Adaptive tiled Neural Networks. - Mohammad Nokhbeh-Zaeem; Daniel Khashabi; Heidar Ali Talebi; Shiva Navabi; Faramarz Vaziri (SMC, 2011)

Generating Motion Patterns Using Evolutionary Computation in Digital Soccer - Masood Amoozgar; Daniel Khashabi; Milad Heydarian; Mohammad Nokhbeh-Zaeem; Saeed Bagheri Shouraki (CoRR, 2012)

Heteroscedastic Relevance Vector Machine - Daniel Khashabi; Mojtaba Ziyadi; Feng Liang (CoRR, 2013)

Joint Demosaicing and Denoising via Learned Nonparametric Random Fields. - Daniel Khashabi; Sebastian Nowozin; Jeremy Jancsary; Andrew W. Fitzgibbon (IEEE Trans. Image Process., 2014)

Solving Hard Coreference Problems. - Haoruo Peng; Daniel Khashabi; Dan Roth 001 (HLT-NAACL, 2015)

Online Learning with Adversarial Delays. - Kent Quanrud; Daniel Khashabi (NIPS, 2015)

Clustering With Side Information: From a Probabilistic Model to a Deterministic Algorithm. - Daniel Khashabi; Jeffrey Yufei Liu; John Wieting; Feng Liang (CoRR, 2015)

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 (AAAI, 2016)

Better call Saul: Flexible Programming for Learning and Inference in NLP. - Parisa Kordjamshidi; Daniel Khashabi; Christos Christodoulopoulos 001; Bhargav Mangipudi; Sameer Singh 001; Dan Roth 001 (COLING, 2016)

Question Answering via Integer Programming over Semi-Structured Knowledge. - Daniel Khashabi; Tushar Khot; Ashish Sabharwal; Peter Clark; Oren Etzioni; Dan Roth 001 (IJCAI, 2016)

EDISON: Feature Extraction for NLP, Simplified. - Mark Sammons; Christos Christodoulopoulos 001; Parisa Kordjamshidi; Daniel Khashabi; Vivek Srikumar; Dan Roth 001 (LREC, 2016)

Learning What is Essential in Questions. - Daniel Khashabi; Tushar Khot; Ashish Sabharwal; Dan Roth 001 (CoNLL, 2017)

Relational Learning and Feature Extraction by Querying over Heterogeneous Information Networks. - Parisa Kordjamshidi; Sameer Singh 001; Daniel Khashabi; Christos Christodoulopoulos 001; Mark Sammons; Saurabh Sinha; Dan Roth 001 (CoRR, 2017)

Question Answering as Global Reasoning Over Semantic Abstractions. - Daniel Khashabi; Tushar Khot; Ashish Sabharwal; Dan Roth 001 (AAAI, 2018)

Zero-Shot Open Entity Typing as Type-Compatible Grounding. - Ben Zhou; Daniel Khashabi; Chen-Tse Tsai; Dan Roth 001 (EMNLP, 2018)

CogCompNLP: Your Swiss Army Knife for NLP. - Daniel Khashabi; Mark Sammons; Ben Zhou; Tom Redman; Christos Christodoulopoulos 001; Vivek Srikumar; Nicholas Rizzolo; Lev-Arie Ratinov; Guanheng Luo; Quang Do; Chen-Tse Tsai; Subhro Roy; et al. (LREC, 2018)

Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences. - Daniel Khashabi; Snigdha Chaturvedi; Michael Roth 001; Shyam Upadhyay; Dan Roth 001 (NAACL-HLT, 2018)

PerspectroScope: A Window to the World of Diverse Perspectives. - Sihao Chen; Daniel Khashabi; Chris Callison-Burch; Dan Roth 001 (ACL (3), 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 001 (EMNLP/IJCNLP (1), 2019)

Seeing Things from a Different Angle: Discovering Diverse Perspectives about Claims. - Sihao Chen; Daniel Khashabi; Wenpeng Yin 001; Chris Callison-Burch; Dan Roth 001 (NAACL-HLT (1), 2019)

