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20242026
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cs.CL2025

MULTI: Multimodal Understanding Leaderboard with Text and Images

Zichen Zhu, Yang Xu, Lu Chen +11

The rapid development of multimodal large language models (MLLMs) raises the question of how they compare to human performance. While existing datasets often feature synthetic or o…

cs.CL2025

Enhancing LLM Reliability via Explicit Knowledge Boundary Modeling

Hang Zheng, Hongshen Xu, Yuncong Liu +3

Large language models (LLMs) are prone to hallucination stemming from misaligned self-awareness, particularly when processing queries exceeding their knowledge boundaries. While ex…

cs.CL2025

Compressing KV Cache for Long-Context LLM Inference with Inter-Layer Attention Similarity

Da Ma, Lu Chen, Situo Zhang +8

The rapid expansion of context window sizes in Large Language Models~(LLMs) has enabled them to tackle increasingly complex tasks involving lengthy documents. However, this progres…

cs.CL2025

Developing ChemDFM as a large language foundation model for chemistry

Zihan Zhao, Da Ma, Lu Chen +11

Artificial intelligence (AI) has played an increasingly important role in chemical research. However, most models currently used in chemistry are specialist models that require tra…

cs.CL2025

NeuSym-RAG: Hybrid Neural Symbolic Retrieval with Multiview Structuring for PDF Question Answering

Ruisheng Cao, Hanchong Zhang, Tiancheng Huang +8

The increasing number of academic papers poses significant challenges for researchers to efficiently acquire key details. While retrieval augmented generation (RAG) shows great pro…

cs.CL2025

Reducing Tool Hallucination via Reliability Alignment

Hongshen Xu, Zichen Zhu, Lei Pan +6

Large Language Models (LLMs) have expanded their capabilities beyond language generation to interact with external tools, enabling automation and real-world applications. However,…