Fetching the paper…
Reading the bibliography…
In this paper, the second of two companion pieces, we explore novel philosophical questions raised by recent progress in large language models (LLMs) that go beyond the classical debates covered in the first part.
Chomsky, N. (1965), Aspects of the Theory of Syntax
1965
Earlier work this paper cites.
Goodhart, C. (1975), ‘Problems of monetary management: The U.K. experience’, Papers in Monetary Economics
1975
Earlier work this paper cites.
Marr, D. (1982), Vision: A Computational Approach
1982
Earlier work this paper cites.
Smolensky, P. (1986), Neural and conceptual interpretation of PDP models, in
1986
Earlier work this paper cites.
Rumelhart, D. E., Mcclelland, J. L. & Group, P. R. (1987), Parallel Distributed Processing, Volume 1: Explorations in the Microstructure of Cognition: Foundations
1987
Earlier work this paper cites.
Sejnowski, T. J. & Rosenberg, C. R. (1987), ‘Parallel Networks that Learn to Pronounce English Text’, Complex System
1987
Earlier work this paper cites.
Vygotsky, L. S. (1987), ‘Thinking and Speech’, The Collected Works of L. S. Vygotsky
1987
Earlier work this paper cites.
Smolensky, P. (1988), ‘On the proper treatment of connectionism’, Behavioral and Brain Sciences
1988
Earlier work this paper cites.
Baars, B. J. (1993), A Cognitive Theory of Consciousness
1993
Earlier work this paper cites.
Chalmers, D. J. (1995), Absent Qualia, Fading Qualia, Dancing Qualia, in
1995
Earlier work this paper cites.
Franks, B. (1995), ‘On Explanation in the Cognitive Sciences: Competence, Idealization, and the Failure of the Classical Cascade’, The British Journal for the Philosophy of Science
1995
Earlier work this paper cites.
Clark, A. (1998), Magic Words: How Language Augments Human Computation, in
1998
Earlier work this paper cites.
Thomas, R. K. (1998), Lloyd Morgan’s Canon, in
1998
Earlier work this paper cites.
Machamer, P., Darden, L. & Craver, C. F. (2000), ‘Thinking about Mechanisms’, Philosophy of Science
2000
Earlier work this paper cites.
Dehaene, S. & Naccache, L. (2001), ‘Towards a cognitive neuroscience of consciousness: Basic evidence and a workspace framework’, Cognition
2001
Earlier work this paper cites.
Theakston, A. L., Lieven, E. V. M., Pine, J. M. & Rowland, C. F. (2001), ‘The role of performance limitations in the acquisition of verb-argument structure: An alternative account’, Journal of Child Language
2001
Earlier work this paper cites.
Carruthers, P. (2002), ‘The cognitive functions of language’, Behavioral and Brain Sciences
2002
Earlier work this paper cites.
Merker, B. (2005), ‘The liabilities of mobility: A selection pressure for the transition to consciousness in animal evolution’, Consciousness and Cognition
2005
Earlier work this paper cites.
Seth, A. K., Baars, B. J. & Edelman, D. B. (2005), ‘Criteria for consciousness in humans and other mammals’, Consciousness and Cognition
2005
Earlier work this paper cites.
Woodward, J. (2005), Making Things Happen: A Theory of Causal Explanation
2005
Earlier work this paper cites.
Lamme, V. A. F. (2006), ‘Towards a true neural stance on consciousness’, Trends in Cognitive Sciences
2006
Earlier work this paper cites.
Craver, C. F. (2007), Explaining the Brain: Mechanisms and the Mosaic Unity of Neuroscience
2007
Earlier work this paper cites.
Cabanac, M., Cabanac, A. J. & Parent, A. (2009), ‘The emergence of consciousness in phylogeny’, Behavioural Brain Research
2009
Earlier work this paper cites.
Plaut, D. C. & McClelland, J. L. (2010), ‘Locating object knowledge in the brain: Comment on Bowers’s (2009) attempt to revive the grandmother cell hypothesis’, Psychological Review
2009
Earlier work this paper cites.