On the Capabilities and Limitations of Reasoning for Natural Language Understanding. - Daniel Khashabi; Erfan Sadeqi Azer; Tushar Khot; Ashish Sabharwal; Dan Roth 001 (CoRR, 2019)

Reasoning-Driven Question-Answering for Natural Language Understanding. - Daniel Khashabi (CoRR, 2019)

Not All Claims are Created Equal: Choosing the Right Approach to Assess Your Hypotheses. - Erfan Sadeqi Azer; Daniel Khashabi; Ashish Sabharwal; Dan Roth 001 (CoRR, 2019)

Not All Claims are Created Equal: Choosing the Right Statistical Approach to Assess Hypotheses. - Erfan Sadeqi Azer; Daniel Khashabi; Ashish Sabharwal; Dan Roth 001 (ACL, 2020)

Temporal Common Sense Acquisition with Minimal Supervision. - Ben Zhou; Qiang Ning; Daniel Khashabi; Dan Roth 001 (ACL, 2020)

Evaluating Models' Local Decision Boundaries via Contrast Sets. - Matt Gardner 001; Yoav Artzi; Victoria Basmova; Jonathan Berant; Ben Bogin; Sihao Chen; Pradeep Dasigi; Dheeru Dua; Yanai Elazar; Ananth Gottumukkala; Nitish Gupta; Hannaneh Hajishirzi; et al. (EMNLP (Findings), 2020)

More Bang for Your Buck: Natural Perturbation for Robust Question Answering. - Daniel Khashabi; Tushar Khot; Ashish Sabharwal (EMNLP (1), 2020)

UnifiedQA: Crossing Format Boundaries With a Single QA System. - Daniel Khashabi; Sewon Min; Tushar Khot; Ashish Sabharwal; Oyvind Tafjord; Peter Clark; Hannaneh Hajishirzi (EMNLP (Findings), 2020)

UNQOVERing Stereotypical Biases via Underspecified Questions. - Tao Li 039; Daniel Khashabi; Tushar Khot; Ashish Sabharwal; Vivek Srikumar (EMNLP (Findings), 2020)

TransOMCS: From Linguistic Graphs to Commonsense Knowledge. - Hongming Zhang 009; Daniel Khashabi; Yangqiu Song; Dan Roth 001 (IJCAI, 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 001; Ashish Sabharwal; Carissa Schoenick; Oyvind Tafjord; Niket Tandon; Sumithra Bhakthavatsalam; Dirk Groeneveld; et al. (AI Mag., 2020)

Evaluating NLP Models via Contrast Sets. - Matt Gardner 001; Yoav Artzi; Victoria Basmova; Jonathan Berant; Ben Bogin; Sihao Chen; Pradeep Dasigi; Dheeru Dua; Yanai Elazar; Ananth Gottumukkala; Nitish Gupta; Hanna Hajishirzi; et al. (CoRR, 2020)

Natural Perturbation for Robust Question Answering. - Daniel Khashabi; Tushar Khot; Ashish Sabharwal (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)

UnQovering Stereotyping Biases via Underspecified Questions. - Tao Li 039; Tushar Khot; Daniel Khashabi; Ashish Sabharwal; Vivek Srikumar (CoRR, 2020)

Ethical-Advice Taker: Do Language Models Understand Natural Language Interventions? - Jieyu Zhao 001; Daniel Khashabi; Tushar Khot; Ashish Sabharwal; Kai-Wei Chang (ACL/IJCNLP (Findings), 2021)

GooAQ: Open Question Answering with Diverse Answer Types. - Daniel Khashabi; Amos Ng; Tushar Khot; Ashish Sabharwal; Hannaneh Hajishirzi; Chris Callison-Burch (EMNLP (Findings), 2021)

