3 citations · 7 across the 10 of their papers we have counts for
10 papers
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…
StreamingBench: Assessing the Gap for MLLMs to Achieve Streaming Video Understanding
Junming Lin, Zheng Fang, Chi Chen +5
The rapid development of Multimodal Large Language Models (MLLMs) has expanded their capabilities from image comprehension to video understanding. However, most of these MLLMs focu…
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…
Reasoning in Conversation: Solving Subjective Tasks through Dialogue Simulation for Large Language Models
Xiaolong Wang, Yile Wang, Yuanchi Zhang +4
Large Language Models (LLMs) have achieved remarkable performance in objective tasks such as open-domain question answering and mathematical reasoning, which can often be solved th…
Enhancing Multilingual Capabilities of Large Language Models through Self-Distillation from Resource-Rich Languages
Yuanchi Zhang, Yile Wang, Zijun Liu +5
While large language models (LLMs) have been pre-trained on multilingual corpora, their performance still lags behind in most languages compared to a few resource-rich languages. O…
CODIS: Benchmarking Context-Dependent Visual Comprehension for Multimodal Large Language Models
Fuwen Luo, Chi Chen, Zihao Wan +11
Multimodal large language models (MLLMs) have demonstrated promising results in a variety of tasks that combine vision and language. As these models become more integral to researc…
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…
Model Composition for Multimodal Large Language Models
Chi Chen, Yiyang Du, Zheng Fang +8
Recent developments in Multimodal Large Language Models (MLLMs) have shown rapid progress, moving towards the goal of creating versatile MLLMs that understand inputs from various m…
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…
Self-Knowledge Guided Retrieval Augmentation for Large Language Models
Yile Wang, Peng Li, Maosong Sun +1
Large language models (LLMs) have shown superior performance without task-specific fine-tuning. Despite the success, the knowledge stored in the parameters of LLMs could still be i…