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- Ashish Sabharwal
AI2, Allen Institute for Artificial Intelligence, Seattle, USA
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Publication search results
found 225 matches
- 2024
- Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal, Sanchaita Hazra, Ashish Sabharwal, Peter Clark:
Data-driven Discovery with Large Generative Models. CoRR abs/2402.13610 (2024) - Lena Strobl, Dana Angluin, David Chiang, Jonathan Rawski, Ashish Sabharwal:
Transformers as Transducers. CoRR abs/2404.02040 (2024) - 2023
- Zeming Chen, Qiyue Gao, Antoine Bosselut, Ashish Sabharwal, Kyle Richardson:
DISCO: Distilling Counterfactuals with Large Language Models. ACL (1) 2023: 5514-5528 - Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions. ACL (1) 2023: 10014-10037 - Wenhao Yu, Meng Jiang, Peter Clark, Ashish Sabharwal:
IfQA: A Dataset for Open-domain Question Answering under Counterfactual Presuppositions. EMNLP 2023: 8276-8288 - Nora Kassner, Oyvind Tafjord, Ashish Sabharwal, Kyle Richardson, Hinrich Schütze, Peter Clark:
Language Models with Rationality. EMNLP 2023: 14190-14201 - Sarah Wiegreffe, Matthew Finlayson, Oyvind Tafjord, Peter Clark, Ashish Sabharwal:
Increasing Probability Mass on Answer Choices Does Not Always Improve Accuracy. EMNLP 2023: 8392-8417 - Yao Fu, Hao Peng, Ashish Sabharwal, Peter Clark, Tushar Khot:
Complexity-Based Prompting for Multi-step Reasoning. ICLR 2023 - Tushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu, Kyle Richardson, Peter Clark, Ashish Sabharwal:
Decomposed Prompting: A Modular Approach for Solving Complex Tasks. ICLR 2023 - Yao Fu, Hao Peng, Litu Ou, Ashish Sabharwal, Tushar Khot:
Specializing Smaller Language Models towards Multi-Step Reasoning. ICML 2023: 10421-10430 - William Merrill, Ashish Sabharwal:
A Logic for Expressing Log-Precision Transformers. NeurIPS 2023 - Yao Fu, Hao Peng, Litu Ou, Ashish Sabharwal, Tushar Khot:
Specializing Smaller Language Models towards Multi-Step Reasoning. CoRR abs/2301.12726 (2023) - Wenhao Yu, Zhihan Zhang, Zhenwen Liang, Meng Jiang, Ashish Sabharwal:
Improving Language Models via Plug-and-Play Retrieval Feedback. CoRR abs/2305.14002 (2023) - Wenhao Yu, Meng Jiang, Peter Clark, Ashish Sabharwal:
IfQA: A Dataset for Open-domain Question Answering under Counterfactual Presuppositions. CoRR abs/2305.14010 (2023) - Nora Kassner, Oyvind Tafjord, Ashish Sabharwal, Kyle Richardson, Hinrich Schütze, Peter Clark:
Language Models with Rationality. CoRR abs/2305.14250 (2023) - Sarah Wiegreffe, Matthew Finlayson, Oyvind Tafjord, Peter Clark, Ashish Sabharwal:
Attentiveness to Answer Choices Doesn't Always Entail High QA Accuracy. CoRR abs/2305.14596 (2023) - Matthew Finlayson, John Hewitt, Alexander Koller, Swabha Swayamdipta, Ashish Sabharwal:
Closing the Curious Case of Neural Text Degeneration. CoRR abs/2310.01693 (2023) - William Merrill, Ashish Sabharwal:
The Expressive Power of Transformers with Chain of Thought. CoRR abs/2310.07923 (2023) - Vishvak Murahari, Ameet Deshpande, Peter Clark, Tanmay Rajpurohit, Ashish Sabharwal, Karthik Narasimhan, Ashwin Kalyan:
QualEval: Qualitative Evaluation for Model Improvement. CoRR abs/2311.02807 (2023) - Shashank Gupta, Vaishnavi Shrivastava, Ameet Deshpande, Ashwin Kalyan, Peter Clark, Ashish Sabharwal, Tushar Khot:
Bias Runs Deep: Implicit Reasoning Biases in Persona-Assigned LLMs. CoRR abs/2311.04892 (2023) - Archiki Prasad, Alexander Koller, Mareike Hartmann, Peter Clark, Ashish Sabharwal, Mohit Bansal, Tushar Khot:
ADaPT: As-Needed Decomposition and Planning with Language Models. CoRR abs/2311.05772 (2023) - Ben Bogin, Shivanshu Gupta, Peter Clark, Ashish Sabharwal:
Leveraging Code to Improve In-context Learning for Semantic Parsing. CoRR abs/2311.09519 (2023) - 2022
- William Merrill, Ashish Sabharwal, Noah A. Smith:
Saturated Transformers are Constant-Depth Threshold Circuits. Trans. Assoc. Comput. Linguistics 10: 843-856 (2022) - Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
♫ MuSiQue: Multihop Questions via Single-hop Question Composition. Trans. Assoc. Comput. Linguistics 10: 539-554 (2022) - Kyle Richardson, Ashish Sabharwal:
Pushing the Limits of Rule Reasoning in Transformers through Natural Language Satisfiability. AAAI 2022: 11209-11219 - Jialin Wu, Jiasen Lu, Ashish Sabharwal, Roozbeh Mottaghi:
Multi-Modal Answer Validation for Knowledge-Based VQA. AAAI 2022: 2712-2721 - Tushar Khot, Kyle Richardson, Daniel Khashabi, Ashish Sabharwal:
Hey AI, Can You Solve Complex Tasks by Talking to Agents? ACL (Findings) 2022: 1808-1823 - Kyle Richardson, Ronen Tamari, Oren Sultan, Dafna Shahaf, Reut Tsarfaty, Ashish Sabharwal:
Breakpoint Transformers for Modeling and Tracking Intermediate Beliefs. EMNLP 2022: 9703-9719 - Matthew Finlayson, Kyle Richardson, Ashish Sabharwal, Peter Clark:
What Makes Instruction Learning Hard? An Investigation and a New Challenge in a Synthetic Environment. EMNLP 2022: 414-426 - Swaroop Mishra, Matthew Finlayson, Pan Lu, Leonard Tang, Sean Welleck, Chitta Baral, Tanmay Rajpurohit, Oyvind Tafjord, Ashish Sabharwal, Peter Clark, Ashwin Kalyan:
LILA: A Unified Benchmark for Mathematical Reasoning. EMNLP 2022: 5807-5832
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