244 citations · 336 across the 24 of their papers we have counts for
6 papers · 1 filter
Keys to Robust Edits: from Theoretical Insights to Practical Advances
Jianhao Yan, Futing Wang, Yun Luo +2
Large language models (LLMs) struggle with maintaining accurate knowledge due to conflicting/outdated parametric memories. While locate-and-edit methods address this, their relianc…
LexMatcher: Dictionary-centric Data Collection for LLM-based Machine Translation
Yongjing Yin, Jiali Zeng, Yafu Li +2
The fine-tuning of open-source large language models (LLMs) for machine translation has recently received considerable attention, marking a shift towards data-centric research from…
Spotting AI's Touch: Identifying LLM-Paraphrased Spans in Text
Yafu Li, Zhilin Wang, Leyang Cui +3
AI-generated text detection has attracted increasing attention as powerful language models approach human-level generation. Limited work is devoted to detecting (partially) AI-para…
What Have We Achieved on Non-autoregressive Translation?
Yafu Li, Huajian Zhang, Jianhao Yan +2
Recent advances have made non-autoregressive (NAT) translation comparable to autoregressive methods (AT). However, their evaluation using BLEU has been shown to weakly correlate wi…
MCRanker: Generating Diverse Criteria On-the-Fly to Improve Point-wise LLM Rankers
Fang Guo, Wenyu Li, Honglei Zhuang +5
The most recent pointwise Large Language Model (LLM) rankers have achieved remarkable ranking results. However, these rankers are hindered by two major drawbacks: (1) they fail to…
Potential and Challenges of Model Editing for Social Debiasing
Jianhao Yan, Futing Wang, Yafu Li +1
Large language models (LLMs) trained on vast corpora suffer from inevitable stereotype biases. Mitigating these biases with fine-tuning could be both costly and data-hungry. Model…