activity
20242026
most citedFlow Matching Meets Biology and Life Science: A Survey

2 citations · 2 across the 14 of their papers we have counts for

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7 papers · 1 filter

cs.AI2026

Evo-Harness: Context-to-Harness Skill Compilation for Self-Evolving Agents

Tianxin Wei, Zhan Shi, Minhua Lin +14

Learning from experience is critical for developing capable, self-improving large language model (LLM) agents. Existing methods typically extract knowledge from accumulated traject…

cs.AI2026

ReContext: Recursive Evidence Replay as LLM Harness for Long-Context Reasoning

Yanjun Zhao, Ruizhong Qiu, Tianxin Wei +6

Understanding and reasoning over long contexts has become a key requirement for deploying large language models (LLMs) in realistic applications. Although recent LLMs support incre…

cs.AI2026

TSAQA: Time Series Analysis Question And Answering Benchmark

Baoyu Jing, Sanhorn Chen, Lecheng Zheng +13

Time series data are integral to critical applications across domains such as finance, healthcare, transportation, and environmental science. While recent work has begun to explore…

cs.AI2026

Heterogeneous Scientific Foundation Model Collaboration

Zihao Li, Jiaru Zou, Feihao Fang +6

Agentic large language model systems have demonstrated strong capabilities. However, their reliance on language as the universal interface fundamentally limits their applicability…

cs.AI2026

MC-Search: Evaluating and Enhancing Multimodal Agentic Search with Structured Long Reasoning Chains

Xuying Ning, Dongqi Fu, Tianxin Wei +7

With the increasing demand for step-wise, cross-modal, and knowledge-grounded reasoning, multimodal large language models (MLLMs) are evolving beyond the traditional fixed retrieve…

cs.AI20261 cited

Agentic Reasoning for Large Language Models

Tianxin Wei, Ting-Wei Li, Zhining Liu +26

Reasoning is a fundamental cognitive process underlying inference, problem-solving, and decision-making. While large language models (LLMs) demonstrate strong reasoning capabilitie…