:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Li, Yanyang, Lyu, Michael, Wang, Liwei
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Computation and Language
Online Access:	https://arxiv.org/abs/2502.15771
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Beyond Embeddings: The Promise of Visual Table in Visual Reasoning
by: Zhong, Yiwu, et al.
Published: (2024)

Parallel Test-Time Scaling for Latent Reasoning Models
by: You, Runyang, et al.
Published: (2025)

Understanding and Mitigating Spurious Signal Amplification in Test-Time Reinforcement Learning for Math Reasoning
by: Yu, Yongcan, et al.
Published: (2026)

Enhancing Temporal Modeling of Video LLMs via Time Gating
by: Hu, Zi-Yuan, et al.
Published: (2024)

Scaling over Scaling: Exploring Test-Time Scaling Plateau in Large Reasoning Models
by: Wang, Jian, et al.
Published: (2025)

Crosslingual Reasoning through Test-Time Scaling
by: Yong, Zheng-Xin, et al.
Published: (2025)

Log-Augmented Generation: Scaling Test-Time Reasoning with Reusable Computation
by: Chen, Peter Baile, et al.
Published: (2025)

Enhancing LLM Reasoning via Critique Models with Test-Time and Training-Time Supervision
by: Xi, Zhiheng, et al.
Published: (2024)

Understanding and Steering the Cognitive Behaviors of Reasoning Models at Test-Time
by: Zhang, Zhenyu, et al.
Published: (2025)

Bringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning
by: Shan, Zikang, et al.
Published: (2026)

Seek in the Dark: Reasoning via Test-Time Instance-Level Policy Gradient in Latent Space
by: Li, Hengli, et al.
Published: (2025)

Online Reasoning Calibration: Test-Time Training Enables Generalizable Conformal LLM Reasoning
by: Zhou, Cai, et al.
Published: (2026)

Amplification Effects in Test-Time Reinforcement Learning: Safety and Reasoning Vulnerabilities
by: Khattar, Vanshaj, et al.
Published: (2026)

Learning to (Learn at Test Time): RNNs with Expressive Hidden States
by: Sun, Yu, et al.
Published: (2024)

TTSR: Test-Time Self-Reflection for Continual Reasoning Improvement
by: He, Haoyang, et al.
Published: (2026)

A Survey of Test-Time Compute: From Intuitive Inference to Deliberate Reasoning
by: Ji, Yixin, et al.
Published: (2025)

Rethinking Chain-of-Thought Reasoning for Videos
by: Zhong, Yiwu, et al.
Published: (2025)

Adaptive Test-Time Reasoning via Reward-Guided Dual-Phase Search
by: Cui, Yingqian, et al.
Published: (2025)

Agent-Omni: Test-Time Multimodal Reasoning via Model Coordination for Understanding Anything
by: Lin, Huawei, et al.
Published: (2025)

Test-Time Learning for Large Language Models
by: Hu, Jinwu, et al.
Published: (2025)

TaTToo: Tool-Grounded Thinking PRM for Test-Time Scaling in Tabular Reasoning
by: Zou, Jiaru, et al.
Published: (2025)

How Numerical Precision Affects Arithmetical Reasoning Capabilities of LLMs
by: Feng, Guhao, et al.
Published: (2024)

Titans: Learning to Memorize at Test Time
by: Behrouz, Ali, et al.
Published: (2024)

Pluralistic Behavior Suite: Stress-Testing Multi-Turn Adherence to Custom Behavioral Policies
by: Varshney, Prasoon, et al.
Published: (2025)

Test-Time Scaling in Reasoning Models Is Not Effective for Knowledge-Intensive Tasks Yet
by: Zhao, James Xu, et al.
Published: (2025)

Prompting Test-Time Scaling Is A Strong LLM Reasoning Data Augmentation
by: Bsharat, Sondos Mahmoud, et al.
Published: (2025)

Dynamic Experts Search: Enhancing Reasoning in Mixture-of-Experts LLMs at Test Time
by: Han, Yixuan, et al.
Published: (2025)

Reinforcement Learning with Backtracking Feedback
by: Sel, Bilgehan, et al.
Published: (2026)

Reasoning Elicitation in Language Models via Counterfactual Feedback
by: Hüyük, Alihan, et al.
Published: (2024)

Reinforcement Learning Teachers of Test Time Scaling
by: Cetin, Edoardo, et al.
Published: (2025)

The Power of Power Law: Asymmetry Enables Compositional Reasoning
by: Wang, Zixuan, et al.
Published: (2026)

Parameter Efficient Reinforcement Learning from Human Feedback
by: Sidahmed, Hakim, et al.
Published: (2024)

Test-Time Detoxification without Training or Learning Anything
by: Saglam, Baturay, et al.
Published: (2026)

Self-Harmony: Learning to Harmonize Self-Supervision and Self-Play in Test-Time Reinforcement Learning
by: Wang, Ru, et al.
Published: (2025)

RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
by: Lee, Harrison, et al.
Published: (2023)

Learning Personalized Agents from Human Feedback
by: Liang, Kaiqu, et al.
Published: (2026)

Becoming Experienced Judges: Selective Test-Time Learning for Evaluators
by: Jwa, Seungyeon, et al.
Published: (2025)

The Surprising Effectiveness of Test-Time Training for Few-Shot Learning
by: Akyürek, Ekin, et al.
Published: (2024)

Gradient Regularization Prevents Reward Hacking in Reinforcement Learning from Human Feedback and Verifiable Rewards
by: Ackermann, Johannes, et al.
Published: (2026)

Learning to Reason Over Time: Timeline Self-Reflection for Improved Temporal Reasoning in Language Models
by: Bazaga, Adrián, et al.
Published: (2025)