Copertina

Inference-Time Scaling for Generalist Reward Modeling

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Liu, Zijun, Wang, Peiyi, Xu, Runxin, Ma, Shirong, Ruan, Chong, Li, Peng, Liu, Yang, Wu, Yu
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Computation and Language Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
di: Shao, Zhihong, et al.
Pubblicazione: (2024)

Temper and Tilt Lead to SLOP: Reward Hacking Mitigation with Inference-Time Alignment
di: Wang, Ye, et al.
Pubblicazione: (2026)

LimiX: Unleashing Structured-Data Modeling Capability for Generalist Intelligence
di: Zhang, Xingxuan, et al.
Pubblicazione: (2025)

Let the Expert Stick to His Last: Expert-Specialized Fine-Tuning for Sparse Architectural Large Language Models
di: Wang, Zihan, et al.
Pubblicazione: (2024)

Inverse Reinforcement Learning with Dynamic Reward Scaling for LLM Alignment
di: Cheng, Ruoxi, et al.
Pubblicazione: (2025)

Diagnosing Training Inference Mismatch in LLM Reinforcement Learning
di: Zhong, Tianle, et al.
Pubblicazione: (2026)

Reward Modeling with Ordinal Feedback: Wisdom of the Crowd
di: Liu, Shang, et al.
Pubblicazione: (2024)

ControlMath: Controllable Data Generation Promotes Math Generalist Models
di: Chen, Nuo, et al.
Pubblicazione: (2024)

ROSE: A Reward-Oriented Data Selection Framework for LLM Task-Specific Instruction Tuning
di: Wu, Yang, et al.
Pubblicazione: (2024)

Advancing LLM Reasoning Generalists with Preference Trees
di: Yuan, Lifan, et al.
Pubblicazione: (2024)

$ϕ$-Decoding: Adaptive Foresight Sampling for Balanced Inference-Time Exploration and Exploitation
di: Xu, Fangzhi, et al.
Pubblicazione: (2025)

Text2Reward: Reward Shaping with Language Models for Reinforcement Learning
di: Xie, Tianbao, et al.
Pubblicazione: (2023)

DavIR: Data Selection via Implicit Reward for Large Language Models
di: Zhou, Haotian, et al.
Pubblicazione: (2023)

Entropy Centroids as Intrinsic Rewards for Test-Time Scaling
di: Zhao, Wenshuo, et al.
Pubblicazione: (2026)

MarkovScale: Towards Optimal Sequential Scaling at Inference Time
di: Wang, Youkang, et al.
Pubblicazione: (2026)

Generalist Foundation Models Are Not Clinical Enough for Hospital Operations
di: Jiang, Lavender Y., et al.
Pubblicazione: (2025)

On Designing Effective RL Reward at Training Time for LLM Reasoning
di: Gao, Jiaxuan, et al.
Pubblicazione: (2024)

Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy
di: Liu, Chris Yuhao, et al.
Pubblicazione: (2025)

AIGS: Generating Science from AI-Powered Automated Falsification
di: Liu, Zijun, et al.
Pubblicazione: (2024)

Scaling Generalist Data-Analytic Agents
di: Qiao, Shuofei, et al.
Pubblicazione: (2025)

Duel-Evolve: Reward-Free Test-Time Scaling via LLM Self-Preferences
di: Karlekar, Sweta, et al.
Pubblicazione: (2026)

Enabling Weak LLMs to Judge Response Reliability via Meta Ranking
di: Liu, Zijun, et al.
Pubblicazione: (2024)

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

More Bang for the Buck: Process Reward Modeling with Entropy-Driven Uncertainty
di: Cao, Lang, et al.
Pubblicazione: (2025)

Mitigating Premature Exploitation in Particle-based Monte Carlo for Inference-Time Scaling
di: Giannone, Giorgio, et al.
Pubblicazione: (2025)

The Lessons of Developing Process Reward Models in Mathematical Reasoning
di: Zhang, Zhenru, et al.
Pubblicazione: (2025)

DeepSeek LLM: Scaling Open-Source Language Models with Longtermism
di: DeepSeek-AI, et al.
Pubblicazione: (2024)

CoLD: Counterfactually-Guided Length Debiasing for Process Reward Models in Mathematical Reasoning
di: Zheng, Congmin, et al.
Pubblicazione: (2025)

Reward Models Identify Consistency, Not Causality
di: Xu, Yuhui, et al.
Pubblicazione: (2025)

Are More Tokens Rational? Inference-Time Scaling in Language Models as Adaptive Resource Rationality
di: Hu, Zhimin, et al.
Pubblicazione: (2026)

SPARK: Stepwise Process-Aware Rewards for Reference-Free Reinforcement Learning
di: Rahman, Salman, et al.
Pubblicazione: (2025)

Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms
di: Rafailov, Rafael, et al.
Pubblicazione: (2024)

From Generalist to Specialist: A Survey of Large Language Models for Chemistry
di: Han, Yang, et al.
Pubblicazione: (2024)

Action Controlled Paraphrasing
di: Shi, Ning, et al.
Pubblicazione: (2024)

GLiREL -- Generalist Model for Zero-Shot Relation Extraction
di: Boylan, Jack, et al.
Pubblicazione: (2025)

GLiClass: Generalist Lightweight Model for Sequence Classification Tasks
di: Stepanov, Ihor, et al.
Pubblicazione: (2025)

Scaling Inference-Efficient Language Models
di: Bian, Song, et al.
Pubblicazione: (2025)

SPEC-RL: Accelerating On-Policy Reinforcement Learning with Speculative Rollouts
di: Liu, Bingshuai, et al.
Pubblicazione: (2025)

PRISM: Parametrically Refactoring Inference for Speculative Sampling Draft Models
di: Wang, Xuliang, et al.
Pubblicazione: (2026)

Observational Scaling Laws and the Predictability of Language Model Performance
di: Ruan, Yangjun, et al.
Pubblicazione: (2024)