37 citations · 92 across the 15 of their papers we have counts for
15 papers
The Devil Is in the Details: Tackling Unimodal Spurious Correlations for Generalizable Multimodal Reward Models
Zichao Li, Xueru Wen, Jie Lou +5
Multimodal Reward Models (MM-RMs) are crucial for aligning Large Language Models (LLMs) with human preferences, particularly as LLMs increasingly interact with multimodal data. How…
Match, Compare, or Select? An Investigation of Large Language Models for Entity Matching
Tianshu Wang, Xiaoyang Chen, Hongyu Lin +5
Entity matching (EM) is a critical step in entity resolution (ER). Recently, entity matching based on large language models (LLMs) has shown great promise. However, current LLM-bas…
Retentive or Forgetful? Diving into the Knowledge Memorizing Mechanism of Language Models
Boxi Cao, Qiaoyu Tang, Hongyu Lin +6
Memory is one of the most essential cognitive functions serving as a repository of world knowledge and episodes of activities. In recent years, large-scale pre-trained language mod…
Influence of External Information on Large Language Models Mirrors Social Cognitive Patterns
Ning Bian, Hongyu Lin, Peilin Liu +5
Social cognitive theory explains how people learn and acquire knowledge through observing others. Recent years have witnessed the rapid development of large language models (LLMs),…
Groupwise Query Performance Prediction with BERT
Xiaoyang Chen, Ben He, Le Sun
While large-scale pre-trained language models like BERT have advanced the state-of-the-art in IR, its application in query performance prediction (QPP) is so far based on pointwise…
A Rigorous Study on Named Entity Recognition: Can Fine-tuning Pretrained Model Lead to the Promised Land?
Hongyu Lin, Yaojie Lu, Jialong Tang +4
Fine-tuning pretrained model has achieved promising performance on standard NER benchmarks. Generally, these benchmarks are blessed with strong name regularity, high mention covera…