| 2026 | ACL | PrefixNLI: Detecting Factual Inconsistencies as Soon as They Arise. | Sapir Harary, Eran Hirsch, Aviv Slobodkin, David Wan, Mohit Bansal, Ido Dagan |
| 2026 | EACL | DART: Leveraging Multi-Agent Disagreement for Tool Recruitment in Multimodal Reasoning. | Nithin Sivakumaran, Justin Chih-Yao Chen, David Wan, Yue Zhang, Jaehong Yoon, Elias Stengel-Eskin, Mohit Bansal |
| 2025 | ACL | LAQuer: Localized Attribution Queries in Content-grounded Generation. | Eran Hirsch, Aviv Slobodkin, David Wan, Elias Stengel-Eskin, Mohit Bansal, Ido Dagan |
| 2025 | NAACL | MAMM-Refine: A Recipe for Improving Faithfulness in Generation with Multi-Agent Collaboration. | David Wan, Justin Chih-Yao Chen, Elias Stengel-Eskin, Mohit Bansal |
| 2025 | NAACL | On Positional Bias of Faithfulness for Long-form Summarization. | David Wan, Jesse Vig, Mohit Bansal, Shafiq Joty |
| 2024 | ACL | ACUEval: Fine-grained Hallucination Evaluation and Correction for Abstractive Summarization. | David Wan, Koustuv Sinha, Srini Iyer, Asli Celikyilmaz, Mohit Bansal, Ramakanth Pasunuru |
| 2024 | ECCV | Contrastive Region Guidance: Improving Grounding in Vision-Language Models Without Training. | David Wan, Jaemin Cho, Elias Stengel-Eskin, Mohit Bansal |
| 2023 | ACL | Extractive is not Faithful: An Investigation of Broad Unfaithfulness Problems in Extractive Summarization. | Shiyue Zhang, David Wan, Mohit Bansal |
| 2023 | EACL | Faithfulness-Aware Decoding Strategies for Abstractive Summarization. | David Wan, Mengwen Liu, Kathleen R. McKeown, Markus Dreyer, Mohit Bansal |
| 2023 | EMNLP | HistAlign: Improving Context Dependency in Language Generation by Aligning with History. | David Wan, Shiyue Zhang, Mohit Bansal |
| 2022 | COLING | Constrained Regeneration for Cross-Lingual Query-Focused Extractive Summarization. | Elsbeth Turcan, David Wan, Faisal Ladhak, Petra Galusckov, Sukanta Sen, Svetlana Tchistiakova, Weijia Xu, Marine Carpuat, Kenneth Heafield, Douglas W. Oard, Kathleen R. McKeown |
| 2022 | EMNLP | Evaluating and Improving Factuality in Multimodal Abstractive Summarization. | David Wan, Mohit Bansal |
| 2022 | NAACL | FactPEGASUS: Factuality-Aware Pre-training and Fine-tuning for Abstractive Summarization. | David Wan, Mohit Bansal |
| 2021 | EACL | Segmenting Subtitles for Correcting ASR Segmentation Errors. | David Wan, Chris Kedzie, Faisal Ladhak, Elsbeth Turcan, Petra Galusckov, Elena Zotkina, Zhengping Jiang, Peter Bell, Kathleen R. McKeown |
| 2020 | LREC | Subtitles to Segmentation: Improving Low-Resource Speech-to-TextTranslation Pipelines. | David Wan, Zhengping Jiang, Chris Kedzie, Elsbeth Turcan, Peter Bell, Kathy McKeown |