Towards Bridging the Reward-Generation Gap in Direct Alignment Algorithms
Fuente:
arXiv
Saved in:
| Main Authors: | Xiao, Zeguan, Chen, Yun, Chen, Guanhua, Tang, Ke |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Adaptive Segment-level Reward: Bridging the Gap Between Action and Reward Space in Alignment
by: Li, Yanshi, et al.
Published: (2024)
by: Li, Yanshi, et al.
Published: (2024)
Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms
by: Rafailov, Rafael, et al.
Published: (2024)
by: Rafailov, Rafael, et al.
Published: (2024)
Distract Large Language Models for Automatic Jailbreak Attack
by: Xiao, Zeguan, et al.
Published: (2024)
by: Xiao, Zeguan, et al.
Published: (2024)
Bridging the Gap Between Preference Alignment and Machine Unlearning
by: Feng, Xiaohua, et al.
Published: (2025)
by: Feng, Xiaohua, et al.
Published: (2025)
Enhancing Uncertainty Estimation in LLMs with Expectation of Aggregated Internal Belief
by: Xiao, Zeguan, et al.
Published: (2025)
by: Xiao, Zeguan, et al.
Published: (2025)
Directional Alignment Mitigates Reward Hacking in Reinforcement Learning for Language Models
by: Deng, Wenlong, et al.
Published: (2026)
by: Deng, Wenlong, et al.
Published: (2026)
Reward-free Alignment for Conflicting Objectives
by: Chen, Peter, et al.
Published: (2026)
by: Chen, Peter, et al.
Published: (2026)
Noise Contrastive Alignment of Language Models with Explicit Rewards
by: Chen, Huayu, et al.
Published: (2024)
by: Chen, Huayu, et al.
Published: (2024)
On the Limited Generalization Capability of the Implicit Reward Model Induced by Direct Preference Optimization
by: Lin, Yong, et al.
Published: (2024)
by: Lin, Yong, et al.
Published: (2024)
Spurious Rewards Paradox: Mechanistically Understanding How RLVR Activates Memorization Shortcuts in LLMs
by: Yan, Lecheng, et al.
Published: (2026)
by: Yan, Lecheng, et al.
Published: (2026)
Alignment through Meta-Weighted Online Sampling: Bridging the Gap between Data Generation and Preference Optimization
by: Yang, Junming, et al.
Published: (2025)
by: Yang, Junming, et al.
Published: (2025)
Generalizing Reward Modeling for Out-of-Distribution Preference Learning
by: Jia, Chen
Published: (2024)
by: Jia, Chen
Published: (2024)
Enhancing Delta Compression in LLMs via SVD-based Quantization Error Minimization
by: Xiong, Boya, et al.
Published: (2025)
by: Xiong, Boya, et al.
Published: (2025)
Towards Cost-Effective Reward Guided Text Generation
by: Rashid, Ahmad, et al.
Published: (2025)
by: Rashid, Ahmad, et al.
Published: (2025)
Bridging the Creativity Understanding Gap: Small-Scale Human Alignment Enables Expert-Level Humor Ranking in LLMs
by: Zhou, Kuan Lok, et al.
Published: (2025)
by: Zhou, Kuan Lok, et al.
Published: (2025)
Understanding Likelihood Over-optimisation in Direct Alignment Algorithms
by: Shi, Zhengyan, et al.
Published: (2024)
by: Shi, Zhengyan, et al.
Published: (2024)
On the Robustness of Reward Models for Language Model Alignment
by: Hong, Jiwoo, et al.
Published: (2025)
by: Hong, Jiwoo, et al.
Published: (2025)
SALMON: Self-Alignment with Instructable Reward Models
by: Sun, Zhiqing, et al.
Published: (2023)
by: Sun, Zhiqing, et al.
Published: (2023)
Towards Robust Alignment of Language Models: Distributionally Robustifying Direct Preference Optimization
by: Wu, Junkang, et al.
Published: (2024)
by: Wu, Junkang, et al.
Published: (2024)
Cascade Reward Sampling for Efficient Decoding-Time Alignment
by: Li, Bolian, et al.
Published: (2024)
by: Li, Bolian, et al.
Published: (2024)
Towards High Data Efficiency in Reinforcement Learning with Verifiable Reward
by: Tang, Xinyu, et al.
Published: (2025)
by: Tang, Xinyu, et al.
Published: (2025)
Toward Automated Robustness Evaluation of Mathematical Reasoning
by: Hou, Yutao, et al.