Text Modular Networks: Learning to Decompose Tasks in the Language of Existing Models. - Tushar Khot; Daniel Khashabi; Kyle Richardson 001; Peter Clark; Ashish Sabharwal (NAACL-HLT, 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; et al. (WMT@EMNLP, 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 001; Noah A. Smith; Daniel S. Weld (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 001; Ashish Sabharwal; Carissa Schoenick; Oyvind Tafjord; Peter Clark (CoRR, 2021)

Natural Instructions: Benchmarking Generalization to New Tasks from Natural Language Instructions. - Swaroop Mishra; Daniel Khashabi; Chitta Baral; Hannaneh Hajishirzi (CoRR, 2021)

Reframing Instructional Prompts to GPTk's Language. - Swaroop Mishra; Daniel Khashabi; Chitta Baral; Yejin Choi 001; Hannaneh Hajishirzi (CoRR, 2021)

Learning to Solve Complex Tasks by Talking to Agents. - Tushar Khot; Kyle Richardson 001; Daniel Khashabi; Ashish Sabharwal (CoRR, 2021)

PROMPT WAYWARDNESS: The Curious Case of Discretized Interpretation of Continuous Prompts. - Daniel Khashabi; Shane Lyu; Sewon Min; Lianhui Qin; Kyle Richardson 001; Sameer Singh 001; Sean Welleck; Hannaneh Hajishirzi; Tushar Khot; Ashish Sabharwal; Yejin Choi 001 (CoRR, 2021)

Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies. - Mor Geva; Daniel Khashabi; Elad Segal; Tushar Khot; Dan Roth 001; Jonathan Berant (Trans. Assoc. Comput. Linguistics, 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; et al. (Trans. Assoc. Comput. Linguistics, 2021)

Reframing Instructional Prompts to GPTk's Language. - Daniel Khashabi; Chitta Baral; Yejin Choi 001; Hannaneh Hajishirzi (ACL (Findings), 2022)

Hey AI, Can You Solve Complex Tasks by Talking to Agents? - Tushar Khot; Kyle Richardson 001; Daniel Khashabi; Ashish Sabharwal (ACL (Findings), 2022)

Cross-Task Generalization via Natural Language Crowdsourcing Instructions. - Swaroop Mishra; Daniel Khashabi; Chitta Baral; Hannaneh Hajishirzi (ACL (1), 2022)

ProsocialDialog: A Prosocial Backbone for Conversational Agents. - Hyunwoo Kim 002; Youngjae Yu; Liwei Jiang; Ximing Lu; Daniel Khashabi; Gunhee Kim; Yejin Choi 001; Maarten Sap (EMNLP, 2022)

GENIE: Toward Reproducible and Standardized Human Evaluation for Text Generation. - Daniel Khashabi; Gabriel Stanovsky; Jonathan Bragg; Nicholas Lourie; Jungo Kasai; Yejin Choi 001; Noah A. Smith; Daniel S. Weld (EMNLP, 2022)

Prompt Waywardness: The Curious Case of Discretized Interpretation of Continuous Prompts. - Daniel Khashabi; Xinxi Lyu; Sewon Min; Lianhui Qin; Kyle Richardson 001; Sean Welleck; Hannaneh Hajishirzi; Tushar Khot; Ashish Sabharwal; Sameer Singh 001; Yejin Choi 001 (NAACL-HLT, 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 001; Lianhui Qin; Youngjae Yu; Rowan Zellers; Noah A. Smith; Yejin Choi 001 (NAACL-HLT, 2022)

Time Waits for No One! Analysis and Challenges of Temporal Misalignment. - Kelvin Luu; Daniel Khashabi; Suchin Gururangan; Karishma Mandyam; Noah A. Smith (NAACL-HLT, 2022)

COLD Decoding: Energy-based Constrained Text Generation with Langevin Dynamics. - Lianhui Qin; Sean Welleck; Daniel Khashabi; Yejin Choi 001 (NeurIPS, 2022)

UnifiedQA-v2: Stronger Generalization via Broader Cross-Format Training. - Daniel Khashabi; Yeganeh Kordi; Hannaneh Hajishirzi (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; et al. (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)

