most citedGLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models

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

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cs.CL2025

DispatchMAS: Fusing taxonomy and artificial intelligence agents for emergency medical services

Xiang Li, Huizi Yu, Wenkong Wang +17

Objective: Emergency medical dispatch (EMD) is a high-stakes process challenged by caller distress, ambiguity, and cognitive load. Large Language Models (LLMs) and Multi-Agent Syst…

cs.CL2025

HiPO: Hybrid Policy Optimization for Dynamic Reasoning in LLMs

Ken Deng, Zizheng Zhan, Wen Xiang +25

Large Language Models (LLMs) increasingly rely on Chain-of-Thought (CoT) reasoning to improve accuracy on complex tasks. However, always generating lengthy reasoning traces is inef…

cs.CL2025

MoSEs: Uncertainty-Aware AI-Generated Text Detection via Mixture of Stylistics Experts with Conditional Thresholds

Junxi Wu, Jinpeng Wang, Zheng Liu +4

The rapid advancement of large language models has intensified public concerns about the potential misuse. Therefore, it is important to build trustworthy AI-generated text detecti…

cs.CL2025

QZhou-Embedding Technical Report

Peng Yu, En Xu, Bin Chen +2

We present QZhou-Embedding, a general-purpose contextual text embedding model with exceptional text representation capabilities. Built upon the Qwen2.5-7B-Instruct foundation model…

cs.CL20254 cited

GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models

5 Team, Aohan Zeng, Xin Lv +167

We present GLM-4.5, an open-source Mixture-of-Experts (MoE) large language model with 355B total parameters and 32B activated parameters, featuring a hybrid reasoning method that s…

cs.CL2025

Beyond Templates: Dynamic Adaptation of Reasoning Demonstrations via Feasibility-Aware Exploration

Yong Wu, Weihang Pan, Ke Li +3

Large language models (LLMs) have shown remarkable reasoning capabilities, yet aligning such abilities to small language models (SLMs) remains a challenge due to distributional mis…