Daniel Khashabi
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
70
Venues
14
Active years
2011–2026
Best venue rank
A*
Where they publish
Papers
70 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | arXiv2Table: Toward Realistic Benchmarking and Evaluation for LLM-Based Literature-Review Table Generation. | Weiqi Wang, Jiefu Ou, Yangqiu Song, Benjamin Van Durme, Daniel Khashabi |
| 2026 | EACL | Query Decomposition for RAG: Balancing Exploration-Exploitation. | Roxana Petcu, Kenton Murray, Daniel Khashabi, Evangelos Kanoulas, Maarten de Rijke, Dawn J. Lawrie, Kevin Duh |
| 2026 | ECIR | Principled Context Engineering for RAG: Statistical Guarantees via Conformal Prediction. | Debashish Chakraborty, Eugene Yang, Daniel Khashabi, Dawn J. Lawrie, Kevin Duh |
| 2025 | AAAI | SELF-[IN]CORRECT: LLMs Struggle with Discriminating Self-Generated Responses. | Dongwei Jiang, Jingyu Zhang, Orion Weller, Nathaniel Weir, Benjamin Van Durme, Daniel Khashabi |
| 2025 | AAAI | WorldAPIs: The World Is Worth How Many APIs? A Thought Experiment. | Jiefu Ou, Arda Uzunoglu, Benjamin Van Durme, Daniel Khashabi |
| 2025 | ACL | 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 |
| 2025 | ACL | Core: Robust Factual Precision with Informative Sub-Claim Identification. | Zhengping Jiang, Jingyu Zhang, Nathaniel Weir, Seth Ebner, Miriam Wanner, Kate Sanders, Daniel Khashabi, Anqi Liu, Benjamin Van Durme |
| 2025 | EMNLP | Evaluating the Evaluators: Are readability metrics good measures of readability? | Isabel Cachola, Daniel Khashabi, Mark Dredze |
| 2025 | EMNLP | ICL CIPHERS: Quantifying "Learning" in In-Context Learning via Substitution Ciphers. | Zhouxiang Fang, Aayush Mishra, Muhan Gao, Anqi Liu, Daniel Khashabi |
| 2025 | EMNLP | Challenging the Evaluator: LLM Sycophancy Under User Rebuttal. | Sung Won Kim, Daniel Khashabi |
| 2025 | EMNLP | CLAIMCHECK: How Grounded are LLM Critiques of Scientific Papers? | Jiefu Ou, William Gantt Walden, Kate Sanders, Zhengping Jiang, Kaiser Sun, Jeffrey Cheng, William Jurayj, Miriam Wanner, Shaobo Liang, Candice Morgan, Seunghoon Han, Weiqi Wang, Chandler May, Hannah Recknor, Daniel Khashabi, Benjamin Van Durme |
| 2025 | EMNLP | Jailbreak Distillation: Renewable Safety Benchmarking. | Jingyu Zhang, Ahmed Elgohary, Xiawei Wang, A S. M. Iftekhar, Ahmed Magooda, Benjamin Van Durme, Daniel Khashabi, Kyle Jackson |
| 2025 | EMNLP | Certified Mitigation of Worst-Case LLM Copyright Infringement. | Jingyu Zhang, Jiacan Yu, Marc Marone, Benjamin Van Durme, Daniel Khashabi |
| 2025 | ICLR | GenEx: Generating an Explorable World. | Taiming Lu, Tianmin Shu, Alan L. Yuille, Daniel Khashabi, Jieneng Chen |
| 2025 | ICLR | Controllable Safety Alignment: Inference-Time Adaptation to Diverse Safety Requirements. | Jingyu Zhang, Ahmed Elgohary, Ahmed Magooda, Daniel Khashabi, Benjamin Van Durme |
| 2025 | ICML | SIMPLEMIX: Frustratingly Simple Mixing of Off- and On-policy Data in Language Model Preference Learning. | Tianjian Li, Daniel Khashabi |
| 2025 | IJCNLP | 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 |
| 2025 | NAACL | Upsample or Upweight? Balanced Training on Heavily Imbalanced Datasets. | Tianjian Li, Haoran Xu, Weiting Tan, Kenton Murray, Daniel Khashabi |
| 2025 | NAACL | Benchmarking Language Model Creativity: A Case Study on Code Generation. | Yining Lu, Dixuan Wang, Tianjian Li, Dongwei Jiang, Sanjeev Khudanpur, Meng Jiang, Daniel Khashabi |
| 2025 | NAACL | TurkingBench: A Challenge Benchmark for Web Agents. | Kevin Xu, Yeganeh Kordi, Tanay Nayak, Adi Asija, Yizhong Wang, Kate Sanders, Adam Byerly, Jingyu Zhang, Benjamin Van Durme, Daniel Khashabi |
| 2025 | NAACL | Verifiable by Design: Aligning Language Models to Quote from Pre-Training Data. | Jingyu Zhang, Marc Marone, Tianjian Li, Benjamin Van Durme, Daniel Khashabi |
| 2024 | ACL | k-SemStamp: A Clustering-Based Semantic Watermark for Detection of Machine-Generated Text. | Abe Bohan Hou, Jingyu Zhang, Yichen Wang, Daniel Khashabi, Tianxing He |
| 2024 | ACL | RORA: Robust Free-Text Rationale Evaluation. | Zhengping Jiang, Yining Lu, Hanjie Chen, Daniel Khashabi, Benjamin Van Durme, Anqi Liu |
| 2024 | ACL | 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 |
| 2024 | EACL | GEAR: Augmenting Language Models with Generalizable and Efficient Tool Resolution. | Yining Lu, Haoping Yu, Daniel Khashabi |
| 2024 | EACL | "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 |
| 2024 | EMNLP | Insights into LLM Long-Context Failures: When Transformers Know but Don't Tell. | Muhan Gao, Taiming Lu, Kuai Yu, Adam Byerly, Daniel Khashabi |
| 2024 | EMNLP | 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 |