Tomasello, M. (2009), Constructing a Language
2009
Earlier work this paper cites.
Gallistel, R. C. & King, A. P. (2011), Memory and the Computational Brain: Why Cognitive Science Will Transform Neuroscience
2011
Earlier work this paper cites.
Lupyan, G. (2012), Chapter Seven - What Do Words Do? Toward a Theory of Language-Augmented Thought, in
2012
Earlier work this paper cites.
Barron, A. B. & Klein, C. (2016), ‘What insects can tell us about the origins of consciousness’, Proceedings of the National Academy of Sciences
2016
Earlier work this paper cites.
Christiansen, M. H. & Chater, N. (2016), Creating Language: Integrating Evolution, Acquisition, and Processing
2016
Earlier work this paper cites.
Godfrey-Smith, P. (2016), ‘Mind, Matter, and Metabolism’, The Journal of Philosophy
2016
Earlier work this paper cites.
Frank, M. C., Bergelson, E., Bergmann, C., Cristia, A., Floccia, C., Gervain, J., Hamlin, J. K., Hannon, E. E., Kline, M., Levelt, C., Lew-Williams, C., Nazzi, T., Panneton, R., Rabagliati, H., Soderstrom, M., Sullivan, J., Waxman, S. & Yurovsky, D. (2017), ‘A Collaborative Approach to Infant Research: Promoting Reproducibility, Best Practices, and Theory-Building’, Infancy
2017
Earlier work this paper cites.
Icard, T. F. (2017), From programs to causal models, in
2017
Earlier work this paper cites.
Jonas, E. & Kording, K. P. (2017), ‘Could a Neuroscientist Understand a Microprocessor?’, PLOS Computational Biology
2017
Earlier work this paper cites.
Racanière, S., Weber, T., Reichert, D., Buesing, L., Guez, A., Jimenez Rezende, D., Puigdomènech Badia, A., Vinyals, O., Heess, N., Li, Y., Pascanu, R., Battaglia, P., Hassabis, D., Silver, D. & Wierstra, D. (2017), Imagination-Augmented Agents for Deep Reinforcement Learning, in
2017
Earlier work this paper cites.
Alain, G. & Bengio, Y. (2018), ‘Understanding intermediate layers using linear classifier probes’
2018
Earlier work this paper cites.
Beran, M. (2018), ‘Replication and Pre-Registration in Comparative Psychology’, International Journal of Comparative Psychology
2018
Earlier work this paper cites.
Giulianelli, M., Harding, J., Mohnert, F., Hupkes, D. & Zuidema, W. (2018), Under the Hood: Using Diagnostic Classifiers to Investigate and Improve how Language Models Track Agreement Information, in
2018
Earlier work this paper cites.
Gururangan, S., Swayamdipta, S., Levy, O., Schwartz, R., Bowman, S. R. & Smith, N. A. (2018), ‘Annotation Artifacts in Natural Language Inference Data’
2018
Earlier work this paper cites.
Henderson, P., Islam, R., Bachman, P., Pineau, J., Precup, D. & Meger, D. (2018), ‘Deep Reinforcement Learning That Matters’, Proceedings of the AAAI Conference on Artificial Intelligence
2018
Earlier work this paper cites.
Hupkes, D., Veldhoen, S. & Zuidema, W. (2018), ‘Visualisation and ’Diagnostic Classifiers’ Reveal How Recurrent and Recursive Neural Networks Process Hierarchical Structure’, Journal of Artificial Intelligence Research
2018
Earlier work this paper cites.
Lipton, Z. C. (2018), ‘The mythos of model interpretability’, Communications of the ACM
2018
Earlier work this paper cites.
2018
Earlier work this paper cites.
Barwich, A.-S. (2019), ‘The Value of Failure in Science: The Story of Grandmother Cells in Neuroscience’, Frontiers in Neuroscience
2019
Earlier work this paper cites.
Brown, R., Lau, H. & LeDoux, J. E. (2019), ‘Understanding the Higher-Order Approach to Consciousness’, Trends in Cognitive Sciences
2019
Earlier work this paper cites.
