Andrew K. Lampinen

According to our database, Andrew K. Lampinen authored at least 47 papers between 2017 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

Representation biases: will we achieve complete understanding by analyzing representations?

Andrew Kyle Lampinen, Stephanie C. Y. Chan, Yuxuan Li, Katherine L. Hermann

CoRR, July, 2025

Distinct Computations Emerge From Compositional Curricula in In-Context Learning.

Jin Hwa Lee, Andrew K. Lampinen, Aaditya K. Singh, Andrew M. Saxe

CoRR, June, 2025

The emergence of sparse attention: impact of data distribution and benefits of repetition.

Nicolas Zucchet, Francesco D'Angelo, Andrew K. Lampinen, Stephanie C. Y. Chan

CoRR, May, 2025

On the generalization of language models from in-context learning and finetuning: a controlled study.

Andrew K. Lampinen, Arslan Chaudhry, Stephanie C. Y. Chan, Cody Wild, Diane Wan, Alex Ku, Jörg Bornschein, Razvan Pascanu, Murray Shanahan, James L. McClelland

CoRR, May, 2025

How do language models learn facts? Dynamics, curricula and hallucinations.

Nicolas Zucchet, Jörg Bornschein, Stephanie C. Y. Chan, Andrew K. Lampinen, Razvan Pascanu, Soham De

CoRR, March, 2025

Decoupling the components of geometric understanding in Vision Language Models.

Eliza Kosoy, Annya Dahmani, Andrew K. Lampinen, Iulia M. Comsa, Soojin Jeong, Ishita Dasgupta, Kelsey Allen

CoRR, March, 2025

Naturalistic Computational Cognitive Science: Towards generalizable models and theories that capture the full range of natural behavior.

Wilka Carvalho, Andrew K. Lampinen

CoRR, February, 2025

The in-context inductive biases of vision-language models differ across modalities.

Kelsey Allen, Ishita Dasgupta, Eliza Kosoy, Andrew K. Lampinen

CoRR, February, 2025

2024

Evaluating Spatial Understanding of Large Language Models.

Yutaro Yamada, Yihan Bao, Andrew Kyle Lampinen, Jungo Kasai, Ilker Yildirim

Trans. Mach. Learn. Res., 2024

Learned feature representations are biased by complexity, learning order, position, and more.

Andrew Kyle Lampinen, Stephanie C. Y. Chan, Katherine L. Hermann

Trans. Mach. Learn. Res., 2024

The broader spectrum of in-context learning.

Andrew Kyle Lampinen, Stephanie C. Y. Chan, Aaditya K. Singh, Murray Shanahan

CoRR, 2024

Aligning Machine and Human Visual Representations across Abstraction Levels.

Lukas Muttenthaler, Klaus Greff, Frieda Born, Bernhard Spitzer, Simon Kornblith, Michael C. Mozer, Klaus-Robert Müller, Thomas Unterthiner, Andrew K. Lampinen

CoRR, 2024

Scaling Instructable Agents Across Many Simulated Worlds.

