 @@
 {"tstamp": 1723770965.3468, "task_type": "retrieval", "type": "bothbadvote", "models": ["intfloat/e5-mistral-7b-instruct", "BAAI/bge-large-en-v1.5"], "ip": "", "0_conv_id": "a4a782ecf33645c88dd3bb620d3eb0b8", "0_model_name": "intfloat/e5-mistral-7b-instruct", "0_prompt": "西新潟中央病院の院長", "0_output": [["西新潟中央病院の院長", "List of university hospitals\n\nKitasato University Hospital w:ja:北里大学病院 National Defense Medical College Hospital w:ja:防衛医科大学校病院\nNihon University Itabashi Hospital w:ja:日本大学医学部附属板橋病院\nSt. Marianna University School of Medicine Hospital w:ja:聖マリアンナ医科大学病院\nThe University of Tokyo Hospital w:ja:東京大学医学部附属病院\nTokai University Hospital w:ja:東海大学医学部付属病院\nTokyo Medical And Dental University Dental Hospital w:ja:東京医科歯科大学歯学部附属病院\nTokyo Medical And Dental University Medical Hospital w:ja:東京医科歯科大学医学部附属病院\nTokyo Medical University Hospital w:ja:東京医科大学病院\nUniversity of Tsukuba Hospital w:ja:筑波大学附属病院\nYokohama City University Hospital w:ja:横浜市立大学附属病院\nTōkai and Hokuriku\nNagoya University Hospital w:ja:名古屋大学医学部附属病院\nNagoya City University Hospital w:ja:名古屋市立大学病院\nGifu University Hospital w:ja:岐阜大学医学部附属病院\nKinki\nKyoto University Hospital w:ja:京都大学医学部附属病院\nKyoto Prefectural University of Medicine Hospital w:ja:京都府立医科大学附属病院\nUniversity of Fukui Hospital w:ja:福井大学医学部附属病院\nOsaka University Hospital w:ja:大阪大学医学部附属病院\nOsaka University Dental Hospital w:ja:大阪大学歯学部附属病院\nOsaka City University Hospital w:ja:大阪市立大学医学部附属病院\nKindai University Hospital w:ja:近畿大学医学部附属病院\nWakayama Medical University Hospital w:ja:和歌山県立医科大学附属病院\nChugoku and Shikoku\nKagawa University Hospital w:ja:香川大学医学部附属病院\nOkayama University Hospital w:ja:岡山大学病院\nTokushima University Hospital w:ja:徳島大学病院\nKyūshū\nKagoshima University Hospital w:ja:鹿児島大学病院\nKumamoto University Hospital w:ja:熊本大学医学部附属病院\nKurume University Hospital w:ja:久留米大学病院\nKyūshū University Hospital w:ja:九州大学病院\nNagasaki University Hospital w:ja:長崎大学病院\nSaga University Hospital w:ja:佐賀大学医学部附属病院\nJordan\nKing Abdullah University Hospital, Irbid\nUniversity of Jordan Hospital, Amman\nKenya\nAga Khan University Hospital, Nairobi\nLatvia\nRiga Eastern University Hospital, Riga\nPauls Stradins Clinical University Hospital, Riga\nChildren's Clinical University Hospital, Riga\nLebanon\nSaint Georges Hospital - University Medical Center - Saint George University of Beirut – Beirut"]], "0_corpus": "wikipedia", "1_conv_id": "8f07dd46447b4393afcd6d2bb4fe82e5", "1_model_name": "BAAI/bge-large-en-v1.5", "1_prompt": "西新潟中央病院の院長", "1_output": [["西新潟中央病院の院長", "Cho Jung-tai\n\nCho Jung-tai (; born 22 January 1959) is a Taiwanese politician who is the premier of the Republic of China. He served on the Taipei City Council from 1990 to 1998, when he was first elected to the Legislative Yuan. Cho remained a legislator through 2004, when he was appointed deputy secretary-general to the president during the Chen Shui-bian administration. During Frank Hsieh's 2008 presidential bid, Cho assumed the post of Secretary-General of the Democratic Progressive Party. He returned to public service in 2017, as secretary-general of the Executive Yuan under Premier William Lai. In 2019, Cho succeeded Tsai Ing-wen as leader of the Democratic Progressive Party. He remained leader of the party until May 2020, when Tsai resumed the role.\nEarly life and education\nCho was born in Taipei, Taiwan. He obtained his bachelor's degree in law from National Chung Hsing University."]], "1_corpus": "wikipedia"}
+{"tstamp": 1723835646.5349, "task_type": "retrieval", "type": "share", "models": ["### Model A: nomic-ai/nomic-embed-text-v1.5", "### Model B: intfloat/multilingual-e5-large-instruct"], "ip": "", "0_conv_id": "f985dd54db3741639850f2bbf7a4a6e6", "0_model_name": "nomic-ai/nomic-embed-text-v1.5", "0_prompt": "what I want to learn more about the intersection of parallel infinites and np-hard problems", "0_output": [["what I want to learn more about the intersection of parallel infinites and np-hard problems", "NP-hardness\n\nIn computational complexity theory, a computational problem H is called NP-hard if, for  every problem L which can be solved in non-deterministic polynomial-time, there is a polynomial-time reduction from L to H. That is, assuming a solution for H takes 1 unit time, Hs solution can be used to solve L in polynomial time. As a consequence, finding a polynomial time algorithm to solve a single NP-hard problem would give polynomial time algorithms for all the problems in the complexity class NP. As it is suspected, but unproven, that P≠NP, it is unlikely that any polynomial-time algorithms for NP-hard problems exist.\nA simple example of an NP-hard problem is the subset sum problem.