Published: (2025)
by: Hou, Yutao, et al.
Published: (2025)
Larger or Smaller Reward Margins to Select Preferences for Alignment?
by: Huang, Kexin, et al.
Published: (2025)
by: Huang, Kexin, et al.
Published: (2025)
Arithmetic Control of LLMs for Diverse User Preferences: Directional Preference Alignment with Multi-Objective Rewards
by: Wang, Haoxiang, et al.
Published: (2024)
by: Wang, Haoxiang, et al.
Published: (2024)
Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment
by: Xiao, Teng, et al.
Published: (2024)
by: Xiao, Teng, et al.
Published: (2024)
Bridging the Gap for Test-Time Multimodal Sentiment Analysis
by: Guo, Zirun, et al.
Published: (2024)
by: Guo, Zirun, et al.
Published: (2024)
Modeling LLM Unlearning as an Asymmetric Two-Task Learning Problem
by: Xiao, Zeguan, et al.
Published: (2026)
by: Xiao, Zeguan, et al.
Published: (2026)
Representation-Guided Parameter-Efficient LLM Unlearning
by: Xiao, Zeguan, et al.
Published: (2026)
by: Xiao, Zeguan, et al.
Published: (2026)
Robust LLM Unlearning Against Relearning Attacks: The Minor Components in Representations Matter
by: Xiao, Zeguan, et al.
Published: (2026)
by: Xiao, Zeguan, et al.
Published: (2026)
Low-probability Tokens Sustain Exploration in Reinforcement Learning with Verifiable Reward
by: Huang, Guanhua, et al.
Published: (2025)
by: Huang, Guanhua, et al.
Published: (2025)
Energy-Based Reward Models for Robust Language Model Alignment
by: Lochab, Anamika, et al.
Published: (2025)
by: Lochab, Anamika, et al.
Published: (2025)
Online Merging Optimizers for Boosting Rewards and Mitigating Tax in Alignment
by: Lu, Keming, et al.
Published: (2024)
by: Lu, Keming, et al.
Published: (2024)
Towards Unified Task Embeddings Across Multiple Models: Bridging the Gap for Prompt-Based Large Language Models and Beyond
by: Wang, Xinyu, et al.
Published: (2024)
by: Wang, Xinyu, et al.
Published: (2024)
GRAM-R$^2$: Self-Training Generative Foundation Reward Models for Reward Reasoning
by: Wang, Chenglong, et al.
Published: (2025)
by: Wang, Chenglong, et al.
Published: (2025)
RLHF in an SFT Way: From Optimal Solution to Reward-Weighted Alignment
by: Du, Yuhao, et al.
Published: (2025)
by: Du, Yuhao, et al.
Published: (2025)
Learning to Optimize Multi-Objective Alignment Through Dynamic Reward Weighting
by: Lu, Yining, et al.
Published: (2025)
by: Lu, Yining, et al.
Published: (2025)
ARGS: Alignment as Reward-Guided Search
by: Khanov, Maxim, et al.
Published: (2024)
by: Khanov, Maxim, et al.
Published: (2024)
Large Language Model-Enhanced Algorithm Selection: Towards Comprehensive Algorithm Representation
by: Wu, Xingyu, et al.
Published: (2023)
by: Wu, Xingyu, et al.
Published: (2023)
Rewards-in-Context: Multi-objective Alignment of Foundation Models with Dynamic Preference Adjustment
by: Yang, Rui, et al.
Published: (2024)
by: Yang, Rui, et al.
Published: (2024)
Reward-aware Preference Optimization: A Unified Mathematical Framework for Model Alignment
by: Sun, Shengyang, et al.
Published: (2025)
by: Sun, Shengyang, et al.
Published: (2025)
Similar Items
-
Adaptive Segment-level Reward: Bridging the Gap Between Action and Reward Space in Alignment
by: Li, Yanshi, et al.
Published: (2024) -
Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms
by: Rafailov, Rafael, et al.
Published: (2024) -
Distract Large Language Models for Automatic Jailbreak Attack
by: Xiao, Zeguan, et al.
Published: (2024) -
Bridging the Gap Between Preference Alignment and Machine Unlearning
by: Feng, Xiaohua, et al.
Published: (2025) -
Enhancing Uncertainty Estimation in LLMs with Expectation of Aggregated Internal Belief
by: Xiao, Zeguan, et al.
Published: (2025)