Daniel Khashabi

According to our database, Daniel Khashabi authored at least 78 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Dated Data: Tracing Knowledge Cutoffs in Large Language Models.

Jeffrey Cheng, Marc Marone, Orion Weller, Dawn J. Lawrie, Daniel Khashabi, Benjamin Van Durme

CoRR, 2024

Tur[k]ingBench: A Challenge Benchmark for Web Agents.

Kevin Xu, Yeganeh Kordi, Kate Sanders, Yizhong Wang, Adam Byerly, Jack Zhang, Benjamin Van Durme, Daniel Khashabi

CoRR, 2024

RORA: Robust Free-Text Rationale Evaluation.

Zhengping Jiang, Yining Lu, Hanjie Chen, Daniel Khashabi, Benjamin Van Durme, Anqi Liu

CoRR, 2024

AnaloBench: Benchmarking the Identification of Abstract and Long-context Analogies.

Xiao Ye, Andrew Wang, Jacob Choi, Yining Lu, Shreya Sharma, Lingfeng Shen, Vijay Tiyyala, Nicholas Andrews, Daniel Khashabi

CoRR, 2024

k-SemStamp: A Clustering-Based Semantic Watermark for Detection of Machine-Generated Text.

Abe Bohan Hou, Jingyu Zhang, Yichen Wang, Daniel Khashabi, Tianxing He

CoRR, 2024

The Language Barrier: Dissecting Safety Challenges of LLMs in Multilingual Contexts.

Lingfeng Shen, Weiting Tan, Sihao Chen, Yunmo Chen, Jingyu Zhang, Haoran Xu, Boyuan Zheng, Philipp Koehn, Daniel Khashabi

CoRR, 2024

"According to . . . ": Prompting Language Models Improves Quoting from Pre-Training Data.

Orion Weller, Marc Marone, Nathaniel Weir, Dawn J. Lawrie, Daniel Khashabi, Benjamin Van Durme

Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, 2024

GEAR: Augmenting Language Models with Generalizable and Efficient Tool Resolution.

Yining Lu, Haoping Yu, Daniel Khashabi

Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, 2024

2023

Do pretrained Transformers Really Learn In-context by Gradient Descent?

Lingfeng Shen, Aayush Mishra, Daniel Khashabi

CoRR, 2023

SemStamp: A Semantic Watermark with Paraphrastic Robustness for Text Generation.

Abe Bohan Hou, Jingyu Zhang, Tianxing He, Yichen Wang, Yung-Sung Chuang, Hongwei Wang, Lingfeng Shen, Benjamin Van Durme, Daniel Khashabi, Yulia Tsvetkov

CoRR, 2023

Error Norm Truncation: Robust Training in the Presence of Data Noise for Text Generation Models.

Tianjian Li, Haoran Xu, Philipp Koehn, Daniel Khashabi, Kenton Murray

CoRR, 2023

The Trickle-down Impact of Reward (In-)consistency on RLHF.

Lingfeng Shen, Sihao Chen, Linfeng Song, Lifeng Jin, Baolin Peng, Haitao Mi, Daniel Khashabi, Dong Yu

CoRR, 2023

Generating Sequences by Learning to Self-Correct.

Sean Welleck, Ximing Lu, Peter West, Faeze Brahman, Tianxiao Shen, Daniel Khashabi, Yejin Choi

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Flatness-Aware Prompt Selection Improves Accuracy and Sample Efficiency.

Lingfeng Shen, Weiting Tan, Boyuan Zheng, Daniel Khashabi

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Representation Projection Invariance Mitigates Representation Collapse.

Anastasia Razdaibiedina, Ashish Khetan, Zohar Karnin, Daniel Khashabi, Vivek Madan

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Self-Instruct: Aligning Language Models with Self-Generated Instructions.

Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi, Hannaneh Hajishirzi

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

The Tail Wagging the Dog: Dataset Construction Biases of Social Bias Benchmarks.

