Ashish Sabharwal
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
122
Venues
17
Active years
2002–2025
Best venue rank
A*
Where they publish
Papers
122 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ICLR | DiscoveryBench: Towards Data-Driven Discovery with Large Language Models. | Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal, Bhavana Dalvi Mishra, Abhijeetsingh Meena, Aryan Prakhar, Tirth Vora, Tushar Khot, Ashish Sabharwal, Peter Clark |
| 2025 | ICLR | Answer, Assemble, Ace: Understanding How LMs Answer Multiple Choice Questions. | Sarah Wiegreffe, Oyvind Tafjord, Yonatan Belinkov, Hannaneh Hajishirzi, Ashish Sabharwal |
| 2025 | ICML | Understanding the Logic of Direct Preference Alignment through Logic. | Kyle Richardson, Vivek Srikumar, Ashish Sabharwal |
| 2025 | ICML | ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning. | Bill Yuchen Lin, Ronan Le Bras, Kyle Richardson, Ashish Sabharwal, Radha Poovendran, Peter Clark, Yejin Choi |
| 2024 | ACL | AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents. | Harsh Trivedi, Tushar Khot, Mareike Hartmann, Ruskin Manku, Vinty Dong, Edward Li, Shashank Gupta, Ashish Sabharwal, Niranjan Balasubramanian |
| 2024 | EMNLP | SUPER: Evaluating Agents on Setting Up and Executing Tasks from Research Repositories. | Ben Bogin, Kejuan Yang, Shashank Gupta, Kyle Richardson, Erin Bransom, Peter Clark, Ashish Sabharwal, Tushar Khot |
| 2024 | ICLR | Closing the Curious Case of Neural Text Degeneration. | Matthew Finlayson, John Hewitt, Alexander Koller, Swabha Swayamdipta, Ashish Sabharwal |
| 2024 | ICLR | Bias Runs Deep: Implicit Reasoning Biases in Persona-Assigned LLMs. | Shashank Gupta, Vaishnavi Shrivastava, Ameet Deshpande, Ashwin Kalyan, Peter Clark, Ashish Sabharwal, Tushar Khot |
| 2024 | ICLR | The Expressive Power of Transformers with Chain of Thought. | William Merrill, Ashish Sabharwal |
| 2024 | ICML | Position: Data-driven Discovery with Large Generative Models. | Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal, Sanchaita Hazra, Ashish Sabharwal, Peter Clark |
| 2024 | ICML | The Illusion of State in State-Space Models. | William Merrill, Jackson Petty, Ashish Sabharwal |
| 2024 | NAACL | Leveraging Code to Improve In-Context Learning for Semantic Parsing. | Ben Bogin, Shivanshu Gupta, Peter Clark, Ashish Sabharwal |
| 2024 | NAACL | QualEval: Qualitative Evaluation for Model Improvement. | Vishvak Murahari, Ameet Deshpande, Peter Clark, Tanmay Rajpurohit, Ashish Sabharwal, Karthik Narasimhan, Ashwin Kalyan |
| 2024 | NAACL | ADaPT: As-Needed Decomposition and Planning with Language Models. | Archiki Prasad, Alexander Koller, Mareike Hartmann, Peter Clark, Ashish Sabharwal, Mohit Bansal, Tushar Khot |
| 2023 | ACL | DISCO: Distilling Counterfactuals with Large Language Models. | Zeming Chen, Qiyue Gao, Antoine Bosselut, Ashish Sabharwal, Kyle Richardson |
| 2023 | ACL | Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions. | Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal |
| 2023 | EMNLP | IfQA: A Dataset for Open-domain Question Answering under Counterfactual Presuppositions. | Wenhao Yu, Meng Jiang, Peter Clark, Ashish Sabharwal |
