Papers by Brian Wong
FOLIO: Natural Language Reasoning with First-Order Logic (2024.emnlp-main)
Copied to clipboard
Simeng Han, Hailey Schoelkopf, Yilun Zhao, Zhenting Qi, Martin Riddell, Wenfei Zhou, James Coady, David Peng, Yujie Qiao, Luke Benson, Lucy Sun, Alexander Wardle-Solano, Hannah Szabó, Ekaterina Zubova, Matthew Burtell, Jonathan Fan, Yixin Liu, Brian Wong, Malcolm Sailor, Ansong Ni, Linyong Nan, Jungo Kasai, Tao Yu, Rui Zhang, Alexander Fabbri, Wojciech Kryscinski, Semih Yavuz, Ye Liu, Xi Lin, Shafiq Joty, Yingbo Zhou, Caiming Xiong, Rex Ying, Arman Cohan, Dragomir Radev
| Challenge: | Existing benchmarks for logical reasoning in large language models lack language naturalness or limited complexity. |
| Approach: | They propose to use first-order logic annotations to evaluate logical reasoning capabilities of large language models. |
| Outcome: | The proposed dataset evaluates the FOL reasoning ability of supervised fine-tuning on medium-sized language models. |
ParseJargon: Personalized Real-time Jargon Support in Online Meetings (2026.acl-demo)
Copied to clipboard
| Challenge: | Recent advances in speech-to-text technologies and large language models (LLMs) have the potential to overcome these limitations with automated, real-time jargon support. |
| Approach: | They built an interactive LLM-powered system that provides real-time personalized jargon support tailored to users’ individual backgrounds in online meetings. |
| Outcome: | The proposed system provides more precise jargon identification and enhanced participants’ comprehension, engagement, and appreciation of colleagues’ work. |