Buckner, C. (2019), ‘Deep learning: A philosophical introduction’, Philosophy Compass
2019
Earlier work this paper cites.
Hewitt, J. & Liang, P. (2019), Designing and Interpreting Probes with Control Tasks, in
2019
Earlier work this paper cites.
Meyes, R., Lu, M., de Puiseau, C. W. & Meisen, T. (2019), ‘Ablation Studies in Artificial Neural Networks’
2019
Earlier work this paper cites.
Rahwan, I., Cebrian, M., Obradovich, N., Bongard, J., Bonnefon, J.-F., Breazeal, C., Crandall, J. W., Christakis, N. A., Couzin, I. D., Jackson, M. O., Jennings, N. R., Kamar, E., Kloumann, I. M., Larochelle, H., Lazer, D., McElreath, R., Mislove, A., Parkes, D. C., Pentland, A. S., Roberts, M. E., Shariff, A., Tenenbaum, J. B. & Wellman, M. (2019), ‘Machine behaviour’, Nature
2019
Earlier work this paper cites.
Wiggins, B. J. & Christopherson, C. D. (2019), ‘The replication crisis in psychology: An overview for theoretical and philosophical psychology’, Journal of Theoretical and Philosophical Psychology
2019
Earlier work this paper cites.
Beckers, S., Eberhardt, F. & Halpern, J. Y. (2020), Approximate Causal Abstractions, in
2020
Earlier work this paper cites.
Firestone, C. (2020), ‘Performance vs. competence in human–machine comparisons’, Proceedings of the National Academy of Sciences
2020
Earlier work this paper cites.
Kaplan, J., McCandlish, S., Henighan, T., Brown, T. B., Chess, B., Child, R., Gray, S., Radford, A., Wu, J. & Amodei, D. (2020), ‘Scaling Laws for Neural Language Models’
2020
Earlier work this paper cites.
Nickles, T. (2020), ‘Alien Reasoning: Is a Major Change in Scientific Research Underway?’, Topoi
2020
Earlier work this paper cites.
Ravfogel, S., Elazar, Y., Gonen, H., Twiton, M. & Goldberg, Y. (2020), ‘Null It Out: Guarding Protected Attributes by Iterative Nullspace Projection’
2020
Cited alongside, same era.
Rogers, A., Kovaleva, O. & Rumshisky, A. (2020), ‘A Primer in BERTology: What We Know About How BERT Works’, Transactions of the Association for Computational Linguistics
2020
Cited alongside, same era.
Caucheteux, C., Gramfort, A. & King, J.-R. (2021), ‘GPT-2’s activations predict the degree of semantic comprehension in the human brain’
2021
Cited alongside, same era.
Chefer, H., Gur, S. & Wolf, L. (2021), Transformer Interpretability Beyond Attention Visualization, in
2021
Cited alongside, same era.
Colas, C., Karch, T., Moulin-Frier, C. & Oudeyer, P.-Y. (2021), ‘Language as a Cognitive Tool: Dall-E, Humans and Vygotskian RL Agents’
2021
Cited alongside, same era.
Giannou, A., Rajput, S., Sohn, J.-y., Lee, K., Lee, J. D. & Papailiopoulos, D. (2023), ‘Looped Transformers as Programmable Computers’
2023
Later among the works it cites.
Gozalo-Brizuela, R. & Garrido-Merchán, E. C. (2023), ‘A survey of Generative AI Applications’
2023
Later among the works it cites.
Harding, J. (2023), ‘Operationalising Representation in Natural Language Processing’
2023
Later among the works it cites.
Hazineh, D. S., Zhang, Z. & Chiu, J. (2023), ‘Linear Latent World Models in Simple Transformers: A Case Study on Othello-GPT’
2023
Later among the works it cites.
Henighan, T., Carter, S., Hume, T., Elhage, N., Lasenby, R., Fort, S., Schiefer, N. & Olah, C. (2023), ‘Superposition, memorization, and double descent’, Transformer Circuits Thread
2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., Zhai, X., Unterthiner, T., Dehghani, M., Minderer, M., Heigold, G., Gelly, S., Uszkoreit, J. & Houlsby, N. (2021), ‘An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale’
2021
Cited alongside, same era.