| 2023 | EMNLP | Language Models with Rationality. | Nora Kassner, Oyvind Tafjord, Ashish Sabharwal, Kyle Richardson, Hinrich Schtze, Peter Clark |
| 2023 | EMNLP | Increasing Probability Mass on Answer Choices Does Not Always Improve Accuracy. | Sarah Wiegreffe, Matthew Finlayson, Oyvind Tafjord, Peter Clark, Ashish Sabharwal |
| 2023 | ICLR | Complexity-Based Prompting for Multi-step Reasoning. | Yao Fu, Hao Peng, Ashish Sabharwal, Peter Clark, Tushar Khot |
| 2023 | ICLR | Decomposed Prompting: A Modular Approach for Solving Complex Tasks. | Tushar Khot, Harsh Trivedi, Matthew Finlayson, Yao Fu, Kyle Richardson, Peter Clark, Ashish Sabharwal |
| 2023 | ICML | Specializing Smaller Language Models towards Multi-Step Reasoning. | Yao Fu, Hao Peng, Litu Ou, Ashish Sabharwal, Tushar Khot |
| 2022 | AAAI | Pushing the Limits of Rule Reasoning in Transformers through Natural Language Satisfiability. | Kyle Richardson, Ashish Sabharwal |
| 2022 | AAAI | Multi-Modal Answer Validation for Knowledge-Based VQA. | Jialin Wu, Jiasen Lu, Ashish Sabharwal, Roozbeh Mottaghi |
| 2022 | ACL | Hey AI, Can You Solve Complex Tasks by Talking to Agents? | Tushar Khot, Kyle Richardson, Daniel Khashabi, Ashish Sabharwal |
| 2022 | EMNLP | Breakpoint Transformers for Modeling and Tracking Intermediate Beliefs. | Kyle Richardson, Ronen Tamari, Oren Sultan, Dafna Shahaf, Reut Tsarfaty, Ashish Sabharwal |
| 2022 | EMNLP | What Makes Instruction Learning Hard? An Investigation and a New Challenge in a Synthetic Environment. | Matthew Finlayson, Kyle Richardson, Ashish Sabharwal, Peter Clark |
| 2022 | EMNLP | LILA: A Unified Benchmark for Mathematical Reasoning. | Swaroop Mishra, Matthew Finlayson, Pan Lu, Leonard Tang, Sean Welleck, Chitta Baral, Tanmay Rajpurohit, Oyvind Tafjord, Ashish Sabharwal, Peter Clark, Ashwin Kalyan |
| 2022 | EMNLP | Teaching Broad Reasoning Skills for Multi-Step QA by Generating Hard Contexts. | Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal |
| 2022 | NAACL | Prompt Waywardness: The Curious Case of Discretized Interpretation of Continuous Prompts. | Daniel Khashabi, Xinxi Lyu, Sewon Min, Lianhui Qin, Kyle Richardson, Sean Welleck, Hannaneh Hajishirzi, Tushar Khot, Ashish Sabharwal, Sameer Singh, Yejin Choi |
| 2021 | ACL | ReadOnce Transformers: Reusable Representations of Text for Transformers. | Shih-Ting Lin, Ashish Sabharwal, Tushar Khot |
| 2021 | ACL | Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions? | Jieyu Zhao, Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Kai-Wei Chang |
| 2021 | EMNLP | How much coffee was consumed during EMNLP 2019? Fermi Problems: A New Reasoning Challenge for AI. | Ashwin Kalyan, Abhinav Kumar, Arjun Chandrasekaran, Ashish Sabharwal, Peter Clark |
| 2021 | EMNLP | GooAQ: Open Question Answering with Diverse Answer Types. | Daniel Khashabi, Amos Ng, Tushar Khot, Ashish Sabharwal, Hannaneh Hajishirzi, Chris Callison-Burch |
| 2021 | NAACL | Text Modular Networks: Learning to Decompose Tasks in the Language of Existing Models. | Tushar Khot, Daniel Khashabi, Kyle Richardson, Peter Clark, Ashish Sabharwal |