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 of Parametric and Non-Parametric Memories. - Alex Mallen; Akari Asai; Victor Zhong; Rajarshi Das; Daniel Khashabi; Hannaneh Hajishirzi (ACL (1), 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 (ACL (2), 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 (ACL (1), 2023)

Representation Projection Invariance Mitigates Representation Collapse. - Anastasia Razdaibiedina; Ashish Khetan; Zohar Karnin; Daniel Khashabi; Vivek Madan (EMNLP (Findings), 2023)

Flatness-Aware Prompt Selection Improves Accuracy and Sample Efficiency. - Lingfeng Shen; Weiting Tan; Boyuan Zheng; Daniel Khashabi (EMNLP (Findings), 2023)

Generating Sequences by Learning to Self-Correct. - Sean Welleck; Ximing Lu; Peter West; Faeze Brahman; Tianxiao Shen; Daniel Khashabi; Yejin Choi 001 (ICLR, 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 001 (CoRR, 2023)

Do pretrained Transformers Really Learn In-context by Gradient Descent? - Lingfeng Shen; Aayush Mishra; Daniel Khashabi (CoRR, 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

k-SemStamp: A Clustering-Based Semantic Watermark for Detection of Machine-Generated Text. - Abe Bohan Hou; Jingyu Zhang; Yichen Wang; Daniel Khashabi; Tianxing He (ACL (Findings), 2024)

RORA: Robust Free-Text Rationale Evaluation. - Zhengping Jiang; Yining Lu; Hanjie Chen; Daniel Khashabi; Benjamin Van Durme; Anqi Liu (ACL (1), 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 (ACL (Findings), 2024)

GEAR: Augmenting Language Models with Generalizable and Efficient Tool Resolution. - Yining Lu; Haoping Yu; Daniel Khashabi (EACL (1), 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 (EACL (1), 2024)

Insights into LLM Long-Context Failures: When Transformers Know but Don't Tell. - Muhan Gao; Taiming Lu; Kuai Yu; Adam Byerly; Daniel Khashabi (EMNLP (Findings), 2024)

AnaloBench: Benchmarking the Identification of Abstract and Long-context Analogies. - Xiao Ye; Andrew Wang; Jacob Choi; Yining Lu; Shreya Sharma; Lingfeng Shen; Vijay Murari Tiyyala; Nicholas Andrews; Daniel Khashabi (EMNLP, 2024)

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 (ICLR, 2024)

The Trickle-down Impact of Reward Inconsistency on RLHF. - Lingfeng Shen; Sihao Chen; Linfeng Song; Lifeng Jin; Baolin Peng; Haitao Mi; Daniel Khashabi; Dong Yu 001 (ICLR, 2024)

Position: Do pretrained Transformers Learn In-Context by Gradient Descent? - Lingfeng Shen; Aayush Mishra; Daniel Khashabi (ICML, 2024)

SemStamp: A Semantic Watermark with Paraphrastic Robustness for Text Generation. - Abe Bohan Hou; Jingyu Zhang; Tianxing He; Yichen Wang 002; Yung-Sung Chuang; Hongwei Wang; Lingfeng Shen; Benjamin Van Durme; Daniel Khashabi; Yulia Tsvetkov (NAACL-HLT, 2024)

Efficient Large Multi-modal Models via Visual Context Compression. - Jieneng Chen; Luoxin Ye; Ju He; Zhaoyang Wang; Daniel Khashabi; Alan L. Yuille (NeurIPS, 2024)

DiffNorm: Self-Supervised Normalization for Non-autoregressive Speech-to-speech Translation. - Weiting Tan; Jingyu Zhang; Lingfeng Shen; Daniel Khashabi; Philipp Koehn (NeurIPS, 2024)

AnaloBench: Benchmarking the Identification of Abstract and Long-context Analogies. - Xiao Ye; Andrew Wang; Jacob Choi; Yining Lu; Shreya Sharma 010; Lingfeng Shen; Vijay Murari Tiyyala; Nicholas Andrews; Daniel Khashabi (CoRR, 2024)

