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Intelligence is a crucial trait for species to find solutions within a limited number of trial-and-error attempts.
Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych · 1908
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Computing machinery and intelligence
A. M. Turing · 1950
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Relevance weighting of search terms
Stephen E Robertson and K Sparck Jones · 1976
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Collapse of loaded fractal trees
DL Turcotte, RF Smalley Jr, and Sara A Solla · 1985
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Self-organized criticality: An explanation of the 1/f noise
Per Bak, Chao Tang, and Kurt Wiesenfeld · 1987
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Other bodies, other minds: A machine incarnation of an old philosophical problem
Stevan Harnad · 1991
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Neural networks: a comprehensive foundation
Simon Haykin · 1994
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Reinforcement learning: A survey
Leslie Pack Kaelbling, Michael L Littman, and Andrew W Moore · 1996
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Forest fires: an example of self-organized critical behavior
Bruce D Malamud, Gleb Morein, and Donald L Turcotte · 1998
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The chinese room, 1999
John Searle · 1999
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Pessimalprint: a reverse turing test
Henry S Baird, Allison L Coates, and Richard J Fateman · 2003
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Creativity, the turing test, and the (better) lovelace test
Selmer Bringsjord, Paul Bello, and David Ferrucci · 2003
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Theoretical studies of self-organized criticality
Deepak Dhar · 2006
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Universal intelligence: A definition of machine intelligence
Shane Legg and Marcus Hutter · 2007
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Emergent complex neural dynamics
Dante R Chialvo · 2010
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Friendship and mobility: user movement in location-based social networks
Eunjoon Cho, Seth A Myers, and Jure Leskovec · 2011
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The mnist database of handwritten digit images for machine learning research
Li Deng · 2012
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First quora dataset release: Question pairs, 2012
Shankar Iyer, Nikhil Dandekar, and Kornél Csernai · 2012
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The winograd schema challenge
Hector Levesque, Ernest Davis, and Leora Morgenstern · 2012
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How nature works: the science of self-organized criticality
Per Bak · 2013
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Artificial General Intelligence: Concept, State of the Art, and Future Prospects
Ben Goertzel · 2014
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick · 2014
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Fractals and self-organized criticality in proteins
JC Phillips · 2014
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Visual turing test for computer vision systems
Donald Geman, Stuart Geman, Neil Hallonquist, and Laurent Younes · 2015
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The movielens datasets: History and context
F Maxwell Harper and Joseph A Konstan · 2015
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Cqadupstack: A benchmark data set for community question-answering research
Doris Hoogeveen, Karin M. Verspoor, and Timothy Baldwin · 2015
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Flickr30k entities: Collecting region-to-phrase correspondences for richer image-to-sentence models
Bryan A Plummer, Liwei Wang, Chris M Cervantes, Juan C Caicedo, Julia Hockenmaier, and Svetlana Lazebnik · 2015
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Generalised sandpile dynamics on artificial and real-world directed networks
Nicky Zachariou, Paul Expert, Misako Takayasu, and Kim Christensen · 2015
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Ms marco: A human generated machine reading comprehension dataset
Payal Bajaj, Daniel Campos, Nick Craswell, Li Deng, Jianfeng Gao, Xiaodong Liu, Rangan Majumder, Andrew McNamara, Bhaskar Mitra, Tri Nguyen, et al · 2016
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Ups and downs: Modeling the visual evolution of fashion trends with one-class collaborative filtering
Ruining He and Julian McAuley · 2016
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Session-based recommendations with recurrent neural networks
Balázs Hidasi, Alexandros Karatzoglou, Linas Baltrunas, and Domonkos Tikk · 2016
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Training region-based object detectors with online hard example mining
Abhinav Shrivastava, Abhinav Gupta, and Ross Girshick · 2016
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triviaqa: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension
Mandar Joshi, Eunsol Choi, Daniel Weld, and Luke Zettlemoyer · 2017
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Anserini: Enabling the use of lucene for information retrieval research
Peilin Yang, Hui Fang, and Jimmy Lin · 2017
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Measuring mathematical problem solving with the math dataset
Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt · 2021
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Openclip, July 2021
Gabriel Ilharco, Mitchell Wortsman, Ross Wightman, Cade Gordon, Nicholas Carlini, Rohan Taori, Achal Dave, Vaishaal Shankar, Hongseok Namkoong, John Miller, Hannaneh Hajishirzi, Ali Farhadi, and Ludwig Schmidt · 2021
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Unsupervised dense information retrieval with contrastive learning
Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, and Edouard Grave · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Approximate nearest neighbor negative contrastive learning for dense text retrieval
Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul N. Bennett, Junaid Ahmed, and Arnold Overwijk · 2021
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Recurrent neural networks with top-k gains for session-based recommendations