| 2021 | NAACL | Temporal Reasoning on Implicit Events from Distant Supervision. | Ben Zhou, Kyle Richardson, Qiang Ning, Tushar Khot, Ashish Sabharwal, Dan Roth |
| 2020 | AAAI | QASC: A Dataset for Question Answering via Sentence Composition. | Tushar Khot, Peter Clark, Michal Guerquin, Peter Jansen, Ashish Sabharwal |
| 2020 | AAAI | Probing Natural Language Inference Models through Semantic Fragments. | Kyle Richardson, Hai Hu, Lawrence S. Moss, Ashish Sabharwal |
| 2020 | ACL | Not All Claims are Created Equal: Choosing the Right Statistical Approach to Assess Hypotheses. | Erfan Sadeqi Azer, Daniel Khashabi, Ashish Sabharwal, Dan Roth |
| 2020 | ECAI | Towards Efficient Discrete Integration via Adaptive Quantile Queries. | Fan Ding, Hanjing Wang, Ashish Sabharwal, Yexiang Xue |
| 2020 | EMNLP | A Simple Yet Strong Pipeline for HotpotQA. | Dirk Groeneveld, Tushar Khot, Mausam, Ashish Sabharwal |
| 2020 | EMNLP | More Bang for Your Buck: Natural Perturbation for Robust Question Answering. | Daniel Khashabi, Tushar Khot, Ashish Sabharwal |
| 2020 | EMNLP | UnifiedQA: Crossing Format Boundaries With a Single QA System. | Daniel Khashabi, Sewon Min, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, Hannaneh Hajishirzi |
| 2020 | EMNLP | UNQOVERing Stereotypical Biases via Underspecified Questions. | Tao Li, Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Vivek Srikumar |
| 2020 | EMNLP | Is Multihop QA in DiRe Condition? Measuring and Reducing Disconnected Reasoning. | Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal |
| 2020 | ICML | Adversarial Filters of Dataset Biases. | Ronan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula, Rowan Zellers, Matthew E. Peters, Ashish Sabharwal, Yejin Choi |
| 2019 | AAAI | QUAREL: A Dataset and Models for Answering Questions about Qualitative Relationships. | Oyvind Tafjord, Peter Clark, Matt Gardner, Wen-tau Yih, Ashish Sabharwal |
| 2019 | ACL | Exploiting Explicit Paths for Multi-hop Reading Comprehension. | Souvik Kundu, Tushar Khot, Ashish Sabharwal, Peter Clark |
| 2019 | EMNLP | What's Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering. | Tushar Khot, Ashish Sabharwal, Peter Clark |
| 2019 | NAACL | Repurposing Entailment for Multi-Hop Question Answering Tasks. | Harsh Trivedi, Heeyoung Kwon, Tushar Khot, Ashish Sabharwal, Niranjan Balasubramanian |
| 2019 | UAI | Adaptive Hashing for Model Counting. | Jonathan Kuck, Tri Dao, Shenjia Zhao, Burak Bartan, Ashish Sabharwal, Stefano Ermon |
| 2018 | AAAI | Question Answering as Global Reasoning Over Semantic Abstractions. | Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Dan Roth |
| 2018 | AAAI | SciTaiL: A Textual Entailment Dataset from Science Question Answering. | Tushar Khot, Ashish Sabharwal, Peter Clark |
| 2018 | AAAI | Approximate Inference via Weighted Rademacher Complexity. | Jonathan Kuck, Ashish Sabharwal, Stefano Ermon |
| 2018 | ACL | AdvEntuRe: Adversarial Training for Textual Entailment with Knowledge-Guided Examples. | Dongyeop Kang, Tushar Khot, Ashish Sabharwal, Eduard H. Hovy |
| 2018 | EMNLP | Bridging Knowledge Gaps in Neural Entailment via Symbolic Models. | Dongyeop Kang, Tushar Khot, Ashish Sabharwal, Peter Clark |