Tur[k]ingBench: A Challenge Benchmark for Web Agents. - Kevin Xu; Yeganeh Kordi; Kate Sanders 002; Yizhong Wang; Adam Byerly; Jack Zhang; Benjamin Van Durme; Daniel Khashabi (CoRR, 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)

SELF-[IN]CORRECT: LLMs Struggle with Refining Self-Generated Responses. - Dongwei Jiang; Jingyu Zhang; Orion Weller; Nathaniel Weir; Benjamin Van Durme; Daniel Khashabi (CoRR, 2024)

LLaVolta: Efficient Multi-modal Models via Stage-wise Visual Context Compression. - Jieneng Chen; Luoxin Ye; Ju He; Zhaoyang Wang; Daniel Khashabi; Alan L. Yuille (CoRR, 2024)

Core: Robust Factual Precision Scoring with Informative Sub-Claim Identification. - Zhengping Jiang; Jingyu Zhang; Nathaniel Weir; Seth Ebner; Miriam Wanner; Kate Sanders 002; Daniel Khashabi; Anqi Liu; Benjamin Van Durme (CoRR, 2024)

How Effective Is Self-Consistency for Long-Context Problems? - Adam Byerly; Daniel Khashabi (CoRR, 2024)

Generative World Explorer. - Taiming Lu; Tianmin Shu; Alan L. Yuille; Daniel Khashabi; Jieneng Chen (CoRR, 2024)

GenEx: Generating an Explorable World. - Taiming Lu; Tianmin Shu; Junfei Xiao; Luoxin Ye; Jiahao Wang 001; Cheng Peng 008; Chen Wei; Daniel Khashabi; Rama Chellappa; Alan L. Yuille; Jieneng Chen (CoRR, 2024)

SELF-[IN]CORRECT: LLMs Struggle with Discriminating Self-Generated Responses. - Dongwei Jiang; Jingyu Zhang; Orion Weller; Nathaniel Weir; Benjamin Van Durme; Daniel Khashabi (AAAI, 2025)

WorldAPIs: The World Is Worth How Many APIs? A Thought Experiment. - Jiefu Ou; Arda Uzunoglu; Benjamin Van Durme; Daniel Khashabi (AAAI, 2025)

RATIONALYST: Pre-training Process-Supervision for Improving Reasoning. - Dongwei Jiang; Guoxuan Wang; Yining Lu; Andrew Wang; Jingyu Zhang; Chuyu Liu; Benjamin Van Durme; Daniel Khashabi (ACL (1), 2025)

Core: Robust Factual Precision with Informative Sub-Claim Identification. - Zhengping Jiang; Jingyu Zhang; Nathaniel Weir; Seth Ebner; Miriam Wanner; Kate Sanders 002; Daniel Khashabi; Anqi Liu; Benjamin Van Durme (ACL (Findings), 2025)

GenEx: Generating an Explorable World. - Taiming Lu; Tianmin Shu; Alan L. Yuille; Daniel Khashabi; Jieneng Chen (ICLR, 2025)

Controllable Safety Alignment: Inference-Time Adaptation to Diverse Safety Requirements. - Jingyu Zhang; Ahmed Elgohary; Ahmed Magooda; Daniel Khashabi; Benjamin Van Durme (ICLR, 2025)

Upsample or Upweight? Balanced Training on Heavily Imbalanced Datasets. - Tianjian Li; Haoran Xu; Weiting Tan; Kenton Murray; Daniel Khashabi (NAACL (Long Papers), 2025)

Benchmarking Language Model Creativity: A Case Study on Code Generation. - Yining Lu; Dixuan Wang; Tianjian Li; Dongwei Jiang; Sanjeev Khudanpur; Meng Jiang 001; Daniel Khashabi (NAACL (Long Papers), 2025)

TurkingBench: A Challenge Benchmark for Web Agents. - Kevin Xu; Yeganeh Kordi; Tanay Nayak; Adi Asija; Yizhong Wang; Kate Sanders 002; Adam Byerly; Jingyu Zhang; Benjamin Van Durme; Daniel Khashabi (NAACL (Long Papers), 2025)