Dupre, G. (2021), ‘(What) Can Deep Learning Contribute to Theoretical Linguistics?’, Minds and Machines
2021
Cited alongside, same era.
Elhage, N., Nanda, N., Olsson, C., Henighan, T., Joseph, N., Mann, B., Askell, A., Bai, Y., Chen, A., Conerly, T., DasSarma, N., Drain, D., Ganguli, D., Hatfield-Dodds, Z., Hernandez, D., Jones, A., Kernion, J., Lovitt, L., Ndousse, K., Amodei, D., Brown, T., Clark, J., Kaplan, J., McCandlish, S. & Olah, C. (2021), ‘A mathematical framework for transformer circuits’, Transformer Circuits Thread
2021
Cited alongside, same era.
Esser, P., Rombach, R. & Ommer, B. (2021), Taming Transformers for High-Resolution Image Synthesis, in
2021
Cited alongside, same era.
Geiger, A., Lu, H., Icard, T. & Potts, C. (2021), Causal Abstractions of Neural Networks, in
2021
Cited alongside, same era.
Godfrey-Smith, P. (2021), Metazoa: Animal Life and the Birth of the Mind
2021
Cited alongside, same era.
Irvine, E. (2021), ‘Developing Dark Pessimism Towards the Justificatory Role of Introspective Reports’, Erkenntnis
2021
Cited alongside, same era.
Hsieh, C.-Y., Zhang, J., Ma, Z., Kembhavi, A. & Krishna, R. (2023), ‘SugarCrepe: Fixing Hackable Benchmarks for Vision-Language Compositionality’, Advances in Neural Information Processing Systems
2023
Later among the works it cites.
Kamath, A., Hessel, J. & Chang, K.-W. (2023 a
2023
Later among the works it cites.
Kamath, A., Hessel, J. & Chang, K.-W. (2023 b
2023
Later among the works it cites.
Kosinski, M. (2023), ‘Theory of Mind Might Have Spontaneously Emerged in Large Language Models’
2023
Later among the works it cites.
LeDoux, J., Birch, J., Andrews, K., Clayton, N. S., Daw, N. D., Frith, C., Lau, H., Peters, M. A. K., Schneider, S., Seth, A., Suddendorf, T. & Vandekerckhove, M. M. P. (2023), ‘Consciousness beyond the human case’, Current Biology
2023
Later among the works it cites.
Lewis, M., Nayak, N. V., Yu, P., Yu, Q., Merullo, J., Bach, S. H. & Pavlick, E. (2023), ‘Does CLIP Bind Concepts? Probing Compositionality in Large Image Models’
2023
Later among the works it cites.
Li, K., Hopkins, A. K., Bau, D., Viégas, F., Pfister, H. & Wattenberg, M. (2023), ‘Emergent World Representations: Exploring a Sequence Model Trained on a Synthetic Task’
2023
Later among the works it cites.
Lindsay, G. W. & Bau, D. (2023), ‘Testing methods of neural systems understanding’, Cognitive Systems Research
2023
Later among the works it cites.
Mahowald, K., Ivanova, A. A., Blank, I. A., Kanwisher, N., Tenenbaum, J. B. & Fedorenko, E. (2023), ‘Dissociating language and thought in large language models: A cognitive perspective’
2023
Later among the works it cites.
McCoy, R. T., Yao, S., Friedman, D., Hardy, M. & Griffiths, T. L. (2023), ‘Embers of Autoregression: Understanding Large Language Models Through the Problem They are Trained to Solve’
2023
Later among the works it cites.
McGrath, S., Russin, J., Pavlick, E. & Feiman, R. (2023), ‘How Can Deep Neural Networks Inform Theory in Psychological Science?’
2023
Later among the works it cites.
Meng, K., Bau, D., Andonian, A. & Belinkov, Y. (2023), ‘Locating and Editing Factual Associations in GPT’
2023
Later among the works it cites.