Nikil Roashan Selvam, Sunipa Dev, Daniel Khashabi, Tushar Khot, Kai-Wei Chang

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories.

Alex Mallen, Akari Asai, Victor Zhong, Rajarshi Das, Daniel Khashabi, Hannaneh Hajishirzi

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Self-Instruct: Aligning Language Model with Self Generated Instructions.

Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi, Hannaneh Hajishirzi

CoRR, 2022

When Not to Trust Language Models: Investigating Effectiveness and Limitations of Parametric and Non-Parametric Memories.

Alex Mallen, Akari Asai, Victor Zhong, Rajarshi Das, Hannaneh Hajishirzi, Daniel Khashabi

CoRR, 2022

Benchmarking Generalization via In-Context Instructions on 1, 600+ Language Tasks.

Yizhong Wang, Swaroop Mishra, Pegah Alipoormolabashi, Yeganeh Kordi, Amirreza Mirzaei, Anjana Arunkumar, Arjun Ashok, Arut Selvan Dhanasekaran, Atharva Naik, David Stap, Eshaan Pathak, Giannis Karamanolakis, Haizhi Gary Lai, Ishan Purohit, Ishani Mondal, Jacob Anderson, Kirby Kuznia, Krima Doshi, Maitreya Patel, Kuntal Kumar Pal, Mehrad Moradshahi, Mihir Parmar, Mirali Purohit, Neeraj Varshney, Phani Rohitha Kaza, Pulkit Verma, Ravsehaj Singh Puri, Rushang Karia, Shailaja Keyur Sampat, Savan Doshi, Siddhartha Mishra, Sujan Reddy A, Sumanta Patro, Tanay Dixit, Xudong Shen, Chitta Baral, Yejin Choi, Hannaneh Hajishirzi, Noah A. Smith, Daniel Khashabi

CoRR, 2022

UnifiedQA-v2: Stronger Generalization via Broader Cross-Format Training.

Daniel Khashabi, Yeganeh Kordi, Hannaneh Hajishirzi

CoRR, 2022

COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamics.

Lianhui Qin, Sean Welleck, Daniel Khashabi, Yejin Choi

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Time Waits for No One! Analysis and Challenges of Temporal Misalignment.

Kelvin Luu, Daniel Khashabi, Suchin Gururangan, Karishma Mandyam, Noah A. Smith

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

NeuroLogic A*esque Decoding: Constrained Text Generation with Lookahead Heuristics.

Ximing Lu, Sean Welleck, Peter West, Liwei Jiang, Jungo Kasai, Daniel Khashabi, Ronan Le Bras, Lianhui Qin, Youngjae Yu, Rowan Zellers, Noah A. Smith, Yejin Choi

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

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

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

GENIE: Toward Reproducible and Standardized Human Evaluation for Text Generation.

Daniel Khashabi, Gabriel Stanovsky, Jonathan Bragg, Nicholas Lourie, Jungo Kasai, Yejin Choi, Noah A. Smith, Daniel S. Weld

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

ProsocialDialog: A Prosocial Backbone for Conversational Agents.

Hyunwoo Kim, Youngjae Yu, Liwei Jiang, Ximing Lu, Daniel Khashabi, Gunhee Kim, Yejin Choi, Maarten Sap

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Cross-Task Generalization via Natural Language Crowdsourcing Instructions.

Swaroop Mishra, Daniel Khashabi, Chitta Baral, Hannaneh Hajishirzi

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Hey AI, Can You Solve Complex Tasks by Talking to Agents?

Tushar Khot, Kyle Richardson, Daniel Khashabi, Ashish Sabharwal

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

Reframing Instructional Prompts to GPTk's Language.

Daniel Khashabi, Chitta Baral, Yejin Choi, Hannaneh Hajishirzi

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021

ParsiNLU: A Suite of Language Understanding Challenges for Persian.