| 2018 | EMNLP | Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering. | Todor Mihaylov, Peter Clark, Tushar Khot, Ashish Sabharwal |
| 2018 | UAI | Adaptive Stratified Sampling for Precision-Recall Estimation. | Ashish Sabharwal, Yexiang Xue |
| 2017 | ACL | Answering Complex Questions Using Open Information Extraction. | Tushar Khot, Ashish Sabharwal, Peter Clark |
| 2017 | CoNLL | Learning What is Essential in Questions. | Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Dan Roth |
| 2017 | UAI | How Good Are My Predictions? Efficiently Approximating Precision-Recall Curves for Massive Datasets. | Ashish Sabharwal, Hanie Sedghi |
| 2016 | AAAI | Combining Retrieval, Statistics, and Inference to Answer Elementary Science Questions. | Peter Clark, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter D. Turney, Daniel Khashabi |
| 2016 | AAAI | Exact Sampling with Integer Linear Programs and Random Perturbations. | Carolyn Kim, Ashish Sabharwal, Stefano Ermon |
| 2016 | AAAI | Selecting Near-Optimal Learners via Incremental Data Allocation. | Ashish Sabharwal, Horst Samulowitz, Gerald Tesauro |
| 2016 | AAAI | Closing the Gap Between Short and Long XORs for Model Counting. | Shengjia Zhao, Sorathan Chaturapruek, Ashish Sabharwal, Stefano Ermon |
| 2016 | ICML | Beyond Parity Constraints: Fourier Analysis of Hash Functions for Inference. | Tudor Achim, Ashish Sabharwal, Stefano Ermon |
| 2016 | IJCAI | Question Answering via Integer Programming over Semi-Structured Knowledge. | Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Peter Clark, Oren Etzioni, Dan Roth |
| 2015 | CPAIOR | BDD-Guided Clause Generation. | Brian Kell, Ashish Sabharwal, Willem-Jan van Hoeve |
| 2015 | EMNLP | Exploring Markov Logic Networks for Question Answering. | Tushar Khot, Niranjan Balasubramanian, Eric Gribkoff, Ashish Sabharwal, Peter Clark, Oren Etzioni |
| 2014 | AAAI | Non-Restarting SAT Solvers with Simple Preprocessing Can Efficiently Simulate Resolution. | Paul Beame, Ashish Sabharwal |
| 2014 | AAAI | Designing Fast Absorbing Markov Chains. | Stefano Ermon, Carla P. Gomes, Ashish Sabharwal, Bart Selman |
| 2014 | CP | Insights into Parallelism with Intensive Knowledge Sharing. | Ashish Sabharwal, Horst Samulowitz |
| 2014 | CPAIOR | Parallel Combinatorial Optimization with Decision Diagrams. | David Bergman, Andr A. Cir, Ashish Sabharwal, Horst Samulowitz, Vijay A. Saraswat, Willem Jan van Hoeve |
| 2014 | ICML | Low-density Parity Constraints for Hashing-Based Discrete Integration. | Stefano Ermon, Carla P. Gomes, Ashish Sabharwal, Bart Selman |
| 2013 | AAAI | Large Landscape Conservation - Synthetic and Real-World Datasets. | Bistra Dilkina, Katherine J. Lai, Ronan LeBras, Yexiang Xue, Carla P. Gomes, Ashish Sabharwal, Jordan Suter, Kevin S. McKelvey, Michael K. Schwartz, Claire A. Montgomery |
| 2013 | AAAI | Resolution and Parallelizability: Barriers to the Efficient Parallelization of SAT Solvers. | George Katsirelos, Ashish Sabharwal, Horst Samulowitz, Laurent Simon |
| 2013 | AAAI | Automated Design of Search with Composability. | Ashish Sabharwal, Horst Samulowitz, Tom Schrijvers, Peter J. Stuckey, Guido Tack |
