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20222026
most citedTowards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models

18 citations · 83 across the 18 of their papers we have counts for

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5 papers · 1 filter

cs.LG2026

VETTA: Coordinating Turn- and Token-Level Credit Assignment for Multi-Turn LLM Agents

Jiaju Chen, Min Yang, Jinghua Piao +4

Multi-turn LLM agents often receive sparse task feedback across several interactions, while generating each response token by token. This creates two related credit-assignment ques…

cs.AI2026

From Scoring to Acting: Outcome-Verified Comparative Self-Distillation for LLM Agents

Xu Xia, Jinghua Piao, Min Yang +3

Recent work on LLM agents is shifting from external capability elicitation to capability internalization, enabling agents to retain useful skills without retrieval at inference tim…

cs.CL2026

Ring-Zero: Scaling Zero RL to a Trillion Parameters for Emergent Reasoning

Xinyu Tang, Qianggang Cao, Yurou Liu +13

Reinforcement learning with verifiable rewards without human-annotated data, often referred to as zero RL, has emerged as a powerful paradigm for eliciting chain-of-thought reasoni…

cs.AI2026

SkillMaster: Toward Autonomous Skill Mastery in LLM Agents

Min Yang, Jinghua Piao, Xu Xia +4

Skills provide an effective mechanism for improving LLM agents on complex tasks, yet in existing agent frameworks, their creation, refinement, and selection are typically governed…

cs.IR2026

Enhancing Local Life Service Recommendation with Agentic Reasoning in Large Language Model

Shiteng Cao, Xiaochong Lan, Yuwei Du +4

Local life service recommendation is distinct from general recommendation scenarios due to its strong living need-driven nature. Fundamentally, accurately identifying a user's imme…