Daniel Khashabi, Arman Cohan, Siamak Shakeri, Pedram Hosseini, Pouya Pezeshkpour, Malihe Alikhani, Moin Aminnaseri, Marzieh Bitaab, Faeze Brahman, Sarik Ghazarian, Mozhdeh Gheini, Arman Kabiri, Rabeeh Karimi Mahabadi, Omid Memarrast, Ahmadreza Mosallanezhad, Erfan Noury, Shahab Raji, Mohammad Sadegh Rasooli, Sepideh Sadeghi, Erfan Sadeqi Azer, Niloofar Safi Samghabadi, Mahsa Shafaei, Saber Sheybani, Ali Tazarv, Yadollah Yaghoobzadeh

Trans. Assoc. Comput. Linguistics, 2021

Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies.

Mor Geva, Daniel Khashabi, Elad Segal, Tushar Khot, Dan Roth, Jonathan Berant

Trans. Assoc. Comput. Linguistics, 2021

PROMPT WAYWARDNESS: The Curious Case of Discretized Interpretation of Continuous Prompts.

Daniel Khashabi, Shane Lyu, Sewon Min, Lianhui Qin, Kyle Richardson, Sameer Singh, Sean Welleck, Hannaneh Hajishirzi, Tushar Khot, Ashish Sabharwal, Yejin Choi

CoRR, 2021

Learning to Solve Complex Tasks by Talking to Agents.

Tushar Khot, Kyle Richardson, Daniel Khashabi, Ashish Sabharwal

CoRR, 2021

Reframing Instructional Prompts to GPTk's Language.

Swaroop Mishra, Daniel Khashabi, Chitta Baral, Yejin Choi, Hannaneh Hajishirzi

CoRR, 2021

Natural Instructions: Benchmarking Generalization to New Tasks from Natural Language Instructions.

Swaroop Mishra, Daniel Khashabi, Chitta Baral, Hannaneh Hajishirzi

CoRR, 2021

Think you have Solved Direct-Answer Question Answering? Try ARC-DA, the Direct-Answer AI2 Reasoning Challenge.

Sumithra Bhakthavatsalam, Daniel Khashabi, Tushar Khot, Bhavana Dalvi Mishra, Kyle Richardson, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord, Peter Clark

CoRR, 2021

GENIE: A Leaderboard for Human-in-the-Loop Evaluation of Text Generation.

Daniel Khashabi, Gabriel Stanovsky, Jonathan Bragg, Nicholas Lourie, Jungo Kasai, Yejin Choi, Noah A. Smith, Daniel S. Weld

CoRR, 2021

Findings of the 2021 Conference on Machine Translation (WMT21).

Farhad Akhbardeh, Arkady Arkhangorodsky, Magdalena Biesialska, Ondrej Bojar, Rajen Chatterjee, Vishrav Chaudhary, Marta R. Costa-jussà, Cristina España-Bonet, Angela Fan, Christian Federmann, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Barry Haddow, Leonie Harter, Kenneth Heafield, Christopher Homan, Matthias Huck, Kwabena Amponsah-Kaakyire, Jungo Kasai, Daniel Khashabi, Kevin Knight, Tom Kocmi, Philipp Koehn, Nicholas Lourie, Christof Monz, Makoto Morishita, Masaaki Nagata, Ajay Nagesh, Toshiaki Nakazawa, Matteo Negri, Santanu Pal, Allahsera Auguste Tapo, Marco Turchi, Valentin Vydrin, Marcos Zampieri

Proceedings of the Sixth Conference on Machine Translation, 2021

Text Modular Networks: Learning to Decompose Tasks in the Language of Existing Models.

Tushar Khot, Daniel Khashabi, Kyle Richardson, Peter Clark, Ashish Sabharwal

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

GooAQ: Open Question Answering with Diverse Answer Types.

