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20232026
most citedRethinking the Roles of Large Language Models in Chinese Grammatical Error Correction

4 citations · 20 across the 35 of their papers we have counts for

collaborators

38 papers

cs.SE2026

Tool Retrievers Are Underestimated: Annotation Expansion Reveals True Capability

Yanyu Zhu, Chenheng Zhang, Shaoshen Chen +8

In open-world scenarios with massive and evolving tool repositories, tool-augmented large language models rely on a retriever to surface relevant tools for a given query. Because s…

cs.AI2026

From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI

Yongheng Zhang, Ziang Liu, Jiaxuan Zhu +17

Large Language Models (LLMs) are undergoing a fundamental transformation from conversational generators into integrated AI systems capable of reasoning, action, memory, and self-im…

cs.AI2026

Cognitive Mismatch in Multimodal Large Language Models for Discrete Symbol Understanding

Yinghui Li, Jiayi Kuang, Peng Xing +11

Multimodal large language models (MLLMs) perform strongly on natural images, yet their ability to understand discrete visual symbols remains unclear. We present a multi-domain benc…

cs.SE2026

EvoConfig: Self-Evolving Multi-Agent Systems for Efficient Autonomous Environment Configuration

Xinshuai Guo, Jiayi Kuang, Linyue Pan +6

A reliable executable environment is the foundation for ensuring that large language models solve software engineering tasks. Due to the complex and tedious construction process, l…

cs.CV2026

TangramPuzzle: Evaluating Multimodal Large Language Models with Compositional Spatial Reasoning

Daixian Liu, Jiayi Kuang, Yinghui Li +8

Multimodal Large Language Models (MLLMs) have achieved remarkable progress in visual recognition and semantic understanding, yet precise compositional spatial reasoning under geome…

cs.CL2025

AdmTree: Compressing Lengthy Context with Adaptive Semantic Trees

Yangning Li, Shaoshen Chen, Yinghui Li +5

The quadratic complexity of self-attention constrains Large Language Models (LLMs) in processing long contexts, a capability essential for many advanced applications. Context compr…