| 2013 | CPAIOR | Stronger Inference through Implied Literals from Conflicts and Knapsack Covers. | Tobias Achterberg, Ashish Sabharwal, Horst Samulowitz |
| 2013 | ICML | Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization. | Stefano Ermon, Carla P. Gomes, Ashish Sabharwal, Bart Selman |
| 2013 | IJCAI | Algorithm Portfolios Based on Cost-Sensitive Hierarchical Clustering. | Yuri Malitsky, Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann |
| 2013 | UAI | Optimization With Parity Constraints: From Binary Codes to Discrete Integration. | Stefano Ermon, Carla P. Gomes, Ashish Sabharwal, Bart Selman |
| 2013 | SAT | Snappy: A Simple Algorithm Portfolio. | Horst Samulowitz, Chandra Reddy, Ashish Sabharwal, Meinolf Sellmann |
| 2012 | CP | Parallel SAT Solver Selection and Scheduling. | Yuri Malitsky, Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann |
| 2012 | CPAIOR | Guiding Combinatorial Optimization with UCT. | Ashish Sabharwal, Horst Samulowitz, Chandra Reddy |
| 2012 | SAT | SatX10: A Scalable Plug&Play Parallel SAT Framework - (Tool Presentation). | Bard Bloom, David Grove, Benjamin Herta, Ashish Sabharwal, Horst Samulowitz, Vijay A. Saraswat |
| 2012 | SAT | Augmenting Clause Learning with Implied Literals - (Poster Presentation). | Arie Matsliah, Ashish Sabharwal, Horst Samulowitz |
| 2012 | SAT | Learning Back-Clauses in SAT - (Poster Presentation). | Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann |
| 2011 | AAAI | A General Nogood-Learning Framework for Pseudo-Boolean Multi-Valued SAT. | Siddhartha Jain, Ashish Sabharwal, Meinolf Sellmann |
| 2011 | CP | Algorithm Selection and Scheduling. | Serdar Kadioglu, Yuri Malitsky, Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann |
| 2011 | CP | Constraint Reasoning and Kernel Clustering for Pattern Decomposition with Scaling. | Ronan LeBras, Theodoros Damoulas, John M. Gregoire, Ashish Sabharwal, Carla P. Gomes, R. Bruce van Dover |
| 2011 | SAT | Non-Model-Based Algorithm Portfolios for SAT. | Yuri Malitsky, Ashish Sabharwal, Horst Samulowitz, Meinolf Sellmann |
| 2010 | AAAI | Approximate Inference for Clusters in Solution Spaces. | Lukas Kroc, Ashish Sabharwal, Bart Selman |
| 2010 | AAAI | Preface. | Gregory M. Provan, Ashish Sabharwal |
| 2010 | CP | An Empirical Study of Optimization for Maximizing Diffusion in Networks. | Kiyan Ahmadizadeh, Bistra Dilkina, Carla P. Gomes, Ashish Sabharwal |
| 2010 | UAI | Understanding Sampling Style Adversarial Search Methods. | Raghuram Ramanujan, Ashish Sabharwal, Bart Selman |
| 2010 | UAI | Maximizing the Spread of Cascades Using Network Design. | Daniel Sheldon, Bistra Dilkina, Adam N. Elmachtoub, Ryan Finseth, Ashish Sabharwal, Jon Conrad, Carla P. Gomes, David B. Shmoys, William Allen, Ole Amundsen, William Vaughan |
| 2010 | SAT | An Empirical Study of Optimal Noise and Runtime Distributions in Local Search. | Lukas Kroc, Ashish Sabharwal, Bart Selman |
| 2009 | CPAIOR | Backdoors to Combinatorial Optimization: Feasibility and Optimality. | Bistra Dilkina, Carla P. Gomes, Yuri Malitsky, Ashish Sabharwal, Meinolf Sellmann |
