Cover Image

Process Reward Models for LLM Agents: Practical Framework and Directions

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Choudhury, Sanjiban
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Better than Your Teacher: LLM Agents that learn from Privileged AI Feedback
by: Choudhury, Sanjiban, et al.
Published: (2024)

Aligning LLMs with Domain Invariant Reward Models
by: Wu, David, et al.
Published: (2025)

Efficient Imitation under Misspecification
by: Espinosa-Dice, Nicolas, et al.
Published: (2025)

Multi-Turn Code Generation Through Single-Step Rewards
by: Jain, Arnav Kumar, et al.
Published: (2025)

InteRACT: Transformer Models for Human Intent Prediction Conditioned on Robot Actions
by: Kedia, Kushal, et al.
Published: (2023)

Motion Tracks: A Unified Representation for Human-Robot Transfer in Few-Shot Imitation Learning
by: Ren, Juntao, et al.
Published: (2025)

Hybrid Inverse Reinforcement Learning
by: Ren, Juntao, et al.
Published: (2024)

One-Shot Imitation under Mismatched Execution
by: Kedia, Kushal, et al.
Published: (2024)

Imitation Learning via Focused Satisficing
by: Shah, Rushit N., et al.
Published: (2025)

Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching
by: Jain, Arnav Kumar, et al.
Published: (2024)

LLM Reasoning with Process Rewards for Outcome-Guided Steps
by: Rezaei, Mohammad, et al.
Published: (2026)

Adversarial Training for Process Reward Models
by: Juneja, Gurusha, et al.
Published: (2025)

Reward Hacking Benchmark: Measuring Exploits in LLM Agents with Tool Use
by: Thaman, Kunvar
Published: (2026)

GRPO is Secretly a Process Reward Model
by: Sullivan, Michael, et al.
Published: (2025)

Few-shot Steerable Alignment: Adapting Rewards and LLM Policies with Neural Processes
by: Kobalczyk, Katarzyna, et al.
Published: (2024)

Distributional Process Reward Models: Calibrated Prediction of Future Rewards via Conditional Optimal Transport
by: Ma, Rachel, et al.
Published: (2026)

X-Sim: Cross-Embodiment Learning via Real-to-Sim-to-Real
by: Dan, Prithwish, et al.
Published: (2025)

Process Reward Models That Think
by: Khalifa, Muhammad, et al.
Published: (2025)

SignalLLM: A General-Purpose LLM Agent Framework for Automated Signal Processing
by: Ke, Junlong, et al.
Published: (2025)

Efficient Process Reward Model Training via Active Learning
by: Duan, Keyu, et al.
Published: (2025)

Optimal Transport for LLM Reward Modeling from Noisy Preference
by: Pan, Licheng, et al.
Published: (2026)

PROF: An LLM-based Reward Code Preference Optimization Framework for Offline Imitation Learning
by: Sun, Shengjie, et al.
Published: (2025)

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

DreamPRM: Domain-Reweighted Process Reward Model for Multimodal Reasoning
by: Cao, Qi, et al.
Published: (2025)

DreamPRM-Code: Function-as-Step Process Reward Model with Label Correction for LLM Coding
by: Zhang, Ruiyi, et al.
Published: (2025)

Accelerating LLM Reasoning via Early Rejection with Partial Reward Modeling
by: Cheshmi, Seyyed Saeid, et al.
Published: (2025)

AgentRM: Enhancing Agent Generalization with Reward Modeling
by: Xia, Yu, et al.
Published: (2025)

Same Signal, Opposite Meaning: Direction-Informed Adaptive Learning for LLM Agents
by: Li, Ziming, et al.
Published: (2026)

Know What You Don't Know: Uncertainty Calibration of Process Reward Models
by: Park, Young-Jin, et al.
Published: (2025)

MemReward: Graph-Based Experience Memory for LLM Reward Prediction with Limited Labels
by: Luo, Tianyang, et al.
Published: (2026)

Reward-Augmented Data Enhances Direct Preference Alignment of LLMs
by: Zhang, Shenao, et al.
Published: (2024)

ProgAgent:A Continual RL Agent with Progress-Aware Rewards
by: Tan, Jinzhou, et al.
Published: (2026)

RewardUQ: A Unified Framework for Uncertainty-Aware Reward Models
by: Yang, Daniel, et al.
Published: (2026)

Model-Based Reinforcement Learning in Discrete-Action Non-Markovian Reward Decision Processes
by: Trapasso, Alessandro, et al.
Published: (2025)

A Model Can Help Itself: Reward-Free Self-Training for LLM Reasoning
by: Li, Mengqi, et al.
Published: (2025)

Rethinking Rubric Generation for Improving LLM Judge and Reward Modeling for Open-ended Tasks
by: Shen, William F., et al.
Published: (2026)

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

$ξ$-DPO: Direct Preference Optimization via Ratio Reward Margin
by: Fan, Zhengyuan, et al.
Published: (2026)

Robotouille: An Asynchronous Planning Benchmark for LLM Agents
by: Gonzalez-Pumariega, Gonzalo, et al.
Published: (2025)

Debate as Reward: A Multi-Agent Reward System for Scientific Ideation via RL Post-Training
by: Salimi, Moein, et al.
Published: (2026)