:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Entezami, Erfan, Naseh, Ali
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2503.03039
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

RLHS: Mitigating Misalignment in RLHF with Hindsight Simulation
by: Liang, Kaiqu, et al.
Published: (2025)

Preemptive Detection and Steering of LLM Misalignment via Latent Reachability
by: Karnik, Sathwik, et al.
Published: (2025)

Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer
by: Liu, Zhihan, et al.
Published: (2024)

Backdooring Bias ($B^2$) into Stable Diffusion Models
by: Naseh, Ali, et al.
Published: (2024)

A Safe Exploration Strategy for Model-free Task Adaptation in Safety-constrained Grid Environments
by: Entezami, Erfan, et al.
Published: (2024)

Understanding the Effects of RLHF on LLM Generalisation and Diversity
by: Kirk, Robert, et al.
Published: (2023)

Throttling Web Agents Using Reasoning Gates
by: Kumar, Abhinav, et al.
Published: (2025)

RLHF Workflow: From Reward Modeling to Online RLHF
by: Dong, Hanze, et al.
Published: (2024)

RLHF from Heterogeneous Feedback via Personalization and Preference Aggregation
by: Park, Chanwoo, et al.
Published: (2024)

ROCM: RLHF on consistency models
by: Shekhar, Shivanshu, et al.
Published: (2025)

Overtrained, Not Misaligned
by: Schreiber, Joel, et al.
Published: (2026)

Exploring the In-Context Learning Capabilities of LLMs for Money Laundering Detection in Financial Graphs
by: Pirmorad, Erfan
Published: (2025)

Mitigating Reward Over-Optimization in RLHF via Behavior-Supported Regularization
by: Dai, Juntao, et al.
Published: (2025)

Distributionally Robust Token Optimization in RLHF
by: Jin, Yeping, et al.
Published: (2026)

OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework
by: Hu, Jian, et al.
Published: (2024)

Understanding Emergent Misalignment via Feature Superposition Geometry
by: Minegishi, Gouki, et al.
Published: (2026)

Adaptive Margin RLHF via Preference over Preferences
by: Chittepu, Yaswanth, et al.
Published: (2025)

The Hidden Link Between RLHF and Contrastive Learning
by: Lv, Xufei, et al.
Published: (2025)

Towards Reliable Alignment: Uncertainty-aware RLHF
by: Banerjee, Debangshu, et al.
Published: (2024)

Boosting Deductive Reasoning with Step Signals In RLHF
by: Li, Jialian, et al.
Published: (2024)

InfoRM: Mitigating Reward Hacking in RLHF via Information-Theoretic Reward Modeling
by: Miao, Yuchun, et al.
Published: (2024)

Model Organisms for Emergent Misalignment
by: Turner, Edward, et al.
Published: (2025)

Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback
by: Yuan, Yifu, et al.
Published: (2024)

Mitigating Reward Hacking in RLHF via Advantage Sign Robustness
by: Ono, Shinnosuke, et al.
Published: (2026)

RLHF and IIA: Perverse Incentives
by: Xu, Wanqiao, et al.
Published: (2023)

Reward-Robust RLHF in LLMs
by: Yan, Yuzi, et al.
Published: (2024)

A Descriptive and Normative Theory of Human Beliefs in RLHF
by: Dandekar, Sylee, et al.
Published: (2025)

KL-regularization Itself is Differentially Private in Bandits and RLHF
by: Zhang, Yizhou, et al.
Published: (2025)

Policy-labeled Preference Learning: Is Preference Enough for RLHF?
by: Cho, Taehyun, et al.
Published: (2025)

Policy Filtration for RLHF to Mitigate Noise in Reward Models
by: Zhang, Chuheng, et al.
Published: (2024)

Democratic Preference Alignment via Sortition-Weighted RLHF
by: Sana, Suvadip, et al.
Published: (2026)

Convergent Linear Representations of Emergent Misalignment
by: Soligo, Anna, et al.
Published: (2025)

Misalignment from Treating Means as Ends
by: Marklund, Henrik, et al.
Published: (2025)

Comprehensive Modeling Approaches for Forecasting Bitcoin Transaction Fees: A Comparative Study
by: Ma, Jiangqin, et al.
Published: (2025)

Sharpe Ratio-Guided Active Learning for Preference Optimization in RLHF
by: Belakaria, Syrine, et al.
Published: (2025)

Offline and Online KL-Regularized RLHF under Differential Privacy
by: Wu, Yulian, et al.
Published: (2025)

A Shared Low-Rank Adaptation Approach to Personalized RLHF
by: Liu, Renpu, et al.
Published: (2025)

G-Core: A Simple, Scalable and Balanced RLHF Trainer
by: Wu, Junyu, et al.
Published: (2025)

Bias Fitting to Mitigate Length Bias of Reward Model in RLHF
by: Zhao, Kangwen, et al.
Published: (2025)

Generalisation of RLHF under Reward Shift and Clipped KL Regularisation
by: Tang, Kenton, et al.
Published: (2026)