Saved in:
| Main Authors: | Han, Tianyang, Shi, Hengyu, Hu, Junjie, Yang, Xu, Wang, Zhiling, Su, Junhao |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2605.03862 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Rethinking Local Learning: A Cheaper and Faster Recipe for LLM Post-Training
by: Shi, Hengyu, et al.
Published: (2026)
by: Shi, Hengyu, et al.
Published: (2026)
Planner and Executor: Collaboration between Discrete Diffusion And Autoregressive Models in Reasoning
by: Berrayana, Lina, et al.
Published: (2025)
by: Berrayana, Lina, et al.
Published: (2025)
Beyond Words and Pixels: A Benchmark for Implicit World Knowledge Reasoning in Generative Models
by: Han, Tianyang, et al.
Published: (2025)
by: Han, Tianyang, et al.
Published: (2025)
Failure Makes the Agent Stronger: Enhancing Accuracy through Structured Reflection for Reliable Tool Interactions
by: Su, Junhao, et al.
Published: (2025)
by: Su, Junhao, et al.
Published: (2025)
Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMs
by: Wen, Xumeng, et al.
Published: (2025)
by: Wen, Xumeng, et al.
Published: (2025)
Large Language Models as Code Executors: An Exploratory Study
by: Lyu, Chenyang, et al.
Published: (2024)
by: Lyu, Chenyang, et al.
Published: (2024)
Your Models Have Thought Enough: Training Large Reasoning Models to Stop Overthinking
by: Han, Jinyi, et al.
Published: (2025)
by: Han, Jinyi, et al.
Published: (2025)
Memorizing is Not Enough: Deep Knowledge Injection Through Reasoning
by: Xu, Ruoxi, et al.
Published: (2025)
by: Xu, Ruoxi, et al.
Published: (2025)
ToM-LM: Delegating Theory of Mind Reasoning to External Symbolic Executors in Large Language Models
by: Tang, Weizhi, et al.
Published: (2024)
by: Tang, Weizhi, et al.
Published: (2024)
Reward Is Enough: LLMs Are In-Context Reinforcement Learners
by: Song, Kefan, et al.
Published: (2025)
by: Song, Kefan, et al.
Published: (2025)
Self-Rewarding Rubric-Based Reinforcement Learning for Open-Ended Reasoning
by: Ye, Zhiling, et al.
Published: (2025)
by: Ye, Zhiling, et al.
Published: (2025)
DIP: Dynamic In-Context Planner For Diffusion Language Models
by: Li, Yang, et al.
Published: (2026)
by: Li, Yang, et al.
Published: (2026)
Fitting Is Not Enough: Smoothness in Extremely Quantized LLMs
by: Xu, Yuzhuang, et al.
Published: (2026)
by: Xu, Yuzhuang, et al.
Published: (2026)
On Designing Effective RL Reward at Training Time for LLM Reasoning
by: Gao, Jiaxuan, et al.
Published: (2024)
by: Gao, Jiaxuan, et al.
Published: (2024)
RELOOP: Recursive Retrieval with Multi-Hop Reasoner and Planners for Heterogeneous QA
by: Yang, Ruiyi, et al.
Published: (2025)
by: Yang, Ruiyi, et al.
Published: (2025)
Single Ground Truth Is Not Enough: Adding Flexibility to Aspect-Based Sentiment Analysis Evaluation
by: Yang, Soyoung, et al.
Published: (2024)
by: Yang, Soyoung, et al.
Published: (2024)
Agentic Reward Modeling: Integrating Human Preferences with Verifiable Correctness Signals for Reliable Reward Systems
by: Peng, Hao, et al.
Published: (2025)
by: Peng, Hao, et al.
Published: (2025)
Reasoning Isn't Enough: Examining Truth-Bias and Sycophancy in LLMs
by: Barkett, Emilio, et al.
Published: (2025)
by: Barkett, Emilio, et al.
Published: (2025)
OmniEVA: Embodied Versatile Planner via Task-Adaptive 3D-Grounded and Embodiment-aware Reasoning
by: Liu, Yuecheng, et al.
Published: (2025)
by: Liu, Yuecheng, et al.
Published: (2025)
The Art of Efficient Reasoning: Data, Reward, and Optimization
by: Wu, Taiqiang, et al.
Published: (2026)
by: Wu, Taiqiang, et al.
Published: (2026)
AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward Modeling
by: Liu, Zihan, et al.
Published: (2024)
by: Liu, Zihan, et al.
Published: (2024)
ReasonGRM: Enhancing Generative Reward Models through Large Reasoning Models
by: Chen, Bin, et al.
