On the Query Complexity of Verifier-Assisted Language Generation
Edoardo Botta, Yuchen Li, Aashay Mehta, Jordan Ash, Cyril Zhang, Andrej Risteski
ICML 2025 | February 2025
Jordan Ash
Principal Researcher
Papiers de Collaboration
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A Study of Plasticity Loss in On-Policy Deep Reinforcement Learning
Arthur Juliani, Jordan Ash
NeurIPS 2024 | May 2024
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The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
Pratyusha Sharma, Jordan Ash, Dipendra Misra
ICLR 2024 | December 2023
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Exposing Attention Glitches with Flip-Flop Language Modeling
Bingbin Liu, Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
NeurIPS 2023 | October 2023
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Transformers Learn Shortcuts to Automata
Bingbin Liu, Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
ICLR | May 2023
oral presentation
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Streaming Active Learning with Deep Neural Networks
Akanksha Saran, Safoora Yousefi, Akshay Krishnamurthy, John Langford, Jordan Ash
ICML 2023 | March 2023
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Understanding Contrastive Learning Requires Incorporating Inductive Biases
Nikunj Umesh Saunshi, Jordan Ash, Surbhi Goel, Dipendra Kumar Misra, Cyril Zhang, Sanjeev Arora, Sham Kakade, Akshay Krishnamurthy
ICML 2022 | July 2022
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Anti-Concentrated Confidence Bonuses for Scalable Exploration
Jordan T. Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade
ICLR 2022 | April 2022
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Investigating the Role of Negatives in Contrastive Representation Learning
Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra
2022 International Conference on Artificial Intelligence and Statistics | February 2022
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Gone Fishing: Neural Active Learning with Fisher Embeddings
Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Sham Kakade
NeurIPS 2021 | December 2021
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Learning Composable Energy Surrogates for PDE Order Reduction
Alex Beatson, Jordan Ash, Geoffrey Roeder, Tianju Xue, Ryan P. Adams
NeurIPS 2020 | December 2020
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On Warm-Starting Neural Network Training
Jordan Ash, Ryan P. Adams
NeurIPS 2020 | December 2020
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On the Query Complexity of Verifier-Assisted Language Generation
Edoardo Botta, Yuchen Li, Aashay Mehta, Jordan Ash, Cyril Zhang, Andrej Risteski
ICML 2025 | February 2025
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On the Query Complexity of Verifier-Assisted Language Generation
Edoardo Botta, Yuchen Li, Aashay Mehta, Jordan Ash, Cyril Zhang, Andrej Risteski
ICML 2025 | February 2025
-
A Study of Plasticity Loss in On-Policy Deep Reinforcement Learning
Arthur Juliani, Jordan Ash
NeurIPS 2024 | May 2024
-
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
Pratyusha Sharma, Jordan Ash, Dipendra Misra
ICLR 2024 | December 2023
-
Exposing Attention Glitches with Flip-Flop Language Modeling
Bingbin Liu, Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
NeurIPS 2023 | October 2023
-
Transformers Learn Shortcuts to Automata
Bingbin Liu, Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
ICLR | May 2023
oral presentation
-
Streaming Active Learning with Deep Neural Networks
Akanksha Saran, Safoora Yousefi, Akshay Krishnamurthy, John Langford, Jordan Ash
ICML 2023 | March 2023
-
Understanding Contrastive Learning Requires Incorporating Inductive Biases
Nikunj Umesh Saunshi, Jordan Ash, Surbhi Goel, Dipendra Kumar Misra, Cyril Zhang, Sanjeev Arora, Sham Kakade, Akshay Krishnamurthy
ICML 2022 | July 2022
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Anti-Concentrated Confidence Bonuses for Scalable Exploration
Jordan T. Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade
ICLR 2022 | April 2022
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Investigating the Role of Negatives in Contrastive Representation Learning
Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra
2022 International Conference on Artificial Intelligence and Statistics | February 2022
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Gone Fishing: Neural Active Learning with Fisher Embeddings
Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Sham Kakade
NeurIPS 2021 | December 2021
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Learning Composable Energy Surrogates for PDE Order Reduction
Alex Beatson, Jordan Ash, Geoffrey Roeder, Tianju Xue, Ryan P. Adams
NeurIPS 2020 | December 2020
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On Warm-Starting Neural Network Training
Jordan Ash, Ryan P. Adams
NeurIPS 2020 | December 2020
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On the Query Complexity of Verifier-Assisted Language Generation
Edoardo Botta, Yuchen Li, Aashay Mehta, Jordan Ash, Cyril Zhang, Andrej Risteski
ICML 2025 | February 2025
-
A Study of Plasticity Loss in On-Policy Deep Reinforcement Learning
Arthur Juliani, Jordan Ash
NeurIPS 2024 | May 2024
-
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
Pratyusha Sharma, Jordan Ash, Dipendra Misra
ICLR 2024 | December 2023
-
Exposing Attention Glitches with Flip-Flop Language Modeling
Bingbin Liu, Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
NeurIPS 2023 | October 2023
-
Transformers Learn Shortcuts to Automata
Bingbin Liu, Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang
ICLR | May 2023
oral presentation
-
Streaming Active Learning with Deep Neural Networks
Akanksha Saran, Safoora Yousefi, Akshay Krishnamurthy, John Langford, Jordan Ash
ICML 2023 | March 2023
-
Understanding Contrastive Learning Requires Incorporating Inductive Biases
Nikunj Umesh Saunshi, Jordan Ash, Surbhi Goel, Dipendra Kumar Misra, Cyril Zhang, Sanjeev Arora, Sham Kakade, Akshay Krishnamurthy
ICML 2022 | July 2022
-
Anti-Concentrated Confidence Bonuses for Scalable Exploration
Jordan T. Ash, Cyril Zhang, Surbhi Goel, Akshay Krishnamurthy, Sham M. Kakade
ICLR 2022 | April 2022
-
Investigating the Role of Negatives in Contrastive Representation Learning
Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Dipendra Misra
2022 International Conference on Artificial Intelligence and Statistics | February 2022
-
Gone Fishing: Neural Active Learning with Fisher Embeddings
Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Sham Kakade
NeurIPS 2021 | December 2021
-
Learning Composable Energy Surrogates for PDE Order Reduction
Alex Beatson, Jordan Ash, Geoffrey Roeder, Tianju Xue, Ryan P. Adams
NeurIPS 2020 | December 2020
-
On Warm-Starting Neural Network Training
Jordan Ash, Ryan P. Adams
NeurIPS 2020 | December 2020
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