Mirchandani, S., Xia, F., Florence, P., Ichter, B., Driess, D., Arenas, M. G., Rao, K., Sadigh, D. & Zeng, A. (2023), ‘Large Language Models as General Pattern Machines’
2023
Later among the works it cites.
Mollo, D. C. & Millière, R. (2023), ‘The Vector Grounding Problem’
2023
Later among the works it cites.
Nanda, N., Lee, A. & Wattenberg, M. (2023), ‘Emergent Linear Representations in World Models of Self-Supervised Sequence Models’
2023
Later among the works it cites.
OpenAI (2023 a
2023
Later among the works it cites.
OpenAI (2023 b
2023
Later among the works it cites.
Park, J. S., O’Brien, J. C., Cai, C. J., Morris, M. R., Liang, P. & Bernstein, M. S. (2023), ‘Generative Agents: Interactive Simulacra of Human Behavior’
2023
Later among the works it cites.
Park, K., Choe, Y. J. & Veitch, V. (2023), ‘The Linear Representation Hypothesis and the Geometry of Large Language Models’
2023
Later among the works it cites.
Roberts, M., Thakur, H., Herlihy, C., White, C. & Dooley, S. (2023), ‘Data Contamination Through the Lens of Time’
2023
Later among the works it cites.
Schick, T., Dwivedi-Yu, J., Dessì, R., Raileanu, R., Lomeli, M., Zettlemoyer, L., Cancedda, N. & Scialom, T. (2023), ‘Toolformer: Language Models Can Teach Themselves to Use Tools’
2023
Later among the works it cites.
Shea, N. (2023), ‘Moving beyond content-specific computation in artificial neural networks’, Mind & Language
2023
Later among the works it cites.
Shinn, N., Cassano, F., Berman, E., Gopinath, A., Narasimhan, K. & Yao, S. (2023), ‘Reflexion: Language Agents with Verbal Reinforcement Learning’
2023
Later among the works it cites.
Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., Kluska, A., Lewkowycz, A., Agarwal, A., Power, A., Ray, A., Warstadt, A., Kocurek, A. W., Safaya, A., Tazarv, A., Xiang, A., Parrish, A., Nie, A., Hussain, A., Askell, A., Dsouza, A., Slone, A., Rahane, A., Iyer, A. S., Andreassen, A. J., Madotto, A., Santilli, A., Stuhlmüller, A., Dai, A. M., La, A., Lampinen, A., Zou, A., Jiang, A., Chen, A., Vuong, A., Gupta, A., Gottardi, A., Norelli, A., Venkatesh, A., Gholamidavoodi, A., Tabassum, A., Menezes, A., Kirubarajan, A., Mullokandov, A., Sabharwal, A., Herrick, A., Efrat, A., Erdem, A., Karakaş, A., Roberts, B. R., Loe, B. S., Zoph, B., Bojanowski, B., Özyurt, B., Hedayatnia, B., Neyshabur, B., Inden, B., Stein, B., Ekmekci, B., Lin, B. Y., Howald, B., Orinion, B., Diao, C., Dour, C., Stinson, C., Argueta, C., Ferri, C., Singh, C., Rathkopf, C., Meng, C., Baral, C., Wu, C., Callison-Burch, C., Waites, C., Voigt, C., Manning, C. D., Potts, C., Ramirez, C., Rivera, C. E., Siro, C., Raffel, C., Ashcraft, C., Garbacea, C., Sileo, D., Garrette, D., Hendrycks, D., Kilman, D., Roth, D., Freeman, C. D., Khashabi, D., Levy, D., González, D. M., Perszyk, D., Hernandez, D., Chen, D., Ippolito, D., Gilboa, D., Dohan, D., Drakard, D., Jurgens, D., Datta, D., Ganguli, D., Emelin, D., Kleyko, D., Yuret, D., Chen, D., Tam, D., Hupkes, D., Misra, D., Buzan, D., Mollo, D. C., Yang, D., Lee, D.