activity
20242026
collaborators
Showing cs.CLShow all

6 papers · 1 filter

cs.CL2026

OMGEval: An Open Multilingual Generative Evaluation Benchmark for Large Language Models

Yang Liu, Meng Xu, Shuo Wang +7

Modern large language models (LLMs) should generally benefit individuals from various cultural backgrounds around the world. However, most recent advanced generative evaluation ben…

cs.CL2026

Browse and Concentrate: Comprehending Multimodal Content via prior-LLM Context Fusion

Ziyue Wang, Chi Chen, Yiqi Zhu +7

With the bloom of Large Language Models (LLMs), Multimodal Large Language Models (MLLMs) that incorporate LLMs with pre-trained vision models have recently demonstrated impressive…

cs.CL2025

AdaMMS: Model Merging for Heterogeneous Multimodal Large Language Models with Unsupervised Coefficient Optimization

Yiyang Du, Xiaochen Wang, Chi Chen +9

Recently, model merging methods have demonstrated powerful strengths in combining abilities on various tasks from multiple Large Language Models (LLMs). While previous model mergin…

cs.CL2025

StableToolBench: Towards Stable Large-Scale Benchmarking on Tool Learning of Large Language Models

Zhicheng Guo, Sijie Cheng, Hao Wang +6

Large Language Models (LLMs) have witnessed remarkable advancements in recent years, prompting the exploration of tool learning, which integrates LLMs with external tools to addres…

cs.CL2024

PANDA: Preference Adaptation for Enhancing Domain-Specific Abilities of LLMs

An Liu, Zonghan Yang, Zhenhe Zhang +6

While Large language models (LLMs) have demonstrated considerable capabilities across various natural language tasks, they often fall short of the performance achieved by domain-sp…

cs.CL2024

Enabling Weak LLMs to Judge Response Reliability via Meta Ranking

Zijun Liu, Boqun Kou, Peng Li +4

Despite the strong performance of large language models (LLMs) across a wide range of tasks, they still have reliability issues. Previous studies indicate that strong LLMs like GPT…