Cover Image

Mining Intrinsic Rewards from LLM Hidden States for Efficient Best-of-N Sampling

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Guo, Jizhou, Wu, Zhaomin, Yang, Hanchen, Yu, Philip S.
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

LENS: Learning Ensemble Confidence from Neural States for Multi-LLM Answer Integration
by: Guo, Jizhou
Published: (2025)

TreeBoN: Enhancing Inference-Time Alignment with Speculative Tree-Search and Best-of-N Sampling
by: Qiu, Jiahao, et al.
Published: (2024)

Federated Data-Efficient Instruction Tuning for Large Language Models
by: Qin, Zhen, et al.
Published: (2024)

Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models
by: Chow, Yinlam, et al.
Published: (2024)

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

Best-of-N Jailbreaking
by: Hughes, John, et al.
Published: (2024)

When LLM Judge Scores Look Good but Best-of-N Decisions Fail
by: Landesberg, Eddie
Published: (2026)

Boosting Protein Language Models with Negative Sample Mining
by: Xu, Yaoyao, et al.
Published: (2024)

DPIC: Decoupling Prompt and Intrinsic Characteristics for LLM Generated Text Detection
by: Yu, Xiao, et al.
Published: (2023)

Variational Best-of-N Alignment
by: Amini, Afra, et al.
Published: (2024)

LLM DNA: Tracing Model Evolution via Functional Representations
by: Wu, Zhaomin, et al.
Published: (2025)

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

AdaBoN: Adaptive Best-of-N Alignment
by: Raman, Vinod, et al.
Published: (2025)

Efficient Prompt Optimization Through the Lens of Best Arm Identification
by: Shi, Chengshuai, et al.
Published: (2024)

Learning Generative Selection for Best-of-N
by: Toshniwal, Shubham, et al.
Published: (2026)

ReDit: Reward Dithering for Improved LLM Policy Optimization
by: Wei, Chenxing, et al.
Published: (2025)

Majority of the Bests: Improving Best-of-N via Bootstrapping
by: Rakhsha, Amin, et al.
Published: (2025)

GeRe: Towards Efficient Anti-Forgetting in Continual Learning of LLM via General Samples Replay
by: Zhang, Yunan, et al.
Published: (2025)

Efficient Reasoning with Hidden Thinking
by: Shen, Xuan, et al.
Published: (2025)

BOND: Aligning LLMs with Best-of-N Distillation
by: Sessa, Pier Giuseppe, et al.
Published: (2024)

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

IRIS: Intrinsic Reward Image Synthesis
by: Chen, Yihang, et al.
Published: (2025)

Online Intrinsic Rewards for Decision Making Agents from Large Language Model Feedback
by: Zheng, Qinqing, et al.
Published: (2024)

RewardFlow: Topology-Aware Reward Propagation on State Graphs for Agentic RL with Large Language Models
by: Feng, Xiao, et al.
Published: (2026)

LaSeR: Reinforcement Learning with Last-Token Self-Rewarding
by: Yang, Wenkai, et al.
Published: (2025)

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

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

FlowRL: Matching Reward Distributions for LLM Reasoning
by: Zhu, Xuekai, et al.
Published: (2025)

Best of mini-N in-loop Sampling: A Contextual Quality Reward Model for Reliable and Efficient Best-of-N Sampling
by: Rho, Hyung Gyu, et al.
Published: (2025)

Inference-Time Scaling for Generalist Reward Modeling
by: Liu, Zijun, et al.
Published: (2025)

LLM-NEO: Parameter Efficient Knowledge Distillation for Large Language Models
by: Yang, Runming, et al.
Published: (2024)

Automated Rewards via LLM-Generated Progress Functions
by: Sarukkai, Vishnu, et al.
Published: (2024)

User-LLM: Efficient LLM Contextualization with User Embeddings
by: Ning, Lin, et al.
Published: (2024)

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

HiPRAG: Hierarchical Process Rewards for Efficient Agentic Retrieval Augmented Generation
by: Wu, Peilin, et al.
Published: (2025)

HypoEval: Hypothesis-Guided Evaluation for Natural Language Generation
by: Li, Mingxuan, et al.
Published: (2025)

When Chain-of-Thought Fails, the Solution Hides in the Hidden States
by: Mehrafarin, Houman, et al.
Published: (2026)

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

Beyond Numeric Rewards: In-Context Dueling Bandits with LLM Agents
by: Xia, Fanzeng, et al.
Published: (2024)

Scalable Best-of-N Selection for Large Language Models via Self-Certainty
by: Kang, Zhewei, et al.
Published: (2025)