Daniel Khashabi, Amos Ng, Tushar Khot, Ashish Sabharwal, Hannaneh Hajishirzi, Chris Callison-Burch

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions?

Jieyu Zhao, Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Kai-Wei Chang

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020

UnQovering Stereotyping Biases via Underspecified Questions.

Tao Li, Tushar Khot, Daniel Khashabi, Ashish Sabharwal, Vivek Srikumar

CoRR, 2020

UnifiedQA: Crossing Format Boundaries With a Single QA System.

Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, Hannaneh Hajishirzi

CoRR, 2020

Natural Perturbation for Robust Question Answering.

Daniel Khashabi, Tushar Khot, Ashish Sabharwal

CoRR, 2020

Evaluating NLP Models via Contrast Sets.

Matt Gardner, Yoav Artzi, Victoria Basmova, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hanna Hajishirzi, Gabriel Ilharco, Daniel Khashabi, Kevin Lin, Jiangming Liu, Nelson F. Liu, Phoebe Mulcaire, Qiang Ning, Sameer Singh, Noah A. Smith, Sanjay Subramanian, Reut Tsarfaty, Eric Wallace, Ally Zhang, Ben Zhou

CoRR, 2020

From 'F' to 'A' on the N.Y. Regents Science Exams: An Overview of the Aristo Project.

Peter Clark, Oren Etzioni, Tushar Khot, Daniel Khashabi, Bhavana Dalvi Mishra, Kyle Richardson, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord, Niket Tandon, Sumithra Bhakthavatsalam, Dirk Groeneveld, Michal Guerquin, Michael Schmitz

AI Mag., 2020

TransOMCS: From Linguistic Graphs to Commonsense Knowledge.

Hongming Zhang, Daniel Khashabi, Yangqiu Song, Dan Roth

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

UNQOVERing Stereotypical Biases via Underspecified Questions.

Tao Li, Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Vivek Srikumar

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

UnifiedQA: Crossing Format Boundaries With a Single QA System.

Daniel Khashabi, Sewon Min, Tushar Khot, Ashish Sabharwal, Oyvind Tafjord, Peter Clark, Hannaneh Hajishirzi

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

More Bang for Your Buck: Natural Perturbation for Robust Question Answering.

Daniel Khashabi, Tushar Khot, Ashish Sabharwal

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Evaluating Models' Local Decision Boundaries via Contrast Sets.

Matt Gardner, Yoav Artzi, Victoria Basmova, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hannaneh Hajishirzi, Gabriel Ilharco, Daniel Khashabi, Kevin Lin, Jiangming Liu, Nelson F. Liu, Phoebe Mulcaire, Qiang Ning, Sameer Singh, Noah A. Smith, Sanjay Subramanian, Reut Tsarfaty, Eric Wallace, Ally Zhang, Ben Zhou

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Temporal Common Sense Acquisition with Minimal Supervision.

Ben Zhou, Qiang Ning, Daniel Khashabi, Dan Roth

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Not All Claims are Created Equal: Choosing the Right Statistical Approach to Assess Hypotheses.

Erfan Sadeqi Azer, Daniel Khashabi, Ashish Sabharwal, Dan Roth

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Not All Claims are Created Equal: Choosing the Right Approach to Assess Your Hypotheses.

Erfan Sadeqi Azer, Daniel Khashabi, Ashish Sabharwal, Dan Roth

CoRR, 2019

Reasoning-Driven Question-Answering for Natural Language Understanding.

Daniel Khashabi

CoRR, 2019

On the Capabilities and Limitations of Reasoning for Natural Language Understanding.

Daniel Khashabi, Erfan Sadeqi Azer, Tushar Khot, Ashish Sabharwal, Dan Roth

CoRR, 2019

Seeing Things from a Different Angle: Discovering Diverse Perspectives about Claims.

Sihao Chen, Daniel Khashabi, Wenpeng Yin, Chris Callison-Burch, Dan Roth

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

"Going on a vacation" takes longer than "Going for a walk": A Study of Temporal Commonsense Understanding.

