13 citations · 85 across the 35 of their papers we have counts for
15 papers · 1 filter
CARE: Causally-Aligned Reasoning Exploration for Medical Large Language Models
Yucheng Zhou, Peng Luo, Qianning Wang +2
Large Language Models (LLMs) have shown strong potential for medical reasoning, yet the scarcity and cost of expert-annotated data constrain their progress. While reinforcement lea…
Speed Always Wins: A Survey on Efficient Architectures for Large Language Models
Weigao Sun, Jiaxi Hu, Yucheng Zhou +12
Large Language Models (LLMs) have delivered impressive results in language understanding, generation, reasoning, and pushes the ability boundary of multimodal models. Transformer m…
MAM: Modular Multi-Agent Framework for Multi-Modal Medical Diagnosis via Role-Specialized Collaboration
Yucheng Zhou, Lingran Song, Jianbing Shen
Recent advancements in medical Large Language Models (LLMs) have showcased their powerful reasoning and diagnostic capabilities. Despite their success, current unified multimodal m…
Safety Alignment via Constrained Knowledge Unlearning
Zesheng Shi, Yucheng Zhou, Jing Li
Despite significant progress in safety alignment, large language models (LLMs) remain susceptible to jailbreak attacks. Existing defense mechanisms have not fully deleted harmful k…
Beyond Empathy: Integrating Diagnostic and Therapeutic Reasoning with Large Language Models for Mental Health Counseling
He Hu, Yucheng Zhou, Juzheng Si +6
Large language models (LLMs) hold significant potential for mental health support, capable of generating empathetic responses and simulating therapeutic conversations. However, exi…
EmoBench-M: Benchmarking Emotional Intelligence for Multimodal Large Language Models
He Hu, Lianzhong You, Hongbo Xu +7
With the integration of multimodal large language models (MLLMs) into robotic systems and AI applications, embedding emotional intelligence (EI) capabilities is essential for enabl…
Improving Medical Large Vision-Language Models with Abnormal-Aware Feedback
Yucheng Zhou, Lingran Song, Jianbing Shen
Existing Medical Large Vision-Language Models (Med-LVLMs), encapsulating extensive medical knowledge, demonstrate excellent capabilities in understanding medical images. However, t…
Impromptu Cybercrime Euphemism Detection
Xiang Li, Yucheng Zhou, Laiping Zhao +2
Detecting euphemisms is essential for content security on various social media platforms, but existing methods designed for detecting euphemisms are ineffective in impromptu euphem…
Rethinking Visual Dependency in Long-Context Reasoning for Large Vision-Language Models
Yucheng Zhou, Zhi Rao, Jun Wan +1
Large Vision-Language Models (LVLMs) excel in cross-model tasks but experience performance declines in long-context reasoning due to overreliance on textual information and reduced…
Thread of Thought Unraveling Chaotic Contexts
Yucheng Zhou, Xiubo Geng, Tao Shen +4
Large Language Models (LLMs) have ushered in a transformative era in the field of natural language processing, excelling in tasks related to text comprehension and generation. Neve…
Topic-Selective Graph Network for Topic-Focused Summarization
Shi Zesheng, Zhou Yucheng
Due to the success of the pre-trained language model (PLM), existing PLM-based summarization models show their powerful generative capability. However, these models are trained on…
Unsupervised Knowledge Graph Construction and Event-centric Knowledge Infusion for Scientific NLI
Chenglin Wang, Yucheng Zhou, Guodong Long +2
With the advance of natural language inference (NLI), a rising demand for NLI is to handle scientific texts. Existing methods depend on pre-trained models (PTM) which lack domain-s…
Disentangled and Robust Representation Learning for Bragging Classification in Social Media
Xiang Li, Yucheng Zhou
Researching bragging behavior on social media arouses interest of computational (socio) linguists. However, existing bragging classification datasets suffer from a serious data imb…
ClarET: Pre-training a Correlation-Aware Context-To-Event Transformer for Event-Centric Generation and Classification
Yucheng Zhou, Tao Shen, Xiubo Geng +2
Generating new events given context with correlated ones plays a crucial role in many event-centric reasoning tasks. Existing works either limit their scope to specific scenarios o…
EventBERT: A Pre-Trained Model for Event Correlation Reasoning
Yucheng Zhou, Xiubo Geng, Tao Shen +2
Event correlation reasoning infers whether a natural language paragraph containing multiple events conforms to human common sense. For example, "Andrew was very drowsy, so he took…