Group Robust Preference Optimization in Reward-free RLHF
Fuente:
arXiv
Saved in:
| Main Authors: | Ramesh, Shyam Sundhar, Hu, Yifan, Chaimalas, Iason, Mehta, Viraj, Sessa, Pier Giuseppe, Ammar, Haitham Bou, Bogunovic, Ilija |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Distributionally Robust Model-based Reinforcement Learning with Large State Spaces
by: Ramesh, Shyam Sundhar, et al.
Published: (2023)
by: Ramesh, Shyam Sundhar, et al.
Published: (2023)
On Almost Surely Safe Alignment of Large Language Models at Inference-Time
by: Ji, Xiaotong, et al.
Published: (2025)
by: Ji, Xiaotong, et al.
Published: (2025)
Multi-Task GRPO: Reliable LLM Reasoning Across Tasks
by: Ramesh, Shyam Sundhar, et al.
Published: (2026)
by: Ramesh, Shyam Sundhar, et al.
Published: (2026)
Robust Multi-Objective Controlled Decoding of Large Language Models
by: Son, Seongho, et al.
Published: (2025)
by: Son, Seongho, et al.
Published: (2025)
LLM-WikiRace Benchmark: How Far Can LLMs Plan over Real-World Knowledge Graphs?
by: Ziomek, Juliusz, et al.
Published: (2026)
by: Ziomek, Juliusz, et al.
Published: (2026)
This Is Your Doge, If It Please You: Exploring Deception and Robustness in Mixture of LLMs
by: Wolf, Lorenz, et al.
Published: (2025)
by: Wolf, Lorenz, et al.
Published: (2025)
Many of Your DPOs are Secretly One: Attempting Unification Through Mutual Information
by: Tutnov, Rasul, et al.
Published: (2025)
by: Tutnov, Rasul, et al.
Published: (2025)
SparsePO: Controlling Preference Alignment of LLMs via Sparse Token Masks
by: Christopoulou, Fenia, et al.
Published: (2024)
by: Christopoulou, Fenia, et al.
Published: (2024)
Explorer: Robust Collection of Interactable GUI Elements
by: Chaimalas, Iason, et al.
Published: (2025)
by: Chaimalas, Iason, et al.
Published: (2025)
Overton Pluralistic Reinforcement Learning for Large Language Models
by: Fu, Yu, et al.
Published: (2026)
by: Fu, Yu, et al.
Published: (2026)
Reward-Robust RLHF in LLMs
by: Yan, Yuzi, et al.
Published: (2024)
by: Yan, Yuzi, et al.
Published: (2024)
Why Can Large Language Models Generate Correct Chain-of-Thoughts?
by: Tutunov, Rasul, et al.
Published: (2023)
by: Tutunov, Rasul, et al.
Published: (2023)
Reward Difference Optimization For Sample Reweighting In Offline RLHF
by: Wang, Shiqi, et al.
Published: (2024)
by: Wang, Shiqi, et al.
Published: (2024)
Active Preference Optimization for Sample Efficient RLHF
by: Das, Nirjhar, et al.
Published: (2024)
by: Das, Nirjhar, et al.
Published: (2024)
WPO: Enhancing RLHF with Weighted Preference Optimization
by: Zhou, Wenxuan, et al.
Published: (2024)
by: Zhou, Wenxuan, et al.
Published: (2024)
Mixture of Attentions For Speculative Decoding
by: Zimmer, Matthieu, et al.
Published: (2024)
by: Zimmer, Matthieu, et al.
Published: (2024)
RLHF Workflow: From Reward Modeling to Online RLHF
by: Dong, Hanze, et al.
Published: (2024)
by: Dong, Hanze, et al.
Published: (2024)
Risk-Controlled Lean-as-Judge for Natural-Language Mathematical Reasoning
by: Bourigault, Pauline, et al.
Published: (2026)
by: Bourigault, Pauline, et al.
Published: (2026)
Mitigating Reward Hacking in RLHF via Advantage Sign Robustness
by: Ono, Shinnosuke, et al.
Published: (2026)
by: Ono, Shinnosuke, et al.
Published: (2026)
Subjective Depth and Timescale Transformers: Learning Where and When to Compute
by: Wieser, Frederico, et al.
Published: (2025)
by: Wieser, Frederico, et al.