Ben Zhou, Daniel Khashabi, Qiang Ning, Dan Roth

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

PerspectroScope: A Window to the World of Diverse Perspectives.

Sihao Chen, Daniel Khashabi, Chris Callison-Burch, Dan Roth

Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018

Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences.

Daniel Khashabi, Snigdha Chaturvedi, Michael Roth, Shyam Upadhyay, Dan Roth

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

CogCompNLP: Your Swiss Army Knife for NLP.

Daniel Khashabi, Mark Sammons, Ben Zhou, Tom Redman, Christos Christodoulopoulos, Vivek Srikumar, Nicholas Rizzolo, Lev-Arie Ratinov, Guanheng Luo, Quang Do, Chen-Tse Tsai, Subhro Roy, Stephen Mayhew, Zhili Feng, John Wieting, Xiaodong Yu, Yangqiu Song, Shashank Gupta, Shyam Upadhyay, Naveen Arivazhagan, Qiang Ning, Shaoshi Ling, Dan Roth

Proceedings of the Eleventh International Conference on Language Resources and Evaluation, 2018

Zero-Shot Open Entity Typing as Type-Compatible Grounding.

Ben Zhou, Daniel Khashabi, Chen-Tse Tsai, Dan Roth

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Question Answering as Global Reasoning Over Semantic Abstractions.

Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Dan Roth

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Relational Learning and Feature Extraction by Querying over Heterogeneous Information Networks.

Parisa Kordjamshidi, Sameer Singh, Daniel Khashabi, Christos Christodoulopoulos, Mark Sammons, Saurabh Sinha, Dan Roth

CoRR, 2017

Learning What is Essential in Questions.

Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Dan Roth

Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), 2017

2016

EDISON: Feature Extraction for NLP, Simplified.

Mark Sammons, Christos Christodoulopoulos, Parisa Kordjamshidi, Daniel Khashabi, Vivek Srikumar, Dan Roth

Proceedings of the Tenth International Conference on Language Resources and Evaluation LREC 2016, 2016

Question Answering via Integer Programming over Semi-Structured Knowledge.

Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Peter Clark, Oren Etzioni, Dan Roth

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Better call Saul: Flexible Programming for Learning and Inference in NLP.

Parisa Kordjamshidi, Daniel Khashabi, Christos Christodoulopoulos, Bhargav Mangipudi, Sameer Singh, Dan Roth

Proceedings of the COLING 2016, 2016

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

Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015

Clustering With Side Information: From a Probabilistic Model to a Deterministic Algorithm.

Daniel Khashabi, Jeffrey Yufei Liu, John Wieting, Feng Liang

CoRR, 2015

Online Learning with Adversarial Delays.

Kent Quanrud, Daniel Khashabi

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Solving Hard Coreference Problems.

Haoruo Peng, Daniel Khashabi, Dan Roth

Proceedings of the NAACL HLT 2015, The 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, USA, May 31, 2015

2014

Joint Demosaicing and Denoising via Learned Nonparametric Random Fields.

Daniel Khashabi, Sebastian Nowozin, Jeremy Jancsary, Andrew W. Fitzgibbon

IEEE Trans. Image Process., 2014

2013

Heteroscedastic Relevance Vector Machine

Daniel Khashabi, Mojtaba Ziyadi, Feng Liang

CoRR, 2013

2012

Generating Motion Patterns Using Evolutionary Computation in Digital Soccer

Masood Amoozgar, Daniel Khashabi, Milad Heydarian, Mohammad Nokhbeh-Zaeem, Saeed Bagheri Shouraki

CoRR, 2012

2011

Adaptive tiled Neural Networks.

Mohammad Nokhbeh-Zaeem, Daniel Khashabi, Heidar Ali Talebi, Shiva Navabi, Faramarz Vaziri

Proceedings of the IEEE International Conference on Systems, 2011