-H., Schrader, D., Shutova, E., Cubuk, E. D., Segal, E., Hagerman, E., Barnes, E., Donoway, E., Pavlick, E., Rodolà, E., Lam, E., Chu, E., Tang, E., Erdem, E., Chang, E., Chi, E. A., Dyer, E., Jerzak, E., Kim, E., Manyasi, E. E., Zheltonozhskii, E., Xia, F., Siar, F., Martínez-Plumed, F., Happé, F., Chollet, F., Rong, F., Mishra, G., Winata, G. I., de Melo, G., Kruszewski, G., Parascandolo, G., Mariani, G., Wang, G. X., Jaimovitch-Lopez, G., Betz, G., Gur-Ari, G., Galijasevic, H., Kim, H., Rashkin, H., Hajishirzi, H., Mehta, H., Bogar, H., Shevlin, H. F. A., Schuetze, H., Yakura, H., Zhang, H., Wong, H. M., Ng, I., Noble, I., Jumelet, J., Geissinger, J., Kernion, J., Hilton, J., Lee, J., Fisac, J. F., Simon, J. B., Koppel, J., Zheng, J., Zou, J., Kocon, J., Thompson, J., Wingfield, J., Kaplan, J., Radom, J., Sohl-Dickstein, J., Phang, J., Wei, J., Yosinski, J., Novikova, J., Bosscher, J., Marsh, J., Kim, J., Taal, J., Engel, J., Alabi, J., Xu, J., Song, J., Tang, J., Waweru, J., Burden, J., Miller, J., Balis, J. U., Batchelder, J., Berant, J., Frohberg, J., Rozen, J., Hernandez-Orallo, J., Boudeman, J., Guerr, J., Jones, J., Tenenbaum, J. B., Rule, J. S., Chua, J., Kanclerz, K., Livescu, K., Krauth, K., Gopalakrishnan, K., Ignatyeva, K., Markert, K., Dhole, K., Gimpel, K., Omondi, K., Mathewson, K. W., Chiafullo, K., Shkaruta, K., Shridhar, K., McDonell, K., Richardson, K., Reynolds, L., Gao, L., Zhang, L., Dugan, L., Qin, L., Contreras-Ochando, L., Morency, L.-P., Moschella, L., Lam, L., Noble, L., Schmidt, L., He, L., Oliveros-Colón, L., Metz, L., Senel, L. K., Bosma, M., Sap, M., Hoeve, M. T., Farooqi, M., Faruqui, M., Mazeika, M., Baturan, M., Marelli, M., Maru, M., Ramirez-Quintana, M. J., Tolkiehn, M., Giulianelli, M., Lewis, M., Potthast, M., Leavitt, M. L., Hagen, M., Schubert, M., Baitemirova, M. O., Arnaud, M., McElrath, M., Yee, M. A., Cohen, M., Gu, M., Ivanitskiy, M., Starritt, M., Strube, M., Swędrowski, M., Bevilacqua, M., Yasunaga, M., Kale, M., Cain, M., Xu, M., Suzgun, M., Walker, M., Tiwari, M., Bansal, M., Aminnaseri, M., Geva, M., Gheini, M., T, M. V., Peng, N., Chi, N. A., Lee, N., Krakover, N. G.-A., Cameron, N., Roberts, N., Doiron, N., Martinez, N., Nangia, N., Deckers, N., Muennighoff, N., Keskar, N. S., Iyer, N. S., Constant, N., Fiedel, N., Wen, N., Zhang, O., Agha, O., Elbaghdadi, O., Levy, O., Evans, O., Casares, P. A. M., Doshi, P., Fung, P., Liang, P. P., Vicol, P., Alipoormolabashi, P., Liao, P., Liang, P., Chang, P. W., Eckersley, P., Htut, P. M., Hwang, P., Miłkowski, P., Patil, P., Pezeshkpour, P., Oli, P., Mei, Q., Lyu, Q., Chen, Q., Banjade, R., Rudolph, R. E., Gabriel, R., Habacker, R., Risco, R., Millière, R., Garg, R., Barnes, R., Saurous, R. A., Arakawa, R., Raymaekers, R., Frank