\nInformally, if H is NP-hard, then it is at least as difficult to solve as the problems in NP. However, the opposite direction is not true: some problems are undecidable, and therefore even more difficult to solve than all problems in NP, but they are provably not NP-hard (unless P=NP)."]], "0_corpus": "wikipedia", "1_conv_id": "87ee16bd3ee44846a9022579d0e11189", "1_model_name": "intfloat/multilingual-e5-large-instruct", "1_prompt": "what I want to learn more about the intersection of parallel infinites and np-hard problems", "1_output": [["what I want to learn more about the intersection of parallel infinites and np-hard problems", "Computational complexity theory\n\nProblems in NP not known to be in P or NP-complete\nIt was shown by Ladner that if P ≠ NP then there exist problems in NP that are neither in P nor NP-complete. Such problems are called NP-intermediate problems. The graph isomorphism problem, the discrete logarithm problem and the integer factorization problem are examples of problems believed to be NP-intermediate. They are some of the very few NP problems not known to be in P or to be NP-complete.\nThe graph isomorphism problem is the computational problem of determining whether two finite graphs are isomorphic. An important unsolved problem in complexity theory is whether the graph isomorphism problem is in P, NP-complete, or NP-intermediate. The answer is not known, but it is believed that the problem is at least not NP-complete. If graph isomorphism is NP-complete, the polynomial time hierarchy collapses to its second level. Since it is widely believed that the polynomial hierarchy does not collapse to any finite level, it is believed that graph isomorphism is not NP-complete. The best algorithm for this problem, due to László Babai and Eugene Luks has run time  for graphs with n vertices, although some recent work by Babai offers some potentially new perspectives on this."]], "1_corpus": "wikipedia"}
+{"tstamp": 1723835647.9876, "task_type": "retrieval", "type": "share", "models": ["### Model A: nomic-ai/nomic-embed-text-v1.5", "### Model B: intfloat/multilingual-e5-large-instruct"], "ip": "", "0_conv_id": "f985dd54db3741639850f2bbf7a4a6e6", "0_model_name": "nomic-ai/nomic-embed-text-v1.5", "0_prompt": "what I want to learn more about the intersection of parallel infinites and np-hard problems", "0_output": [["what I want to learn more about the intersection of parallel infinites and np-hard problems", "NP-hardness\n\nIn computational complexity theory, a computational problem H is called NP-hard if, for  every problem L which can be solved in non-deterministic polynomial-time, there is a polynomial-time reduction from L to H. That is, assuming a solution for H takes 1 unit time, Hs solution can be used to solve L in polynomial time. As a consequence, finding a polynomial time algorithm to solve a single NP-hard problem would give polynomial time algorithms for all the problems in the complexity class NP. As it is suspected, but unproven, that P≠NP, it is unlikely that any polynomial-time algorithms for NP-hard problems exist.\nA simple example of an NP-hard problem is the subset sum problem.\nInformally, if H is NP-hard, then it is at least as difficult to solve as the problems in NP. However, the opposite direction is not true: some problems are undecidable, and therefore even more difficult to solve than all problems in NP, but they are provably not NP-hard (unless P=NP)."]], "0_corpus": "wikipedia", "1_conv_id": "87ee16bd3ee44846a9022579d0e11189", "1_model_name": "intfloat/multilingual-e5-large-instruct", "1_prompt": "what I want to learn more about the intersection of parallel infinites and np-hard problems", "1_output": [["what I want to learn more about the intersection of parallel infinites and np-hard problems", "Computational complexity theory\n\nProblems in NP not known to be in P or NP-complete\nIt was shown by Ladner that if P ≠ NP then there exist problems in NP that are neither in P nor NP-complete. Such problems are called NP-intermediate problems. The graph isomorphism problem, the discrete logarithm problem and the integer factorization problem are examples of problems believed to be NP-intermediate. They are some of the very few NP problems not known to be in P or to be NP-complete.\nThe graph isomorphism problem is the computational problem of determining whether two finite graphs are isomorphic. An important unsolved problem in complexity theory is whether the graph isomorphism problem is in P, NP-complete, or NP-intermediate. The answer is not known, but it is believed that the problem is at least not NP-complete. If graph isomorphism is NP-complete, the polynomial time hierarchy collapses to its second level. Since it is widely believed that the polynomial hierarchy does not collapse to any finite level, it is believed that graph isomorphism is not NP-complete. The best algorithm for this problem, due to László Babai and Eugene Luks has run time  for graphs with n vertices, although some recent work by Babai offers some potentially new perspectives on this."]], "1_corpus": "wikipedia"}