5 citations · 6 across the 4 of their papers we have counts for
6 papers · 1 filter
Exploring Task Performance with Interpretable Models via Sparse Auto-Encoders
Shun Wang, Tyler Loakman, Youbo Lei +5
Large Language Models (LLMs) are traditionally viewed as black-box algorithms, therefore reducing trustworthiness and obscuring potential approaches to increasing performance on do…
EvolvTrip: Enhancing Literary Character Understanding with Temporal Theory-of-Mind Graphs
Bohao Yang, Hainiu Xu, Jinhua Du +3
A compelling portrayal of characters is essential to the success of narrative writing. For readers, appreciating a character's traits requires the ability to infer their evolving b…
DRE: An Effective Dual-Refined Method for Integrating Small and Large Language Models in Open-Domain Dialogue Evaluation
Kun Zhao, Bohao Yang, Chen Tang +4
Large Language Models (LLMs) excel at many tasks but struggle with ambiguous scenarios where multiple valid responses exist, often yielding unreliable results. Conversely, Small La…
Does Table Source Matter? Benchmarking and Improving Multimodal Scientific Table Understanding and Reasoning
Bohao Yang, Yingji Zhang, Dong Liu +2
Recent large language models (LLMs) have advanced table understanding capabilities but rely on converting tables into text sequences. While multimodal large language models (MLLMs)…
GRAPHMOE: Amplifying Cognitive Depth of Mixture-of-Experts Network via Introducing Self-Rethinking Mechanism
Bo Lv, Chen Tang, Zifan Zheng +8
Traditional Mixture-of-Experts (MoE) networks benefit from utilizing multiple smaller expert models as opposed to a single large network. However, these experts typically operate i…
HERB: Measuring Hierarchical Regional Bias in Pre-trained Language Models
Yizhi Li, Ge Zhang, Bohao Yang +4
Fairness has become a trending topic in natural language processing (NLP), which addresses biases targeting certain social groups such as genders and religions. However, regional b…