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20112026
most citedEvaluating Large Language Models on Multimodal Chemistry Olympiad Exams

4 citations · 7 across the 25 of their papers we have counts for

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5 papers · 2 filters

cs.CL2025★ 4 cited

Evaluating Large Language Models on Multimodal Chemistry Olympiad Exams

Yiming Cui, Xin Yao, Yuxuan Qin +3

Multimodal scientific reasoning remains a significant challenge for large language models (LLMs), particularly in chemistry, where problem-solving relies on symbolic diagrams, mole…

cs.CL2025

InfoAgent: Advancing Autonomous Information-Seeking Agents

Gongrui Zhang, Jialiang Zhu, Ruiqi Yang +15

Building Large Language Model agents that expand their capabilities by interacting with external tools represents a new frontier in AI research and applications. In this paper, we…

cs.CL2025

From Large to Super-Tiny: End-to-End Optimization for Cost-Efficient LLMs

Jiliang Ni, Jiachen Pu, Zhongyi Yang +7

Large Language Models (LLMs) have significantly advanced artificial intelligence by optimizing traditional Natural Language Processing (NLP) workflows, facilitating their integrati…

cs.CL2025★ 1 cited

A Survey on Enhancing Causal Reasoning Ability of Large Language Models

Xin Li, Zhuo Cai, Shoujin Wang +2

Large language models (LLMs) have recently shown remarkable performance in language tasks and beyond. However, due to their limited inherent causal reasoning ability, LLMs still fa…

cs.CL2025

RAPID: Long-Context Inference with Retrieval-Augmented Speculative Decoding

Guanzheng Chen, Qilong Feng, Jinjie Ni +2

The emergence of long-context large language models (LLMs) offers a promising alternative to traditional retrieval-augmented generation (RAG) for processing extensive documents. Ho…