Published: (2025)
YFPO: A Preliminary Study of Yoked Feature Preference Optimization with Neuron-Guided Rewards for Mathematical Reasoning
by: Le, Yifan
Published: (2026)
by: Le, Yifan
Published: (2026)
Robust Preference Optimization through Reward Model Distillation
by: Fisch, Adam, et al.
Published: (2024)
by: Fisch, Adam, et al.
Published: (2024)
Reward Shaping to Mitigate Reward Hacking in RLHF
by: Fu, Jiayi, et al.
Published: (2025)
by: Fu, Jiayi, et al.
Published: (2025)
Taming Overconfidence in LLMs: Reward Calibration in RLHF
by: Leng, Jixuan, et al.
Published: (2024)
by: Leng, Jixuan, et al.
Published: (2024)
Untangling Component Imbalance in Hybrid Linear Attention Conversion Methods
by: Benfeghoul, Martin, et al.
Published: (2025)
by: Benfeghoul, Martin, et al.
Published: (2025)
Robust Bayesian Optimisation with Unbounded Corruptions
by: Ezzerg, Abdelhamid, et al.
Published: (2025)
by: Ezzerg, Abdelhamid, et al.
Published: (2025)
Reward Model Overoptimisation in Iterated RLHF
by: Wolf, Lorenz, et al.
Published: (2025)
by: Wolf, Lorenz, et al.
Published: (2025)
How to Evaluate Reward Models for RLHF
by: Frick, Evan, et al.
Published: (2024)
by: Frick, Evan, et al.
Published: (2024)
Right Now, Wrong Then: Non-Stationary Direct Preference Optimization under Preference Drift
by: Son, Seongho, et al.
Published: (2024)
by: Son, Seongho, et al.
Published: (2024)
Prototypical Reward Network for Data-Efficient RLHF
by: Zhang, Jinghan, et al.
Published: (2024)
by: Zhang, Jinghan, et al.
Published: (2024)
No Preference Left Behind: Group Distributional Preference Optimization
by: Yao, Binwei, et al.
Published: (2024)
by: Yao, Binwei, et al.
Published: (2024)
Sample Efficient Preference Alignment in LLMs via Active Exploration
by: Mehta, Viraj, et al.
Published: (2023)
by: Mehta, Viraj, et al.
Published: (2023)
Adaptive Margin RLHF via Preference over Preferences
by: Chittepu, Yaswanth, et al.
Published: (2025)
by: Chittepu, Yaswanth, et al.
Published: (2025)
SuRe: Surprise-Driven Prioritised Replay for Continual LLM Learning
by: Hazard, Hugo, et al.
Published: (2025)
by: Hazard, Hugo, et al.
Published: (2025)
Quantile Regression for Distributional Reward Models in RLHF
by: Dorka, Nicolai
Published: (2024)
by: Dorka, Nicolai
Published: (2024)
ODIN: Disentangled Reward Mitigates Hacking in RLHF
by: Chen, Lichang, et al.
Published: (2024)
by: Chen, Lichang, et al.
Published: (2024)
Information-Theoretic Reward Decomposition for Generalizable RLHF
by: Mao, Liyuan, et al.
Published: (2025)
by: Mao, Liyuan, et al.
Published: (2025)
Al-Khwarizmi: Discovering Physical Laws with Foundation Models
by: Mower, Christopher E., et al.
Published: (2025)
by: Mower, Christopher E., et al.
Published: (2025)
Exploratory Preference Optimization: Harnessing Implicit Q*-Approximation for Sample-Efficient RLHF
by: Xie, Tengyang, et al.
Published: (2024)
by: Xie, Tengyang, et al.
Published: (2024)
RLHF Can Speak Many Languages: Unlocking Multilingual Preference Optimization for LLMs
by: Dang, John, et al.
Published: (2024)
by: Dang, John, et al.
Published: (2024)
Similar Items
-
Distributionally Robust Model-based Reinforcement Learning with Large State Spaces
by: Ramesh, Shyam Sundhar, et al.
Published: (2023) -
On Almost Surely Safe Alignment of Large Language Models at Inference-Time
by: Ji, Xiaotong, et al.
Published: (2025) -
Multi-Task GRPO: Reliable LLM Reasoning Across Tasks
by: Ramesh, Shyam Sundhar, et al.
Published: (2026) -
Robust Multi-Objective Controlled Decoding of Large Language Models
by: Son, Seongho, et al.
Published: (2025) -
LLM-WikiRace Benchmark: How Far Can LLMs Plan over Real-World Knowledge Graphs?
by: Ziomek, Juliusz, et al.
Published: (2026)