| 2024 | ICLR | 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 |
| 2024 | ICLR | 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 |
| 2024 | ICML | Position: Do pretrained Transformers Learn In-Context by Gradient Descent? | Lingfeng Shen, Aayush Mishra, Daniel Khashabi |
| 2024 | NAACL | 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 |
| 2023 | ACL | 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 |
| 2023 | ACL | The Tail Wagging the Dog: Dataset Construction Biases of Social Bias Benchmarks. | Nikil Roashan Selvam, Sunipa Dev, Daniel Khashabi, Tushar Khot, Kai-Wei Chang |
| 2023 | ACL | Self-Instruct: Aligning Language Models with Self-Generated Instructions. | Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi, Hannaneh Hajishirzi |
| 2023 | EMNLP | Representation Projection Invariance Mitigates Representation Collapse. | Anastasia Razdaibiedina, Ashish Khetan, Zohar S. Karnin, Daniel Khashabi, Vivek Madan |
| 2023 | EMNLP | Flatness-Aware Prompt Selection Improves Accuracy and Sample Efficiency. | Lingfeng Shen, Weiting Tan, Boyuan Zheng, Daniel Khashabi |
| 2023 | ICLR | Generating Sequences by Learning to Self-Correct. | Sean Welleck, Ximing Lu, Peter West, Faeze Brahman, Tianxiao Shen, Daniel Khashabi, Yejin Choi |
| 2022 | ACL | Reframing Instructional Prompts to GPTk's Language. | Daniel Khashabi, Chitta Baral, Yejin Choi, Hannaneh Hajishirzi |
| 2022 | ACL | Hey AI, Can You Solve Complex Tasks by Talking to Agents? | Tushar Khot, Kyle Richardson, Daniel Khashabi, Ashish Sabharwal |
| 2022 | ACL | Cross-Task Generalization via Natural Language Crowdsourcing Instructions. | Swaroop Mishra, Daniel Khashabi, Chitta Baral, Hannaneh Hajishirzi |
| 2022 | EMNLP | ProsocialDialog: A Prosocial Backbone for Conversational Agents. | Hyunwoo Kim, Youngjae Yu, Liwei Jiang, Ximing Lu, Daniel Khashabi, Gunhee Kim, Yejin Choi, Maarten Sap |
| 2022 | EMNLP | 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 |
| 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 |
| 2022 | NAACL | Time Waits for No One! Analysis and Challenges of Temporal Misalignment. | Kelvin Luu, Daniel Khashabi, Suchin Gururangan, Karishma Mandyam, Noah A. Smith |
| 2022 | NAACL | 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 |
| 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 | 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 |
| 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 | ACL | Temporal Common Sense Acquisition with Minimal Supervision. | Ben Zhou, Qiang Ning, Daniel Khashabi, Dan Roth |
| 2020 | EMNLP | 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 |
| 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 | IJCAI | TransOMCS: From Linguistic Graphs to Commonsense Knowledge. | Hongming Zhang, Daniel Khashabi, Yangqiu Song, Dan Roth |
| 2019 | ACL | PerspectroScope: A Window to the World of Diverse Perspectives. | Sihao Chen, Daniel Khashabi, Chris Callison-Burch, Dan Roth |
| 2019 | EMNLP | "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 |
| 2019 | NAACL | Seeing Things from a Different Angle: Discovering Diverse Perspectives about Claims. | Sihao Chen, Daniel Khashabi, Wenpeng Yin, Chris Callison-Burch, Dan Roth |
| 2018 | AAAI | Question Answering as Global Reasoning Over Semantic Abstractions. | Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Dan Roth |
| 2018 | EMNLP | Zero-Shot Open Entity Typing as Type-Compatible Grounding. | Ben Zhou, Daniel Khashabi, Chen-Tse Tsai, Dan Roth |
| 2018 | LREC | 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 |
| 2018 | NAACL | Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences. | Daniel Khashabi, Snigdha Chaturvedi, Michael Roth, Shyam Upadhyay, Dan Roth |
| 2017 | CoNLL | Learning What is Essential in Questions. | Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Dan Roth |
| 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 | COLING | Better call Saul: Flexible Programming for Learning and Inference in NLP. | Parisa Kordjamshidi, Daniel Khashabi, Christos Christodoulopoulos, Bhargav Mangipudi, Sameer Singh, Dan Roth |
| 2016 | IJCAI | Question Answering via Integer Programming over Semi-Structured Knowledge. | Daniel Khashabi, Tushar Khot, Ashish Sabharwal, Peter Clark, Oren Etzioni, Dan Roth |
| 2016 | LREC | EDISON: Feature Extraction for NLP, Simplified. | Mark Sammons, Christos Christodoulopoulos, Parisa Kordjamshidi, Daniel Khashabi, Vivek Srikumar, Dan Roth |
| 2015 | NAACL | Solving Hard Coreference Problems. | Haoruo Peng, Daniel Khashabi, Dan Roth |
| 2011 | SMC | Adaptive tiled Neural Networks. | Mohammad Nokhbeh-Zaeem, Daniel Khashabi, Heidar Ali Talebi, Shiva Navabi, Faramarz Vaziri |