SIMA Team, Maria Abi Raad, Arun Ahuja, Catarina Barros, Frederic Besse, Andrew Bolt, Adrian Bolton, Bethanie Brownfield, Gavin Buttimore, Max Cant, Sarah Chakera, Stephanie C. Y. Chan, Jeff Clune, Adrian Collister, Vikki Copeman, Alex Cullum, Ishita Dasgupta, Dario de Cesare, Julia Di Trapani, Yani Donchev, Emma Dunleavy, Martin Engelcke, Ryan Faulkner, Frankie Garcia, Charles Gbadamosi, Zhitao Gong, Lucy Gonzalez, Kshitij Gupta, Karol Gregor, Arne Olav Hallingstad, Tim Harley, Sam Haves, Felix Hill, Ed Hirst, Drew A. Hudson, Jony Hudson, Steph Hughes-Fitt, Danilo J. Rezende, Mimi Jasarevic, Laura Kampis, Nan Rosemary Ke, Thomas Keck, Junkyung Kim, Oscar Knagg, Kavya Kopparapu, Andrew K. Lampinen, Shane Legg, Alexander Lerchner, Marjorie Limont, Yulan Liu, Maria Loks-Thompson, Joseph Marino, Kathryn Martin Cussons, Loic Matthey, Siobhan Mcloughlin, Piermaria Mendolicchio, Hamza Merzic, Anna Mitenkova, Alexandre Moufarek, Valéria Oliveira, Yanko Gitahy Oliveira, Hannah Openshaw, Renke Pan, Aneesh Pappu, Alex Platonov, Ollie Purkiss, David P. Reichert, John Reid, Pierre Harvey Richemond, Tyson Roberts, Giles Ruscoe, Jaume Sanchez Elias, Tasha Sandars, Daniel P. Sawyer, Tim Scholtes, Guy Simmons, Daniel Slater, Hubert Soyer, Heiko Strathmann, Peter Stys, Allison C. Tam, Denis Teplyashin, Tayfun Terzi, Davide Vercelli, Bojan Vujatovic, Marcus Wainwright, Jane X. Wang, Zhengdong Wang, Daan Wierstra, Duncan Williams, Nathaniel Wong, Sarah York, Nick Young

CoRR, 2024

Can Language Models Handle Recursively Nested Grammatical Structures? A Case Study on Comparing Models and Humans.

Andrew K. Lampinen

Comput. Linguistics, 2024

Understanding Visual Feature Reliance through the Lens of Complexity.

Thomas Fel, Louis Béthune, Andrew K. Lampinen, Thomas Serre, Katherine L. Hermann

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Interpretability Illusions in the Generalization of Simplified Models.

Dan Friedman, Andrew Kyle Lampinen, Lucas Dixon, Danqi Chen, Asma Ghandeharioun

Proceedings of the Forty-first International Conference on Machine Learning, 2024

SODA: Bottleneck Diffusion Models for Representation Learning.

Drew A. Hudson, Daniel Zoran, Mateusz Malinowski, Andrew K. Lampinen, Andrew Jaegle, James L. McClelland, Loic Matthey, Felix Hill, Alexander Lerchner

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.

Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W. Kocurek, Ali Safaya, Ali Tazarv, Alice Xiang, Alicia Parrish, Allen Nie, Aman Hussain, Amanda Askell, Amanda Dsouza, Ambrose Slone, Ameet Rahane, Anantharaman S. Iyer, Anders Andreassen, Andrea Madotto, Andrea Santilli, Andreas Stuhlmüller, Andrew M. Dai, Andrew La, Andrew K. Lampinen, Andy Zou, Angela Jiang, Angelica Chen, Anh Vuong, Animesh Gupta, Anna Gottardi, Antonio Norelli, Anu Venkatesh, Arash Gholamidavoodi, Arfa Tabassum, Arul Menezes, Arun Kirubarajan, Asher Mullokandov, Ashish Sabharwal, Austin Herrick, Avia Efrat, Aykut Erdem, Ayla Karakas, B. Ryan Roberts, Bao Sheng Loe, Barret Zoph, Bartlomiej Bojanowski, Batuhan Özyurt, Behnam Hedayatnia, Behnam Neyshabur, Benjamin Inden, Benno Stein, Berk Ekmekci, Bill Yuchen Lin, Blake Howald, Bryan Orinion, Cameron Diao, Cameron Dour, Catherine Stinson, Cedrick Argueta, Cèsar Ferri Ramírez, Chandan Singh, Charles Rathkopf, Chenlin Meng, Chitta Baral, Chiyu Wu, Chris Callison-Burch, Chris Waites, Christian Voigt, Christopher D. Manning, Christopher Potts, Cindy Ramirez, Clara E. Rivera, Clemencia Siro, Colin Raffel, Courtney Ashcraft, Cristina Garbacea, Damien Sileo, Dan Garrette, Dan Hendrycks, Dan Kilman, Dan Roth, Daniel Freeman, Daniel Khashabi, Daniel Levy, Daniel Moseguí González, Danielle Perszyk, Danny Hernandez, Danqi Chen, Daphne Ippolito, Dar Gilboa, David Dohan, David Drakard, David Jurgens, Debajyoti Datta, Deep Ganguli, Denis Emelin, Denis Kleyko, Deniz Yuret, Derek Chen, Derek Tam, Dieuwke Hupkes, Diganta Misra, Dilyar Buzan, Dimitri Coelho Mollo, Diyi Yang, Dong-Ho Lee, Dylan Schrader, Ekaterina Shutova, Ekin Dogus Cubuk, Elad Segal, Eleanor Hagerman, Elizabeth Barnes, Elizabeth Donoway, Ellie Pavlick, Emanuele Rodolà, Emma Lam, Eric Chu, Eric Tang, Erkut Erdem, Ernie Chang, Ethan A. Chi, Ethan Dyer, Ethan J. Jerzak, Ethan Kim, Eunice Engefu Manyasi, Evgenii Zheltonozhskii, Fanyue Xia, Fatemeh Siar, Fernando Martínez-Plumed, Francesca Happé, François Chollet, Frieda Rong, Gaurav Mishra, Genta Indra Winata, Gerard de Melo, Germán Kruszewski, Giambattista Parascandolo, Giorgio Mariani, Gloria Wang, Gonzalo Jaimovitch-López, Gregor Betz, Guy Gur-Ari, Hana Galijasevic, Hannah Kim, Hannah Rashkin, Hannaneh Hajishirzi, Harsh Mehta, Hayden Bogar, Henry Shevlin, Hinrich Schütze, Hiromu Yakura, Hongming Zhang, Hugh Mee Wong, Ian Ng, Isaac Noble, Jaap Jumelet, Jack Geissinger, Jackson Kernion, Jacob Hilton, Jaehoon Lee, Jaime Fernández Fisac, James B. Simon, James Koppel, James Zheng, James Zou, Jan Kocon, Jana Thompson, Janelle Wingfield, Jared Kaplan, Jarema Radom, Jascha Sohl-Dickstein, Jason Phang, Jason Wei, Jason Yosinski, Jekaterina Novikova, Jelle Bosscher, Jennifer Marsh, Jeremy Kim, Jeroen Taal, Jesse H. Engel, Jesujoba Alabi, Jiacheng Xu, Jiaming Song, Jillian Tang, Joan Waweru, John Burden, John Miller, John U. Balis, Jonathan Batchelder, Jonathan Berant, Jörg Frohberg, Jos Rozen, José Hernández-Orallo, Joseph Boudeman, Joseph Guerr, Joseph Jones, Joshua B. Tenenbaum, Joshua S. Rule, Joyce Chua, Kamil Kanclerz, Karen Livescu, Karl Krauth, Karthik Gopalakrishnan, Katerina Ignatyeva, Katja Markert, Kaustubh D. Dhole, Kevin Gimpel, Kevin Omondi, Kory W. Mathewson, Kristen Chiafullo, Ksenia Shkaruta, Kumar Shridhar, Kyle McDonell, Kyle Richardson, Laria Reynolds, Leo Gao, Li Zhang, Liam Dugan, Lianhui Qin, Lidia