Aaron Halfaker — accepted AI-conference papers

2026

Characterizing Deep Research: A Benchmark and Formal Definition

Abhinav Java, Ashmit Khandelwal, Sukruta Prakash Midigeshi, Aaron Halfaker, Amit Deshpande, Navin Goyal +3

ICLR 2026poster

Information tasks such as writing surveys or analytical reports require complex search and reasoning, and have recently been grouped under the umbrella of _deep research_ --- a term also adopted by recent models targeting these capabilities. Despite growing interest, the scope of the deep research t…

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2023

Logical Transformers: Infusing Logical Structures into Pre-Trained Language Models

Borui Wang, Qiuyuan Huang, Budhaditya Deb, Aaron Halfaker, Liqun Shao, Daniel McDuff +3

ACL 2023findings

Natural language contains rich logical structures and logical information, and correctly detecting and accurately understanding these logical structures and information underlying natural language texts is very crucial for NLP models’ performance on many important NLU and NLG tasks. Existing pre-tra…

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2023

On Improving Summarization Factual Consistency from Natural Language Feedback

Yixin Liu, Budhaditya Deb, Milagro Teruel, Aaron Halfaker, Dragomir Radev, Ahmed Hassan Awadallah

ACL 2023long

Despite the recent progress in language generation models, their outputs may not always meet user expectations. In this work, we study whether informational feedback in natural language can be leveraged to improve generation quality and user preference alignment. To this end, we consider factual con…

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