Imagen de Portada

VerifierQ: Enhancing LLM Test Time Compute with Q-Learning-based Verifiers

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Qi, Jianing, Tang, Hao, Zhu, Zhigang
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning Computation and Language
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Q-NL Verifier: Leveraging Synthetic Data for Robust Knowledge Graph Question Answering
por: Schwabe, Tim, et al.
Publicado: (2025)

ATLAS: Adaptive Test-Time Latent Steering with External Verifiers for Enhancing LLMs Reasoning
por: Nguyen, Tuc, et al.
Publicado: (2026)

Policy Gradient Guidance Enables Test Time Control
por: Qi, Jianing, et al.
Publicado: (2025)

Verifying the Verifiers: Unveiling Pitfalls and Potentials in Fact Verifiers
por: Seo, Wooseok, et al.
Publicado: (2025)

AutoPyVerifier: Learning Compact Executable Verifiers for Large Language Model Outputs
por: Pezeshkpour, Pouya, et al.
Publicado: (2026)

BEATS: Optimizing LLM Mathematical Capabilities with BackVerify and Adaptive Disambiguate based Efficient Tree Search
por: Sun, Linzhuang, et al.
Publicado: (2024)

TrimR: Verifier-based Training-Free Thinking Compression for Efficient Test-Time Scaling
por: Lin, Weizhe, et al.
Publicado: (2025)

SCI-Verifier: Scientific Verifier with Thinking
por: Zheng, Shenghe, et al.
Publicado: (2025)

Towards High Data Efficiency in Reinforcement Learning with Verifiable Reward
por: Tang, Xinyu, et al.
Publicado: (2025)

Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning
por: Setlur, Amrith, et al.
Publicado: (2024)

Low-probability Tokens Sustain Exploration in Reinforcement Learning with Verifiable Reward
por: Huang, Guanhua, et al.
Publicado: (2025)

From Accuracy to Robustness: A Study of Rule- and Model-based Verifiers in Mathematical Reasoning
por: Huang, Yuzhen, et al.
Publicado: (2025)

The Alignment Auditor: A Bayesian Framework for Verifying and Refining LLM Objectives
por: Bou, Matthieu, et al.
Publicado: (2025)

Alternating Reinforcement Learning for Rubric-Based Reward Modeling in Non-Verifiable LLM Post-Training
por: Xu, Ran, et al.
Publicado: (2026)

Silence the Judge: Reinforcement Learning with Self-Verifier via Latent Geometric Clustering
por: Zhang, Nonghai, et al.
Publicado: (2026)

From Reasoning Chains to Verifiable Subproblems: Curriculum Reinforcement Learning Enables Credit Assignment for LLM Reasoning
por: Jiang, Xitai, et al.
Publicado: (2026)

PVMark: Enabling Public Verifiability for LLM Watermarking Schemes
por: Duan, Haohua, et al.
Publicado: (2025)

References Improve LLM Alignment in Non-Verifiable Domains
por: Shi, Kejian, et al.
Publicado: (2026)

MM-Verify: Enhancing Multimodal Reasoning with Chain-of-Thought Verification
por: Sun, Linzhuang, et al.
Publicado: (2025)

When To Solve, When To Verify: Compute-Optimal Problem Solving and Generative Verification for LLM Reasoning
por: Singhi, Nishad, et al.
Publicado: (2025)

HealthQ: Unveiling Questioning Capabilities of LLM Chains in Healthcare Conversations
por: Wang, Ziyu, et al.
Publicado: (2024)

Let it Calm: Exploratory Annealed Decoding for Verifiable Reinforcement Learning
por: Yang, Chenghao, et al.
Publicado: (2025)

Verifying the Robustness of Automatic Credibility Assessment
por: Przybyła, Piotr, et al.
Publicado: (2023)

Reinforcing General Reasoning without Verifiers
por: Zhou, Xiangxin, et al.
Publicado: (2025)

RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments
por: Zeng, Zhiyuan, et al.
Publicado: (2025)

Compress the Context, Keep the Commitments: A Formal Framework for Verifiable LLM Context Compression
por: Trukhina, Natalia, et al.
Publicado: (2026)

Verifying Chain-of-Thought Reasoning via Its Computational Graph
por: Zhao, Zheng, et al.
Publicado: (2025)

Don't Trust: Verify -- Grounding LLM Quantitative Reasoning with Autoformalization
por: Zhou, Jin Peng, et al.
Publicado: (2024)

Transfer Q Star: Principled Decoding for LLM Alignment
por: Chakraborty, Souradip, et al.
Publicado: (2024)

Verifying Computational Graphs in Production-Grade Distributed Machine Learning Frameworks
por: Zulkifli, Kahfi S., et al.
Publicado: (2025)

AutoPSV: Automated Process-Supervised Verifier
por: Lu, Jianqiao, et al.
Publicado: (2024)

vCache: Verified Semantic Prompt Caching
por: Schroeder, Luis Gaspar, et al.
Publicado: (2025)

On the Query Complexity of Verifier-Assisted Language Generation
por: Botta, Edoardo, et al.
Publicado: (2025)

FUSE: Ensembling Verifiers with Zero Labeled Data
por: Lee, Joonhyuk, et al.
Publicado: (2026)

NOVER: Incentive Training for Language Models via Verifier-Free Reinforcement Learning
por: Liu, Wei, et al.
Publicado: (2025)

OPV: Outcome-based Process Verifier for Efficient Long Chain-of-Thought Verification
por: Wu, Zijian, et al.
Publicado: (2025)

Examining Reasoning LLMs-as-Judges in Non-Verifiable LLM Post-Training
por: Liu, Yixin, et al.
Publicado: (2026)

Chart-RL: Generalized Chart Comprehension via Reinforcement Learning with Verifiable Rewards
por: Zhang, Xin, et al.
Publicado: (2026)

On the Ability of Transformers to Verify Plans
por: Sarrof, Yash, et al.
Publicado: (2026)

DeferMem: Query-Time Evidence Distillation via Reinforcement Learning for Long-Term Memory QA
por: Yin, Jianing, et al.
Publicado: (2026)