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20242026
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cs.AI2026

Momentum for Reasoning: Dense Intrinsic Signals in Policy Optimization

Hao Chen, Zhanming Shen, Liyao Li +8

Reinforcement learning with verifiable rewards (RLVR) has emerged as a powerful paradigm for eliciting long-chain reasoning in large language models. However, existing methods base…

cs.AI2026

Stop Unnecessary Reflection: Training LRMs for Efficient Reasoning with Adaptive Reflection and Length Coordinated Penalty

Zewei Yu, Lirong Gao, Yuke Zhu +4

Large Reasoning Models (LRMs) have demonstrated remarkable performance on complex reasoning tasks by employing test-time scaling. However, they often generate over-long chains-of-t…

cs.AI2026

A Syllogistic Probe: Tracing the Evolution of Logic Reasoning in Large Language Models

Zhengqing Zang, Yuqi Ding, Yanmei Gu +5

Human logic has gradually shifted from intuition-driven inference to rigorous formal systems. Motivated by recent advances in large language models (LLMs), we explore whether LLMs…

cs.AI2025

CrowdAgent: Multi-Agent Managed Multi-Source Annotation System

Maosheng Qin, Renyu Zhu, Mingxuan Xia +8

High-quality annotated data is a cornerstone of modern Natural Language Processing (NLP). While recent methods begin to leverage diverse annotation sources-including Large Language…

cs.AI2025

Toward Real-World Table Agents: Capabilities, Workflows, and Design Principles for LLM-based Table Intelligence

Jiaming Tian, Liyao Li, Wentao Ye +6

Tables are fundamental in domains such as finance, healthcare, and public administration, yet real-world table tasks often involve noise, structural heterogeneity, and semantic com…