Contreras Ochando, Louis-Philippe Morency, Luca Moschella, Lucas Lam, Lucy Noble, Ludwig Schmidt, Luheng He, Luis Oliveros Colón, Luke Metz, Lütfi Kerem Senel, Maarten Bosma, Maarten Sap, Maartje ter Hoeve, Maheen Farooqi, Manaal Faruqui, Mantas Mazeika, Marco Baturan, Marco Marelli, Marco Maru, María José Ramírez-Quintana, Marie Tolkiehn, Mario Giulianelli, Martha Lewis, Martin Potthast, Matthew L. Leavitt, Matthias Hagen, Mátyás Schubert, Medina Baitemirova, Melody Arnaud, Melvin McElrath, Michael A. Yee, Michael Cohen, Michael Gu, Michael I. Ivanitskiy, Michael Starritt, Michael Strube, Michal Swedrowski, Michele Bevilacqua, Michihiro Yasunaga, Mihir Kale, Mike Cain, Mimee Xu, Mirac Suzgun, Mitch Walker, Mo Tiwari, Mohit Bansal, Moin Aminnaseri, Mor Geva, Mozhdeh Gheini, Mukund Varma T., Nanyun Peng, Nathan A. Chi, Nayeon Lee, Neta Gur-Ari Krakover, Nicholas Cameron, Nicholas Roberts, Nick Doiron, Nicole Martinez, Nikita Nangia, Niklas Deckers, Niklas Muennighoff, Nitish Shirish Keskar, Niveditha Iyer, Noah Constant, Noah Fiedel, Nuan Wen, Oliver Zhang, Omar Agha, Omar Elbaghdadi, Omer Levy, Owain Evans, Pablo Antonio Moreno Casares, Parth Doshi, Pascale Fung, Paul Pu Liang, Paul Vicol, Pegah Alipoormolabashi, Peiyuan Liao, Percy Liang, Peter Chang, Peter Eckersley, Phu Mon Htut, Pinyu Hwang, Piotr Milkowski, Piyush Patil, Pouya Pezeshkpour, Priti Oli, Qiaozhu Mei, Qing Lyu, Qinlang Chen, Rabin Banjade, Rachel Etta Rudolph, Raefer Gabriel, Rahel Habacker, Ramon Risco, Raphaël Millière, Rhythm Garg, Richard Barnes, Rif A. Saurous, Riku Arakawa, Robbe Raymaekers, Robert Frank, Rohan Sikand, Roman Novak, Roman Sitelew, Ronan LeBras, Rosanne Liu, Rowan Jacobs, Rui Zhang, Ruslan Salakhutdinov, Ryan Chi, Ryan Lee, Ryan Stovall, Ryan Teehan, Rylan Yang, Sahib Singh, Saif M. Mohammad, Sajant Anand, Sam Dillavou, Sam Shleifer, Sam Wiseman, Samuel Gruetter, Samuel R. Bowman, Samuel S. Schoenholz, Sanghyun Han, Sanjeev Kwatra, Sarah A. Rous, Sarik Ghazarian, Sayan Ghosh, Sean Casey, Sebastian Bischoff, Sebastian Gehrmann, Sebastian Schuster, Sepideh Sadeghi, Shadi Hamdan, Sharon Zhou, Shashank Srivastava, Sherry Shi, Shikhar Singh, Shima Asaadi, Shixiang Shane Gu, Shubh Pachchigar, Shubham Toshniwal, Shyam Upadhyay, Shyamolima (Shammie) Debnath, Siamak Shakeri, Simon Thormeyer, Simone Melzi, Siva Reddy, Sneha Priscilla Makini, Soo-Hwan Lee, Spencer Torene, Sriharsha Hatwar, Stanislas Dehaene, Stefan Divic, Stefano Ermon, Stella Biderman, Stephanie Lin, Stephen Prasad, Steven T. Piantadosi, Stuart M. Shieber, Summer Misherghi, Svetlana Kiritchenko, Swaroop Mishra, Tal Linzen, Tal Schuster, Tao Li, Tao Yu, Tariq Ali, Tatsu Hashimoto, Te-Lin Wu, Théo Desbordes, Theodore Rothschild, Thomas Phan, Tianle Wang, Tiberius Nkinyili, Timo Schick, Timofei Kornev, Titus Tunduny, Tobias Gerstenberg, Trenton Chang, Trishala Neeraj, Tushar Khot, Tyler Shultz, Uri Shaham, Vedant Misra, Vera Demberg, Victoria Nyamai, Vikas Raunak, Vinay V. Ramasesh, Vinay Uday Prabhu, Vishakh Padmakumar, Vivek Srikumar, William Fedus, William Saunders, William Zhang, Wout Vossen, Xiang Ren, Xiaoyu Tong, Xinran Zhao, Xinyi Wu, Xudong Shen, Yadollah Yaghoobzadeh, Yair Lakretz, Yangqiu Song, Yasaman Bahri, Yejin Choi, Yichi Yang, Yiding Hao, Yifu Chen, Yonatan Belinkov, Yu Hou, Yufang Hou, Yuntao Bai, Zachary Seid, Zhuoye Zhao, Zijian Wang, Zijie J. Wang, Zirui Wang, Ziyi Wu