| 2009 | IJCAI | Integrating Systematic and Local Search Paradigms: A New Strategy for MaxSAT. | Lukas Kroc, Ashish Sabharwal, Carla P. Gomes, Bart Selman |
| 2009 | SAC | Message-passing and local heuristics as decimation strategies for satisfiability. | Lukas Kroc, Ashish Sabharwal, Bart Selman |
| 2009 | SAT | Backdoors in the Context of Learning. | Bistra Dilkina, Carla P. Gomes, Ashish Sabharwal |
| 2009 | SAT | Relaxed DPLL Search for MaxSAT. | Lukas Kroc, Ashish Sabharwal, Bart Selman |
| 2008 | CPAIOR | Connections in Networks: A Hybrid Approach. | Carla P. Gomes, Willem Jan van Hoeve, Ashish Sabharwal |
| 2008 | CPAIOR | Filtering Atmost1 on Pairs of Set Variables. | Willem Jan van Hoeve, Ashish Sabharwal |
| 2008 | CPAIOR | Leveraging Belief Propagation, Backtrack Search, and Statistics for Model Counting. | Lukas Kroc, Ashish Sabharwal, Bart Selman |
| 2008 | ISAIM | Tradeoffs in Backdoors: Inconsistency Detection, Dynamic Simplification, and Preprocessing. | Bistra Dilkina, Carla P. Gomes, Ashish Sabharwal |
| 2008 | ISAIM | Leveraging Belief Propagation, Backtrack Search, and Statistics for Model Counting. | Lukas Kroc, Bart Selman, Ashish Sabharwal |
| 2007 | AAAI | The Impact of Network Topology on Pure Nash Equilibria in Graphical Games. | Bistra Dilkina, Carla P. Gomes, Ashish Sabharwal |
| 2007 | AAAI | Counting CSP Solutions Using Generalized XOR Constraints. | Carla P. Gomes, Willem Jan van Hoeve, Ashish Sabharwal, Bart Selman |
| 2007 | CP | Tradeoffs in the Complexity of Backdoor Detection. | Bistra Dilkina, Carla P. Gomes, Ashish Sabharwal |
| 2007 | CPAIOR | Connections in Networks: Hardness of Feasibility Versus Optimality. | Jon Conrad, Carla P. Gomes, Willem Jan van Hoeve, Ashish Sabharwal, Jordan Suter |
| 2007 | ICALP | Paper Retraction: On the Hardness of Embeddings Between Two Finite Metrics. | Matthew Cary, Atri Rudra, Ashish Sabharwal |
| 2007 | IJCAI | From Sampling to Model Counting. | Carla P. Gomes, Jrg Hoffmann, Ashish Sabharwal, Bart Selman |
| 2007 | UAI | Survey Propagation Revisited. | Lukas Kroc, Ashish Sabharwal, Bart Selman |
| 2007 | SAT | Short XORs for Model Counting: From Theory to Practice. | Carla P. Gomes, Jrg Hoffmann, Ashish Sabharwal, Bart Selman |
| 2006 | AAAI | Model Counting: A New Strategy for Obtaining Good Bounds. | Carla P. Gomes, Ashish Sabharwal, Bart Selman |
| 2006 | CP | Revisiting the Sequence Constraint. | Willem Jan van Hoeve, Gilles Pesant, Louis-Martin Rousseau, Ashish Sabharwal |
| 2006 | SAT | QBF Modeling: Exploiting Player Symmetry for Simplicity and Efficiency. | Ashish Sabharwal, Carlos Anstegui, Carla P. Gomes, Justin W. Hart, Bart Selman |
| 2005 | AAAI | SymChaff: A Structure-Aware Satisfiability Solver. | Ashish Sabharwal |
| 2003 | IJCAI | Understanding the Power of Clause Learning. | Paul Beame, Henry A. Kautz, Ashish Sabharwal |
| 2003 | SAT | Using Problem Structure for Efficient Clause Learning. | Ashish Sabharwal, Paul Beame, Henry A. Kautz |
| 2002 | FOCS | Bounded-Depth Frege Lower Bounds for Weaker Pigeonhole Principles. | Josh Buresh-Oppenheim, Paul Beame, Toniann Pitassi, Ran Raz, Ashish Sabharwal |