Balázs Hidasi and Alexandros Karatzoglou · 2018
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Self-attentive sequential recommendation
Wang-Cheng Kang and Julian McAuley · 2018
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Www’18 open challenge: Financial opinion mining and question answering
Macedo Maia, Siegfried Handschuh, André Freitas, Brian Davis, Ross McDermott, Manel Zarrouk, and Alexandra Balahur · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Natural questions: a benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Matthew Kelcey, Jacob Devlin, Kenton Lee, Kristina N. Toutanova, Llion Jones, Ming-Wei Chang, Andrew Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov · 2019
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Latent retrieval for weakly supervised open domain question answering
Kenton Lee, Ming-Wei Chang, and Kristina Toutanova · 2019
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Rodrigo Nogueira and Kyunghyun Cho · 2019
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Optimizing dense retrieval model training with hard negatives
Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, and Shaoping Ma · 2021
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Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2022
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Opt: Open pre-trained transformer language models
Susan Zhang, Stephen Roller, Naman Goyal, Mikel Artetxe, Moya Chen, Shuohui Chen, Christopher Dewan, Mona Diab, Xian Li, Xi Victoria Lin, et al · 2022
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Chatgpt broke the turing test-the race is on for new ways to assess ai
Celeste Biever · 2023
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Phi-2: The surprising power of small language models
Mojan Javaheripi, Sébastien Bubeck, Marah Abdin, Jyoti Aneja, Sebastien Bubeck, Caio César Teodoro Mendes, Weizhu Chen, Allie Del Giorno, Ronen Eldan, Sivakanth Gopi, et al · 2023
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Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed · 2023
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The defeat of the winograd schema challenge
Vid Kocijan, Ernest Davis, Thomas Lukasiewicz, Gary Marcus, and Leora Morgenstern · 2023
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Genetic immune escape landscape in primary and metastatic cancer
Francisco Martínez-Jiménez, Peter Priestley, Charles Shale, Jonathan Baber, Erik Rozemuller, and Edwin Cuppen · 2023
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The coming wave: technology, power, and the twenty-first century’s greatest dilemma
Mustafa Suleyman · 2023
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Chinese law and regulations
Tao Wang · 2023
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Cmath: Can your language model pass chinese elementary school math test?, 2023
Tianwen Wei, Jian Luan, Wei Liu, Shuang Dong, and Bin Wang · 2023
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C-pack: Packaged resources to advance general chinese embedding, 2023
Shitao Xiao, Zheng Liu, Peitian Zhang, and Niklas Muennighoff · 2023
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T2ranking: A large-scale chinese benchmark for passage ranking
Xiaohui Xie, Qian Dong, Bingning Wang, Feiyang Lv, Ting Yao, Weinan Gan, Zhijing Wu, Xiangsheng Li, Haitao Li, Yiqun Liu, et al · 2023
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Attributions toward artificial agents in a modified moral turing test
Eyal Aharoni, Sharlene Fernandes, Daniel J Brady, Caelan Alexander, Michael Criner, Kara Queen, Javier Rando, Eddy Nahmias, and Victor Crespo · 2024
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Baichuan-m1-14b
Baichuan · 2024
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Deepseek-v2: A strong, economical, and efficient mixture-of-experts language model, 2024
DeepSeek-AI · 2024
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Abhimanyu Dubey, Abhinav Jauhri, Abhinav Pandey, Abhishek Kadian, Ahmad Al-Dahle, Aiesha Letman, Akhil Mathur, Alan Schelten, Amy Yang, Angela Fan, et al · 2024
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Chatglm: A family of large language models from glm-130b to glm-4 all tools, 2024
Team GLM, Aohan Zeng, Bin Xu, Bowen Wang, Chenhui Zhang, Da Yin, Diego Rojas, Guanyu Feng, Hanlin Zhao, Hanyu Lai, Hao Yu, Hongning Wang, Jiadai Sun, Jiajie Zhang, Jiale Cheng, Jiayi Gui, Jie Tang, Jing Zhang, Juanzi Li, Lei Zhao, Lindong Wu, Lucen Zhong, Mingdao Liu, Minlie Huang, Peng Zhang, Qinkai Zheng, Rui Lu, Shuaiqi Duan, Shudan Zhang, Shulin Cao, Shuxun Yang, Weng Lam Tam, Wenyi Zhao, Xiao Liu, Xiao Xia, Xiaohan Zhang, Xiaotao Gu, Xin Lv, Xinghan Liu, Xinyi Liu, Xinyue Yang, Xixuan Song, Xunkai Zhang, Yifan An, Yifan Xu, Yilin Niu, Yuantao Yang, Yueyan Li, Yushi Bai, Yuxiao Dong, Zehan Qi, Zhaoyu Wang, Zhen Yang, Zhengxiao Du, Zhenyu Hou, and Zihan Wang · 2024
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Cruxeval: A benchmark for code reasoning, understanding and execution
Alex Gu, Baptiste Rozière, Hugh Leather, Armando Solar-Lezama, Gabriel Synnaeve, and Sida I. Wang · 2024
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A turing test of whether ai chatbots are behaviorally similar to humans
Qiaozhu Mei, Yutong Xie, Walter Yuan, and Matthew O Jackson · 2024
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Levels of agi for operationalizing progress on the path to agi, 2024
Meredith Ringel Morris, Jascha Sohl-dickstein, Noah Fiedel, Tris Warkentin, Allan Dafoe, Aleksandra Faust, Clement Farabet, and Shane Legg · 2024
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The laws, centralizing legal texts for better use
Louis Brulé Naudet · 2024
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Mmlu-pro: A more robust and challenging multi-task language understanding benchmark
Yubo Wang, Xueguang Ma, Ge Zhang, Yuansheng Ni, Abhranil Chandra, Shiguang Guo, Weiming Ren, Aaran Arulraj, Xuan He, Ziyan Jiang, et al · 2024
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Deepseek-r1: Incentivizing reasoning capability in llms via reinforcement learning
Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, et al · 2025
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OpenAI Charter, 2018
OpenAI · 2025
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