Trans. Mach. Learn. Res., 2023

Feature-Attending Recurrent Modules for Generalization in Reinforcement Learning.

Wilka Carvalho, Andrew Kyle Lampinen, Kyriacos Nikiforou, Felix Hill, Murray Shanahan

Trans. Mach. Learn. Res., 2023

Getting aligned on representational alignment.

Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller, Andi Peng, Andreea Bobu, Been Kim, Bradley C. Love, Erin Grant, Jascha Achterberg, Joshua B. Tenenbaum, Katherine M. Collins, Katherine L. Hermann, Kerem Oktar, Klaus Greff, Martin N. Hebart, Nori Jacoby, Qiuyi Zhang, Raja Marjieh, Robert Geirhos, Sherol Chen, Simon Kornblith, Sunayana Rane, Talia Konkle, Thomas P. O'Connell, Thomas Unterthiner, Andrew K. Lampinen, Klaus-Robert Müller, Mariya Toneva, Thomas L. Griffiths

CoRR, 2023

Improving neural network representations using human similarity judgments.

Lukas Muttenthaler, Lorenz Linhardt, Jonas Dippel, Robert A. Vandermeulen, Katherine L. Hermann, Andrew K. Lampinen, Simon Kornblith

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Passive learning of active causal strategies in agents and language models.

Andrew K. Lampinen, Stephanie C. Y. Chan, Ishita Dasgupta, Andrew J. Nam, Jane X. Wang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Combining Behaviors with the Successor Features Keyboard.

Wilka Carvalho, Andre Saraiva, Angelos Filos, Andrew K. Lampinen, Loic Matthey, Richard L. Lewis, Honglak Lee, Satinder Singh, Danilo Jimenez Rezende, Daniel Zoran

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Symbol tuning improves in-context learning in language models.

Jerry W. Wei, Le Hou, Andrew K. Lampinen, Xiangning Chen, Da Huang, Yi Tay, Xinyun Chen, Yifeng Lu, Denny Zhou, Tengyu Ma, Quoc V. Le

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Know your audience: specializing grounded language models with listener subtraction.

Aaditya K. Singh, David Ding, Andrew M. Saxe, Felix Hill, Andrew K. Lampinen

Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

2022

Transformers generalize differently from information stored in context vs in weights.

Stephanie C. Y. Chan, Ishita Dasgupta, Junkyung Kim, Dharshan Kumaran, Andrew K. Lampinen, Felix Hill

CoRR, 2022

Language models show human-like content effects on reasoning.

Ishita Dasgupta, Andrew K. Lampinen, Stephanie C. Y. Chan, Antonia Creswell, Dharshan Kumaran, James L. McClelland, Felix Hill

CoRR, 2022

Know your audience: specializing grounded language models with the game of Dixit.

Aaditya K. Singh, David Ding, Andrew M. Saxe, Felix Hill, Andrew K. Lampinen

CoRR, 2022

Semantic Exploration from Language Abstractions and Pretrained Representations.

