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20242026
most citedQwen3 Technical Report

111 citations · 236 across the 13 of their papers we have counts for

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Showing 2025 · cs.CLShow all

6 papers · 2 filters

cs.CL2025

InvestAlign: Overcoming Data Scarcity in Aligning Large Language Models with Investor Decision-Making Processes under Herd Behavior

Huisheng Wang, Zhuoshi Pan, Hangjing Zhang +3

Aligning Large Language Models (LLMs) with investor decision-making processes under herd behavior is a critical challenge in behavioral finance, which grapples with a fundamental l…

cs.CL2025

CoLD: Counterfactually-Guided Length Debiasing for Process Reward Models in Mathematical Reasoning

Congmin Zheng, Jiachen Zhu, Jianghao Lin +6

Process Reward Models (PRMs) play a central role in evaluating and guiding multi-step reasoning in large language models (LLMs), especially for mathematical problem solving. Howeve…

cs.CL2025★ 111 cited

Qwen3 Technical Report

An Yang, Anfeng Li, Baosong Yang +57

In this work, we present Qwen3, the latest version of the Qwen model family. Qwen3 comprises a series of large language models (LLMs) designed to advance performance, efficiency, a…

cs.CL2025★ 2 cited

START: Self-taught Reasoner with Tools

Chengpeng Li, Mingfeng Xue, Zhenru Zhang +7

Large reasoning models (LRMs) like OpenAI-o1 and DeepSeek-R1 have demonstrated remarkable capabilities in complex reasoning tasks through the utilization of long Chain-of-thought (…

cs.CL2025★ 107 cited

Qwen2.5 Technical Report

Qwen, :, An Yang +41

In this report, we introduce Qwen2.5, a comprehensive series of large language models (LLMs) designed to meet diverse needs. Compared to previous iterations, Qwen 2.5 has been sign…

cs.CL2025

The Lessons of Developing Process Reward Models in Mathematical Reasoning

Zhenru Zhang, Chujie Zheng, Yangzhen Wu +6

Process Reward Models (PRMs) emerge as a promising approach for process supervision in mathematical reasoning of Large Language Models (LLMs), which aim to identify and mitigate in…