, R., Sikand, R., Novak, R., Sitelew, R., Bras, R. L., Liu, R., Jacobs, R., Zhang, R., Salakhutdinov, R., Chi, R. A., Lee, S. R., Stovall, R., Teehan, R., Yang, R., Singh, S., Mohammad, S. M., Anand, S., Dillavou, S., Shleifer, S., Wiseman, S., Gruetter, S., Bowman, S. R., Schoenholz, S. S., Han, S., Kwatra, S., Rous, S. A., Ghazarian, S., Ghosh, S., Casey, S., Bischoff, S., Gehrmann, S., Schuster, S., Sadeghi, S., Hamdan, S., Zhou, S., Srivastava, S., Shi, S., Singh, S., Asaadi, S., Gu, S. S., Pachchigar, S., Toshniwal, S., Upadhyay, S., Debnath, S. S., Shakeri, S., Thormeyer, S., Melzi, S., Reddy, S., Makini, S. P., Lee, S.-H., Torene, S., Hatwar, S., Dehaene, S., Divic, S., Ermon, S., Biderman, S., Lin, S., Prasad, S., Piantadosi, S., Shieber, S., Misherghi, S., Kiritchenko, S., Mishra, S., Linzen, T., Schuster, T., Li, T., Yu, T., Ali, T., Hashimoto, T., Wu, T.-L., Desbordes, T., Rothschild, T., Phan, T., Wang, T., Nkinyili, T., Schick, T., Kornev, T., Tunduny, T., Gerstenberg, T., Chang, T., Neeraj, T., Khot, T., Shultz, T., Shaham, U., Misra, V., Demberg, V., Nyamai, V., Raunak, V., Ramasesh, V. V., Prabhu, V. U., Padmakumar, V., Srikumar, V., Fedus, W., Saunders, W., Zhang, W., Vossen, W., Ren, X., Tong, X., Zhao, X., Wu, X., Shen, X., Yaghoobzadeh, Y., Lakretz, Y., Song, Y., Bahri, Y., Choi, Y., Yang, Y., Hao, Y., Chen, Y., Belinkov, Y., Hou, Y., Hou, Y., Bai, Y., Seid, Z., Zhao, Z., Wang, Z., Wang, Z. J., Wang, Z. & Wu, Z. (2023), ‘Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models’, Transactions on Machine Learning Research
2023
Later among the works it cites.
Syed, A., Rager, C. & Conmy, A. (2023), ‘Attribution Patching Outperforms Automated Circuit Discovery’
2023
Later among the works it cites.
Tong, S., Jones, E. & Steinhardt, J. (2023), ‘Mass-Producing Failures of Multimodal Systems with Language Models’, Advances in Neural Information Processing Systems
2023
Later among the works it cites.
Tschannen, M., Kumar, M., Steiner, A., Zhai, X., Houlsby, N. & Beyer, L. (2023), ‘Image Captioners Are Scalable Vision Learners Too’, Advances in Neural Information Processing Systems
2023
Later among the works it cites.
Ullman, T. (2023), ‘Large Language Models Fail on Trivial Alterations to Theory-of-Mind Tasks’
2023
Later among the works it cites.
Wang, G., Xie, Y., Jiang, Y., Mandlekar, A., Xiao, C., Zhu, Y., Fan, L. & Anandkumar, A. (2023), ‘Voyager: An Open-Ended Embodied Agent with Large Language Models’
2023
Later among the works it cites.
Wang, L., Ma, C., Feng, X., Zhang, Z., Yang, H., Zhang, J., Chen, Z., Tang, J., Chen, X., Lin, Y., Zhao, W. X., Wei, Z. & Wen, J.-R. (2023), ‘A Survey on Large Language Model based Autonomous Agents’
2023
Later among the works it cites.
Webb, T., Holyoak, K. J. & Lu, H. (2023), ‘Emergent analogical reasoning in large language models’, Nature Human Behaviour
2023
Later among the works it cites.