Published: (2025)
by: Chen, Bin, et al.
Published: (2025)
Towards Safe Reasoning in Large Reasoning Models via Corrective Intervention
by: Zhang, Yichi, et al.
Published: (2025)
by: Zhang, Yichi, et al.
Published: (2025)
When Is Enough Not Enough? Illusory Completion in Search Agents
by: Ko, Dayoon, et al.
Published: (2026)
by: Ko, Dayoon, et al.
Published: (2026)
StoryAlign: Evaluating and Training Reward Models for Story Generation
by: Xia, Haotian, et al.
Published: (2026)
by: Xia, Haotian, et al.
Published: (2026)
Correct, Concise and Complete: Multi-stage Training For Adaptive Reasoning
by: Rakotonirina, Nathanaël Carraz, et al.
Published: (2026)
by: Rakotonirina, Nathanaël Carraz, et al.
Published: (2026)
Beyond Binary Rewards: Training LMs to Reason About Their Uncertainty
by: Damani, Mehul, et al.
Published: (2025)
by: Damani, Mehul, et al.
Published: (2025)
From Faithfulness to Correctness: Generative Reward Models that Think Critically
by: Ma, Qiyao, et al.
Published: (2025)
by: Ma, Qiyao, et al.
Published: (2025)
ETR: Entropy Trend Reward for Efficient Chain-of-Thought Reasoning
by: Xiong, Xuan, et al.
Published: (2026)
by: Xiong, Xuan, et al.
Published: (2026)
SeedPrints: Fingerprints Can Even Tell Which Seed Your Large Language Model Was Trained From
by: Tong, Yao, et al.
Published: (2025)
by: Tong, Yao, et al.
Published: (2025)
Know Your Needs Better: Towards Structured Understanding of Marketer Demands with Analogical Reasoning Augmented LLMs
by: Wang, Junjie, et al.
Published: (2024)
by: Wang, Junjie, et al.
Published: (2024)
Adaptive Interviewing for Persona Simulation in LLMs: Evidence-Grounded Reasoning Improves Decision Alignment
by: Su, Ruoxi, et al.
Published: (2026)
by: Su, Ruoxi, et al.
Published: (2026)
CSRP: Chain-of-Thought Reasoning for Chinese Text Correction via Reinforcement Learning with Efficiency-Aware Rewards
by: Tian, Wei, et al.
Published: (2026)
by: Tian, Wei, et al.
Published: (2026)
Retrieval is Not Enough: Enhancing RAG Reasoning through Test-Time Critique and Optimization
by: Wei, Jiaqi, et al.
Published: (2025)
by: Wei, Jiaqi, et al.
Published: (2025)
An Efficient and Precise Training Data Construction Framework for Process-supervised Reward Model in Mathematical Reasoning
by: Sun, Wei, et al.
Published: (2025)
by: Sun, Wei, et al.
Published: (2025)
Retrieval-Augmented Self-Taught Reasoning Model with Adaptive Chain-of-Thought for ASR Named Entity Correction
by: An, Junjie, et al.
Published: (2026)
by: An, Junjie, et al.
Published: (2026)
Reward-Guided Speculative Decoding for Efficient LLM Reasoning
by: Liao, Baohao, et al.
Published: (2025)
by: Liao, Baohao, et al.
Published: (2025)
Unlocking Multimodal Mathematical Reasoning via Process Reward Model
by: Luo, Ruilin, et al.
Published: (2025)
by: Luo, Ruilin, et al.
Published: (2025)
MedCritical: Enhancing Medical Reasoning in Small Language Models via Self-Collaborative Correction
by: Su, Xinchun, et al.
Published: (2025)
by: Su, Xinchun, et al.
Published: (2025)
History-Guided Iterative Visual Reasoning with Self-Correction
by: Yang, Xinglong, et al.
Published: (2026)
by: Yang, Xinglong, et al.
Published: (2026)
Similar Items
-
Rethinking Local Learning: A Cheaper and Faster Recipe for LLM Post-Training
by: Shi, Hengyu, et al.
Published: (2026) -
Planner and Executor: Collaboration between Discrete Diffusion And Autoregressive Models in Reasoning
by: Berrayana, Lina, et al.
Published: (2025) -
Beyond Words and Pixels: A Benchmark for Implicit World Knowledge Reasoning in Generative Models
by: Han, Tianyang, et al.
Published: (2025) -
Failure Makes the Agent Stronger: Enhancing Accuracy through Structured Reflection for Reliable Tool Interactions
by: Su, Junhao, et al.
Published: (2025) -
Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMs
by: Wen, Xumeng, et al.
Published: (2025)