Stephanie C. Y. Chan

38 papers A* 11Journal 25Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Architecting Trust in Artificial Epistemic Agents. CoRR Nahema Marchal, Stephanie C. Y. Chan, Matija Franklin, Manon Revel, Geoff Keeling, Roberta Fischli, Bilva Chandra, Iason Gabriel
2025	J	`jnl`	How do language models learn facts? Dynamics, curricula and hallucinations. CoRR Nicolas Zucchet, Jörg Bornschein, Stephanie C. Y. Chan, Andrew K. Lampinen, Razvan Pascanu, Soham De
2025	J	`jnl`	Just-in-time and distributed task representations in language models. CoRR Yuxuan Li, Declan Campbell, Stephanie C. Y. Chan, Andrew Kyle Lampinen
2025	J	`jnl`	On the generalization of language models from in-context learning and finetuning: a controlled study. CoRR Andrew K. Lampinen, Arslan Chaudhry, Stephanie C. Y. Chan, Cody Wild, Diane Wan, Alex Ku, Jörg Bornschein, Razvan Pascanu, Murray Shanahan, James L. McClelland
2025	J	`jnl`	Predictability Shapes Adaptation: An Evolutionary Perspective on Modes of Learning in Transformers. CoRR Alexander Y. Ku, Thomas L. Griffiths, Stephanie C. Y. Chan
2025	J	`jnl`	Representation biases: will we achieve complete understanding by analyzing representations? CoRR Andrew Kyle Lampinen, Stephanie C. Y. Chan, Yuxuan Li, Katherine L. Hermann
2025	A*	`conf`	Strategy Coopetition Explains the Emergence and Transience of In-Context Learning. ICML Aaditya K. Singh, Ted Moskovitz, Sara Dragutinovic, Felix Hill, Stephanie C. Y. Chan, Andrew M. Saxe
2025	J	`jnl`	Strategy Coopetition Explains the Emergence and Transience of In-Context Learning. CoRR Aaditya K. Singh, Ted Moskovitz, Sara Dragutinovic, Felix Hill, Stephanie C. Y. Chan, Andrew M. Saxe
2025	J	`jnl`	The emergence of sparse attention: impact of data distribution and benefits of repetition. CoRR Nicolas Zucchet, Francesco D'Angelo, Andrew K. Lampinen, Stephanie C. Y. Chan
2025	J	`jnl`	Uncovering Competency Gaps in Large Language Models and Their Benchmarks. CoRR Matyas Bohacek, Nino Scherrer, Nicholas Dufour, Thomas Leung, Christoph Bregler, Stephanie C. Y. Chan
2024	A*	`conf`	Genie: Generative Interactive Environments. ICML Jake Bruce, Michael D. Dennis, Ashley Edwards, Jack Parker-Holder, Yuge Shi, Edward Hughes, Matthew Lai, Aditi Mavalankar, Richie Steigerwald, Chris Apps, Yusuf Aytar, Sarah Bechtle, Feryal M. P. Behbahani, Stephanie C. Y. Chan, Nicolas Heess, Lucy Gonzalez, Simon Osindero, Sherjil Ozair, Scott E. Reed, Jingwei Zhang, Konrad Zolna, Jeff Clune, Nando de Freitas, Satinder Singh, Tim Rocktäschel
2024	J	`jnl`	Learned feature representations are biased by complexity, learning order, position, and more. CoRR Andrew Kyle Lampinen, Stephanie C. Y. Chan, Katherine L. Hermann
2024	J	`jnl`	Learned feature representations are biased by complexity, learning order, position, and more. Trans. Mach. Learn. Res. Andrew Kyle Lampinen, Stephanie C. Y. Chan, Katherine L. Hermann
2024	A*	`conf`	Many-Shot In-Context Learning. NeurIPS Rishabh Agarwal, Avi Singh, Lei Zhang, Bernd Bohnet, Luis Rosias, Stephanie C. Y. Chan, Biao Zhang, Ankesh Anand, Zaheer Abbas, Azade Nova, John D. Co-Reyes, Eric Chu, Feryal M. P. Behbahani, Aleksandra Faust, Hugo Larochelle
2024	J	`jnl`	Scaling Instructable Agents Across Many Simulated Worlds. CoRR 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
2024	J	`jnl`	The broader spectrum of in-context learning. CoRR Andrew Kyle Lampinen, Stephanie C. Y. Chan, Aaditya K. Singh, Murray Shanahan
2024	A*	`conf`	What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation. ICML Aaditya K. Singh, Ted Moskovitz, Felix Hill, Stephanie C. Y. Chan, Andrew M. Saxe
2024	J	`jnl`	What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation. CoRR Aaditya K. Singh, Ted Moskovitz, Felix Hill, Stephanie C. Y. Chan, Andrew M. Saxe
