6 papers · 1 filter
Learning What Matters: Dynamic Dimension Selection and Aggregation for Interpretable Vision-Language Reward Modeling
Qiyuan Chen, Hongsen Huang, Jiahe Chen +6
Vision-language reward modeling faces a dilemma: generative approaches are interpretable but slow, while discriminative ones are efficient but act as opaque "black boxes." To bridg…
CC-GSEO-Bench: A Content-Centric Benchmark for Measuring Source Influence in Generative Search Engines
Qiyuan Chen, Jiahe Chen, Hongsen Huang +7
Generative Search Engines (GSEs) synthesize conversational answers from multiple sources, weakening the long-standing link between search ranking and digital visibility. This shift…
Icon: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation
Qiyuan Chen, Hongsen Huang, Qian Shao +6
Large Language Models (LLMs) require high quality preference datasets to align with human preferences. However, conventional methods for constructing such datasets face significant…
Small Models are LLM Knowledge Triggers on Medical Tabular Prediction
Jiahuan Yan, Jintai Chen, Chaowen Hu +4
Recent development in large language models (LLMs) has demonstrated impressive domain proficiency on unstructured textual or multi-modal tasks. However, despite with intrinsic worl…
Unraveling Babel: Exploring Multilingual Activation Patterns of LLMs and Their Applications
Weize Liu, Yinlong Xu, Hongxia Xu +3
Recently, large language models (LLMs) have achieved tremendous breakthroughs in the field of NLP, but still lack understanding of their internal neuron activities when processing…
ClinicalAgent: Clinical Trial Multi-Agent System with Large Language Model-based Reasoning
Ling Yue, Sixue Xing, Jintai Chen +1
Large Language Models (LLMs) and multi-agent systems have shown impressive capabilities in natural language tasks but face challenges in clinical trial applications, primarily due…