Papers by Kevin Meng
Can We Edit LLMs for Long-Tail Biomedical Knowledge? (2025.findings-emnlp)
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| Challenge: | Existing knowledge editing methods can enhance LLMs' performance on long-tail biomedical knowledge, but their performance on high-frequency popular knowledge remains inferior to that on high frequency popular knowledge. |
| Approach: | They conduct the first comprehensive study to investigate the effectiveness of knowledge editing methods for editing long-tail biomedical knowledge. |
| Outcome: | The proposed methods improve LLMs' performance on long-tail biomedical knowledge, but their performance on high-frequency popular knowledge remains inferior even after editing. |
A Dashboard for Mitigating the COVID-19 Misinfodemic (2021.eacl-demos)
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Zhengyuan Zhu, Kevin Meng, Josue Caraballo, Israa Jaradat, Xiao Shi, Zeyu Zhang, Farahnaz Akrami, Haojin Liao, Fatma Arslan, Damian Jimenez, Mohanmmed Samiul Saeef, Paras Pathak, Chengkai Li
| Challenge: | a new public dashboard aims to understand the impact of the COVID-19 misinfodemic on Twitter . the dashboard uses a curated catalog of COVId-19 related facts and debunks of misinformation . |
| Approach: | They propose a public dashboard that matches tweets with COVID-19 misinformation . they also propose experiments to analyze the spread of misinformation on twitter . |
| Outcome: | The proposed dashboard uses a curated catalog of COVID-19 related facts and debunks misinformation . it shows the most prevalent information from the catalog among Twitter users in user-selected geographic regions . |
EnDive: A Cross-Dialect Benchmark for Fairness and Performance in Large Language Models (2025.findings-emnlp)
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| Challenge: | Existing benchmarks often overlook intra-language variations, leaving speakers of non-standard dialects underserved. |
| Approach: | EnDive evaluates seven state-of-the-art large language models across tasks . human evaluations confirm high translation quality, with average scores of at least 6.02/7 . |
| Outcome: | EnDive evaluates state-of-the-art large language models across language understanding, reasoning, mathematics, logic tasks. |