Verifiable by Design: Aligning Language Models to Quote from Pre-Training Data. - Jingyu Zhang; Marc Marone; Tianjian Li; Benjamin Van Durme; Daniel Khashabi (NAACL (Long Papers), 2025)

Can A Society of Generative Agents Simulate Human Behavior and Inform Public Health Policy? A Case Study on Vaccine Hesitancy. - Abe Bohan Hou; Hongru Du; Yichen Wang; Jingyu Zhang; Zixiao Wang; Paul Pu Liang; Daniel Khashabi; Lauren Gardner; Tianxing He (CoRR, 2025)

CLAIMCHECK: How Grounded are LLM Critiques of Scientific Papers? - Jiefu Ou; William Gantt Walden; Kate Sanders 002; Zhengping Jiang; Kaiser Sun; Jeffrey Cheng; William Jurayj; Miriam Wanner; Shaobo Liang; Candice Morgan; Seunghoon Han; Weiqi Wang 001; et al. (CoRR, 2025)

Can LLMs Generate Tabular Summaries of Science Papers? Rethinking the Evaluation Protocol. - Weiqi Wang 001; Jiefu Ou; Yangqiu Song; Benjamin Van Durme; Daniel Khashabi (CoRR, 2025)

Science Hierarchography: Hierarchical Organization of Science Literature. - Muhan Gao; Jash Shah; Weiqi Wang; Daniel Khashabi (CoRR, 2025)

Certified Mitigation of Worst-Case LLM Copyright Infringement. - Jingyu Zhang; Jiacan Yu; Marc Marone; Benjamin Van Durme; Daniel Khashabi (CoRR, 2025)

ICL CIPHERS: Quantifying "Learning" in In-Context Learning via Substitution Ciphers. - Zhouxiang Fang; Aayush Mishra; Muhan Gao; Anqi Liu; Daniel Khashabi (CoRR, 2025)

SIMPLEMIX: Frustratingly Simple Mixing of Off- and On-policy Data in Language Model Preference Learning. - Tianjian Li; Daniel Khashabi (CoRR, 2025)

Lost in the Haystack: Smaller Needles are More Difficult for LLMs to Find. - Owen Bianchi; Mathew J. Koretsky; Maya Willey; Chelsea X. Alvarado; Tanay Nayak; Adi Asija; Nicole Kuznetsov; Mike A. Nalls; Faraz Faghri; Daniel Khashabi (CoRR, 2025)

BiomedSQL: Text-to-SQL for Scientific Reasoning on Biomedical Knowledge Bases. - Mathew J. Koretsky; Maya Willey; Adi Asija; Owen Bianchi; Chelsea X. Alvarado; Tanay Nayak; Nicole Kuznetsov; Sungwon Kim; Mike A. Nalls; Daniel Khashabi; Faraz Faghri (CoRR, 2025)

Jailbreak Distillation: Renewable Safety Benchmarking. - Jingyu Zhang; Ahmed Elgohary; Xiawei Wang; A S. M. Iftekhar; Ahmed Magooda; Benjamin Van Durme; Daniel Khashabi; Kyle Jackson (CoRR, 2025)

Feedback Friction: LLMs Struggle to Fully Incorporate External Feedback. - Dongwei Jiang; Alvin Zhang; Andrew Wang; Nicholas Andrews; Daniel Khashabi (CoRR, 2025)

The Translation Barrier Hypothesis: Multilingual Generation with Large Language Models Suffers from Implicit Translation Failure. - Niyati Bafna; Tianjian Li; Kenton Murray; David R. Mortensen; David Yarowsky; Hale Sirin; Daniel Khashabi (CoRR, 2025)

Hell or High Water: Evaluating Agentic Recovery from External Failures. - Andrew Wang; Sophia Hager; Adi Asija; Daniel Khashabi; Nicholas Andrews (CoRR, 2025)