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20232026
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cs.CL2026

Learning from Medical Entity Trees: An Entity-Centric Medical Data Engineering Framework for MLLMs

Jianghang Lin, Haihua Yang, Deli Yu +6

Multimodal Large Language Models (MLLMs) have shown transformative potential in medical applications, yet their performance is hindered by conventional data curation strategies tha…

cs.CL2026

Optimizing RAG Rerankers with LLM Feedback via Reinforcement Learning

Yuhang Wu, Xiangqing Shen, Fanfan Wang +4

Rerankers play a pivotal role in refining retrieval results for Retrieval-Augmented Generation. However, current reranking models are typically optimized on static human annotated…

cs.CL2026

Characterising Toxicity in Generative Large Language Models

Zhiyao Zhang, Yazan Mash'Al, Yuhan Wu

In recent years, the advent of the attention mechanism has significantly advanced the field of natural language processing (NLP), revolutionizing text processing and text generatio…

cs.CL2025

Training-Free Multimodal Large Language Model Orchestration

Tianyu Xie, Yuexiao Ma, Yuhang Wu +5

Building interactive omni-modal assistants often relies on end-to-end multimodal alignment to fuse heterogeneous modalities, which incurs substantial data and compute costs and lim…

cs.CL2023

RoleLLM: Benchmarking, Eliciting, and Enhancing Role-Playing Abilities of Large Language Models

Zekun Moore Wang, Zhongyuan Peng, Haoran Que +14

The advent of Large Language Models (LLMs) has paved the way for complex tasks such as role-playing, which enhances user interactions by enabling models to imitate various characte…