Wu, Y., Wang, S., Yang, H., Zheng, T., Zhang, H., Zhao, Y. & Qin, B. (2023), ‘An Early Evaluation of GPT-4V(ision)’
2023
Later among the works it cites.
Wu, Z., Geiger, A., Potts, C. & Goodman, N. D. (2023), ‘Interpretability at Scale: Identifying Causal Mechanisms in Alpaca’
2023
Later among the works it cites.
Yang, S., Chiang, W.-L., Zheng, L., Gonzalez, J. E. & Stoica, I. (2023), ‘Rethinking Benchmark and Contamination for Language Models with Rephrased Samples’
2023
Later among the works it cites.
Yang, Z., Li, L., Lin, K., Wang, J., Lin, C.-C., Liu, Z. & Wang, L. (2023), ‘The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision)’
2023
Later among the works it cites.
Yao, S., Zhao, J., Yu, D., Du, N., Shafran, I., Narasimhan, K. & Cao, Y. (2023), ‘ReAct: Synergizing Reasoning and Acting in Language Models’
2023
Later among the works it cites.
Yildirim, I. & Paul, L. A. (2023), ‘From task structures to world models: What do LLMs know?’, Trends in Cognitive Sciences
2023
Later among the works it cites.
Zhang, F. & Nanda, N. (2023), ‘Towards Best Practices of Activation Patching in Language Models: Metrics and Methods’
2023
Later among the works it cites.
Zhang, K. & Lewis, M. (2023), Evaluating CLIP’s Understanding on Relationships in a Blocks World, in
2023
Later among the works it cites.
Zhou, A., Wang, K., Lu, Z., Shi, W., Luo, S., Qin, Z., Lu, S., Jia, A., Song, L., Zhan, M. & Li, H. (2023), ‘Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification’
2023
Later among the works it cites.
Zhou, H., Bradley, A., Littwin, E., Razin, N., Saremi, O., Susskind, J., Bengio, S. & Nakkiran, P. (2023), ‘What Algorithms can Transformers Learn? A Study in Length Generalization’
2023
Later among the works it cites.
Zitkovich, B., Yu, T., Xu, S., Xu, P., Xiao, T., Xia, F., Wu, J., Wohlhart, P., Welker, S., Wahid, A., Vuong, Q., Vanhoucke, V., Tran, H., Soricut, R., Singh, A., Singh, J., Sermanet, P., Sanketi, P. R., Salazar, G., Ryoo, M. S., Reymann, K., Rao, K., Pertsch, K., Mordatch, I., Michalewski, H., Lu, Y., Levine, S., Lee, L., Lee, T.-W. E., Leal, I., Kuang, Y., Kalashnikov, D., Julian, R., Joshi, N. J., Irpan, A., Ichter, B., Hsu, J., Herzog, A., Hausman, K., Gopalakrishnan, K., Fu, C., Florence, P., Finn, C., Dubey, K. A., Driess, D., Ding, T., Choromanski, K. M., Chen, X., Chebotar, Y., Carbajal, J., Brown, N., Brohan, A., Arenas, M. G. & Han, K. (2023), RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control, in
2023
Later among the works it cites.
Han, S. J., Ransom, K. J., Perfors, A. & Kemp, C. (2024), ‘Inductive reasoning in humans and large language models’, Cognitive Systems Research
2024
Closest in time.
Karvonen, A. (2024), ‘Chess-GPT’s Internal World Model’, https://adamkarvonen.github.io/machine_learning/2024/01/03/chess-world-models.html
2024
Closest in time.
Millière, R. & Buckner, C. (2024), ‘A Philosophical Introduction to Language Models – Part I: Continuity With Classic Debates’
2024
Closest in time.
Murphy, E., de Villiers, J. & Morales, S. L. (2024), ‘A Comparative Investigation of Compositional Syntax and Semantics in DALL-E 2’
2024
Closest in time.
Suri, G., Slater, L. R., Ziaee, A. & Nguyen, M. (2024), ‘Do large language models show decision heuristics similar to humans? A case study using GPT-3.5.’, Journal of Experimental Psychology: General
2024
Closest in time.