2023	A*	`conf`	Passive learning of active causal strategies in agents and language models. NeurIPS Andrew K. Lampinen, Stephanie C. Y. Chan, Ishita Dasgupta, Andrew J. Nam, Jane X. Wang
2023	J	`jnl`	Passive learning of active causal strategies in agents and language models. CoRR Andrew Kyle Lampinen, Stephanie C. Y. Chan, Ishita Dasgupta, Andrew J. Nam, Jane X. Wang
2023	A*	`conf`	The Transient Nature of Emergent In-Context Learning in Transformers. NeurIPS Aaditya K. Singh, Stephanie C. Y. Chan, Ted Moskovitz, Erin Grant, Andrew M. Saxe, Felix Hill
2023	J	`jnl`	The Transient Nature of Emergent In-Context Learning in Transformers. CoRR Aaditya K. Singh, Stephanie C. Y. Chan, Ted Moskovitz, Erin Grant, Andrew M. Saxe, Felix Hill
2022	—	`conf`	Can language models learn from explanations in context? EMNLP (Findings) Andrew K. Lampinen, Ishita Dasgupta, Stephanie C. Y. Chan, Kory W. Mathewson, Michael Henry Tessler, Antonia Creswell, James L. McClelland, Jane Wang, Felix Hill
2022	J	`jnl`	Can language models learn from explanations in context? CoRR Andrew K. Lampinen, Ishita Dasgupta, Stephanie C. Y. Chan, Kory W. Mathewson, Michael Henry Tessler, Antonia Creswell, James L. McClelland, Jane X. Wang, Felix Hill
2022	A*	`conf`	Data Distributional Properties Drive Emergent In-Context Learning in Transformers. NeurIPS Stephanie C. Y. Chan, Adam Santoro, Andrew K. Lampinen, Jane X. Wang, Aaditya K. Singh, Pierre H. Richemond, James L. McClelland, Felix Hill
2022	J	`jnl`	Data Distributional Properties Drive Emergent In-Context Learning in Transformers. CoRR Stephanie C. Y. Chan, Adam Santoro, Andrew K. Lampinen, Jane X. Wang, Aaditya K. Singh, Pierre H. Richemond, Jay McClelland, Felix Hill
2022	J	`jnl`	Language models show human-like content effects on reasoning. CoRR Ishita Dasgupta, Andrew K. Lampinen, Stephanie C. Y. Chan, Antonia Creswell, Dharshan Kumaran, James L. McClelland, Felix Hill
2022	A*	`conf`	Semantic Exploration from Language Abstractions and Pretrained Representations. NeurIPS Allison C. Tam, Neil C. Rabinowitz, Andrew K. Lampinen, Nicholas A. Roy, Stephanie C. Y. Chan, DJ Strouse, Jane Wang, Andrea Banino, Felix Hill
2022	J	`jnl`	Semantic Exploration from Language Abstractions and Pretrained Representations. CoRR Allison C. Tam, Neil C. Rabinowitz, Andrew K. Lampinen, Nicholas A. Roy, Stephanie C. Y. Chan, DJ Strouse, Jane X. Wang, Andrea Banino, Felix Hill
2022	A*	`conf`	Tell me why! Explanations support learning relational and causal structure. ICML 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
2022	J	`jnl`	Transformers generalize differently from information stored in context vs in weights. CoRR Stephanie C. Y. Chan, Ishita Dasgupta, Junkyung Kim, Dharshan Kumaran, Andrew K. Lampinen, Felix Hill
2022	—	`conf`	Zipfian Environments for Reinforcement Learning. CoLLAs Stephanie C. Y. Chan, Andrew Kyle Lampinen, Pierre Harvey Richemond, Felix Hill
2022	J	`jnl`	Zipfian environments for Reinforcement Learning. CoRR Stephanie C. Y. Chan, Andrew K. Lampinen, Pierre H. Richemond, Felix Hill
2021	J	`jnl`	Tell me why! - Explanations support learning of relational and causal structure. CoRR 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
2021	A*	`conf`	Towards mental time travel: a hierarchical memory for reinforcement learning agents. NeurIPS Andrew K. Lampinen, Stephanie C. Y. Chan, Andrea Banino, Felix Hill
2021	J	`jnl`	Towards mental time travel: a hierarchical memory for reinforcement learning agents. CoRR Andrew Kyle Lampinen, Stephanie C. Y. Chan, Andrea Banino, Felix Hill
2020	A*	`conf`	Measuring the Reliability of Reinforcement Learning Algorithms. ICLR Stephanie C. Y. Chan, Samuel Fishman, Anoop Korattikara, John F. Canny, Sergio Guadarrama
2019	J	`jnl`	Measuring the Reliability of Reinforcement Learning Algorithms. CoRR Stephanie C. Y. Chan, Sam Fishman, John F. Canny, Anoop Korattikara, Sergio Guadarrama