Allison C. Tam, Neil C. Rabinowitz, Andrew K. Lampinen, Nicholas A. Roy, Stephanie C. Y. Chan, DJ Strouse, Jane Wang, Andrea Banino, Felix Hill

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Data Distributional Properties Drive Emergent In-Context Learning in Transformers.

Stephanie C. Y. Chan, Adam Santoro, Andrew K. Lampinen, Jane X. Wang, Aaditya K. Singh, Pierre H. Richemond, James L. McClelland, Felix Hill

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Tell me why! Explanations support learning relational and causal structure.

Andrew K. Lampinen, Nicholas A. Roy, Ishita Dasgupta, Stephanie C. Y. Chan, Allison C. Tam, James L. McClelland, Chen Yan, Adam Santoro, Neil C. Rabinowitz, Jane X. Wang, Felix Hill

Proceedings of the International Conference on Machine Learning, 2022

Can language models learn from explanations in context?

Andrew K. Lampinen, Ishita Dasgupta, Stephanie C. Y. Chan, Kory W. Mathewson, Michael Henry Tessler, Antonia Creswell, James L. McClelland, Jane Wang, Felix Hill

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Zipfian Environments for Reinforcement Learning.

Stephanie C. Y. Chan, Andrew Kyle Lampinen, Pierre Harvey Richemond, Felix Hill

Proceedings of the Conference on Lifelong Learning Agents, 2022

2021

Symbolic Behaviour in Artificial Intelligence.

Adam Santoro, Andrew K. Lampinen, Kory W. Mathewson, Timothy P. Lillicrap, David Raposo

CoRR, 2021

Towards mental time travel: a hierarchical memory for reinforcement learning agents.

Andrew K. Lampinen, Stephanie C. Y. Chan, Andrea Banino, Felix Hill

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Transforming task representations to perform novel tasks.

Andrew K. Lampinen, James L. McClelland

Proc. Natl. Acad. Sci. USA, 2020

Transforming task representations to allow deep learning models to perform novel tasks.

Andrew K. Lampinen, James L. McClelland

CoRR, 2020

What shapes feature representations? Exploring datasets, architectures, and training.

Katherine L. Hermann, Andrew K. Lampinen

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Automated curriculum generation through setter-solver interactions.

Sébastien Racanière, Andrew K. Lampinen, Adam Santoro, David P. Reichert, Vlad Firoiu, Timothy P. Lillicrap

Proceedings of the 8th International Conference on Learning Representations, 2020

Environmental drivers of systematicity and generalization in a situated agent.

Felix Hill, Andrew K. Lampinen, Rosalia Schneider, Stephen Clark, Matthew M. Botvinick, James L. McClelland, Adam Santoro

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Emergent Systematic Generalization in a Situated Agent.

Felix Hill, Andrew K. Lampinen, Rosalia Schneider, Stephen Clark, Matthew M. Botvinick, James L. McClelland, Adam Santoro

CoRR, 2019

Automated curricula through setter-solver interactions.

Sébastien Racanière, Andrew K. Lampinen, Adam Santoro, David P. Reichert, Vlad Firoiu, Timothy P. Lillicrap

CoRR, 2019

Embedded Meta-Learning: Toward more flexible deep-learning models.

Andrew K. Lampinen, James L. McClelland

CoRR, 2019

An analytic theory of generalization dynamics and transfer learning in deep linear networks.

Andrew K. Lampinen, Surya Ganguli

Proceedings of the 7th International Conference on Learning Representations, 2019

2017

One-shot and few-shot learning of word embeddings.

Andrew K. Lampinen, James L. McClelland

CoRR, 2017

Improving image generative models with human interactions.

Andrew Kyle Lampinen, David So, Douglas Eck, Fred Bertsch

CoRR, 2017

Analogies Emerge from Learning Dyamics in Neural Networks.

Andrew K. Lampinen, Shaw Hsu, James L. McClelland

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017