Aaditya K. Singh

24 papers A* 6A 1Journal 17

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Correlating and Predicting Human Evaluations of Language Models from Natural Language Processing Benchmarks. CoRR Rylan Schaeffer, Punit Singh Koura, Binh Tang, Ranjan Subramanian, Aaditya K. Singh, Todor Mihaylov, Prajjwal Bhargava, Lovish Madaan, Niladri S. Chatterji, Vedanuj Goswami, Sergey Edunov, Dieuwke Hupkes, Sanmi Koyejo, Sharan Narang
2025	J	`jnl`	Distinct Computations Emerge From Compositional Curricula in In-Context Learning. CoRR Jin Hwa Lee, Andrew K. Lampinen, Aaditya K. Singh, Andrew M. Saxe
2025	J	`jnl`	Softmax ≥ Linear: Transformers may learn to classify in-context by kernel gradient descent. CoRR Sara Dragutinovic, Andrew M. Saxe, Aaditya K. Singh
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	A*	`conf`	Training Dynamics of In-Context Learning in Linear Attention. ICML Yedi Zhang, Aaditya K. Singh, Peter E. Latham, Andrew M. Saxe
2025	J	`jnl`	Training Dynamics of In-Context Learning in Linear Attention. CoRR Yedi Zhang, Aaditya K. Singh, Peter E. Latham, Andrew M. Saxe
2024	J	`jnl`	Brevity is the soul of wit: Pruning long files for code generation. CoRR Aaditya K. Singh, Yu Yang, Kushal Tirumala, Mostafa Elhoushi, Ari S. Morcos
2024	A*	`conf`	Confronting Reward Model Overoptimization with Constrained RLHF. ICLR Ted Moskovitz, Aaditya K. Singh, DJ Strouse, Tuomas Sandholm, Ruslan Salakhutdinov, Anca D. Dragan, Stephen Marcus McAleer
2024	J	`jnl`	Evaluation data contamination in LLMs: how do we measure it and (when) does it matter? CoRR Aaditya K. Singh, Muhammed Yusuf Kocyigit, Andrew Poulton, David Esiobu, Maria Lomeli, Gergely Szilvasy, Dieuwke Hupkes
2024	J	`jnl`	HARP: A challenging human-annotated math reasoning benchmark. CoRR Albert S. Yue, Lovish Madaan, Ted Moskovitz, DJ Strouse, Aaditya K. Singh
2024	J	`jnl`	Quantifying Variance in Evaluation Benchmarks. CoRR Lovish Madaan, Aaditya K. Singh, Rylan Schaeffer, Andrew Poulton, Sanmi Koyejo, Pontus Stenetorp, Sharan Narang, Dieuwke Hupkes
2024	J	`jnl`	The broader spectrum of in-context learning. CoRR Andrew Kyle Lampinen, Stephanie C. Y. Chan, Aaditya K. Singh, Murray Shanahan
2024	J	`jnl`	Tokenization counts: the impact of tokenization on arithmetic in frontier LLMs. CoRR Aaditya K. Singh, DJ Strouse
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	J	`jnl`	Confronting Reward Model Overoptimization with Constrained RLHF. CoRR Ted Moskovitz, Aaditya K. Singh, DJ Strouse, Tuomas Sandholm, Ruslan Salakhutdinov, Anca D. Dragan, Stephen McAleer
2023	J	`jnl`	Decoding Data Quality via Synthetic Corruptions: Embedding-guided Pruning of Code Data. CoRR Yu Yang, Aaditya K. Singh, Mostafa Elhoushi, Anas Mahmoud, Kushal Tirumala, Fabian Gloeckle, Baptiste Rozière, Carole-Jean Wu, Ari S. Morcos, Newsha Ardalani
2023	A	`conf`	Know your audience: specializing grounded language models with listener subtraction. EACL Aaditya K. Singh, David Ding, Andrew M. Saxe, Felix Hill, Andrew K. Lampinen
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	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`	Know your audience: specializing grounded language models with the game of Dixit. CoRR Aaditya K. Singh, David Ding, Andrew M. Saxe, Felix Hill, Andrew K. Lampinen