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cs.AI2026

LISA: Linear-Indexed Sparse Attention for Efficient Long-Context Reasoning

Yu Zhao, Zekun Zhang, Fan Jiang +6

Recent advances in long chain-of-thought reasoning models such as DeepSeek-R1 have led to increasingly longer inference context lengths under the test-time scaling paradigm. Howeve…

cs.AI2026

ComplexMCP: Evaluation of LLM Agents in Dynamic, Interdependent, and Large-Scale Tool Sandbox

Yuanyang Li, Xue Yang, Longyue Wang +2

Current LLM agents are proficient at calling isolated APIs but struggle with the "last mile" of commercial software automation. In real-world scenarios, tools are not independent;…

cs.AI2026

From Insight to Action: A Novel Framework for Interpretability-Guided Data Selection in Large Language Models

Ling Shi, Xinwei Wu, Xiaohu Zhao +7

While mechanistic interpretability tools like Sparse Autoencoders (SAEs) can uncover meaningful features within Large Language Models (LLMs), a critical gap remains in transforming…

cs.AI2026

Difficulty-Estimated Policy Optimization

Yu Zhao, Fan Jiang, Tianle Liu +4

Recent advancements in Large Reasoning Models (LRMs), exemplified by DeepSeek-R1, have underscored the potential of scaling inference-time compute through Group Relative Policy Opt…

cs.AI2026

A State-Transition Framework for Efficient LLM Reasoning

Liang Zhang, Yu Zhao, Longyue Wang +4

While Long Chain-of-Thought (CoT) reasoning significantly improves Large Language Models (LLMs) performance on complex reasoning tasks, the substantial computational and memory cos…

cs.AI2025

HSCodeComp: A Realistic and Expert-level Benchmark for Deep Search Agents in Hierarchical Rule Application

Yiqian Yang, Tian Lan, Qianghuai Jia +6

Effective deep search agents must not only access open-domain and domain-specific knowledge but also apply complex rules-such as legal clauses, medical manuals and tariff rules. Th…