4 papers
ROSA-Tuning: Enhancing Long-Context Modeling via Suffix Matching
Yunao Zheng, Xiaojie Wang, Lei Ren +1
Long-context capability and computational efficiency are among the central challenges facing today's large language models. Existing efficient attention methods reduce computationa…
SMAR: Soft Modality-Aware Routing Strategy for MoE-based Multimodal Large Language Models Preserving Language Capabilities
Guoyang Xia, Yifeng Ding, Fengfa Li +4
Mixture of Experts (MoE) architectures have become a key approach for scaling large language models, with growing interest in extending them to multimodal tasks. Existing methods t…
Evaluating MLLMs with Multimodal Multi-image Reasoning Benchmark
Ziming Cheng, Binrui Xu, Lisheng Gong +14
With enhanced capabilities and widespread applications, Multimodal Large Language Models (MLLMs) are increasingly required to process and reason over multiple images simultaneously…
Collab-Overcooked: Benchmarking and Evaluating Large Language Models as Collaborative Agents
Haochen Sun, Shuwen Zhang, Lujie Niu +6
Large Language Models (LLMs) based agent systems have made great strides in real-world applications beyond traditional NLP tasks. This paper proposes a new LLM-based Multi-Agent Sy…