:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Author:	Cataneo, Felipe Biava
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence
Online Access:	https://arxiv.org/abs/2601.08842
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

How to Evaluate Reward Models for RLHF
by: Frick, Evan, et al.
Published: (2024)

Conversational Disease Diagnosis via External Planner-Controlled Large Language Models
by: Sun, Zhoujian, et al.
Published: (2024)

Segmenting Text and Learning Their Rewards for Improved RLHF in Language Model
by: Yin, Yueqin, et al.
Published: (2025)

Sequence to Sequence Reward Modeling: Improving RLHF by Language Feedback
by: Zhou, Jiayi, et al.
Published: (2024)

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

PKU-SafeRLHF: Towards Multi-Level Safety Alignment for LLMs with Human Preference
by: Ji, Jiaming, et al.
Published: (2024)

The Accuracy Paradox in RLHF: When Better Reward Models Don't Yield Better Language Models
by: Chen, Yanjun, et al.
Published: (2024)

Uncertainty as a Planning Signal: Multi-Turn Decision Making for Goal-Oriented Conversation
by: Ling, Xinyi, et al.
Published: (2026)

Language Modeling with Editable External Knowledge
by: Li, Belinda Z., et al.
Published: (2024)

From RLHF to Direct Alignment: A Theoretical Unification of Preference Learning for Large Language Models
by: Raheja, Tarun, et al.
Published: (2026)

Proxy-RLHF: Decoupling Generation and Alignment in Large Language Model with Proxy
by: Zhu, Yu, et al.
Published: (2024)

The Good, The Bad, and The Greedy: Evaluation of LLMs Should Not Ignore Non-Determinism
by: Song, Yifan, et al.
Published: (2024)

Reward Model Overoptimisation in Iterated RLHF
by: Wolf, Lorenz, et al.
Published: (2025)

Three Models of RLHF Annotation: Extension, Evidence, and Authority
by: Coyne, Steve
Published: (2026)

Assessing Good, Bad and Ugly Arguments Generated by ChatGPT: a New Dataset, its Methodology and Associated Tasks
by: Rocha, Victor Hugo Nascimento, et al.
Published: (2024)

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

Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models
by: Noukhovitch, Michael, et al.
Published: (2024)

Automated Conversion of Static to Dynamic Scheduler via Natural Language
by: Tang, Paul Mingzheng, et al.
Published: (2024)

Clarify: Improving Model Robustness With Natural Language Corrections
by: Lee, Yoonho, et al.
Published: (2024)

The Evolution of Natural Language Processing: How Prompt Optimization and Language Models are Shaping the Future
by: Saleem, Summra, et al.
Published: (2025)

Quantile Regression for Distributional Reward Models in RLHF
by: Dorka, Nicolai
Published: (2024)

Deep Natural Language Feature Learning for Interpretable Prediction
by: Urrutia, Felipe, et al.
Published: (2023)

Prototypical Reward Network for Data-Efficient RLHF
by: Zhang, Jinghan, et al.
Published: (2024)

Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wisely
by: Zhao, Siyun, et al.
Published: (2024)

DiffuGuard: How Intrinsic Safety is Lost and Found in Diffusion Large Language Models
by: Li, Zherui, et al.
Published: (2025)

Identifying Multiple Personalities in Large Language Models with External Evaluation
by: Song, Xiaoyang, et al.
Published: (2024)

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

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

Reward Difference Optimization For Sample Reweighting In Offline RLHF
by: Wang, Shiqi, et al.
Published: (2024)

Teaching Language Models How to Code Like Learners: Conversational Serialization for Student Simulation
by: Koutcheme, Charles, et al.
Published: (2026)

Self-Anchoring Calibration Drift in Large Language Models: How Multi-Turn Conversations Reshape Model Confidence
by: Harshavardhan
Published: (2026)

JMedEthicBench: A Multi-Turn Conversational Benchmark for Evaluating Medical Safety in Japanese Large Language Models
by: Liu, Junyu, et al.
Published: (2026)

How to Retrieve Examples in In-context Learning to Improve Conversational Emotion Recognition using Large Language Models?
by: Wang, Mengqi, et al.
Published: (2025)

Mitigating Length Bias in RLHF through a Causal Lens
by: Kim, Hyeonji, et al.
Published: (2025)

More RLHF, More Trust? On The Impact of Preference Alignment On Trustworthiness
by: Li, Aaron J., et al.
Published: (2024)

Removing RLHF Protections in GPT-4 via Fine-Tuning
by: Zhan, Qiusi, et al.
Published: (2023)

It Takes Two: On the Seamlessness between Reward and Policy Model in RLHF
by: Lu, Taiming, et al.
Published: (2024)

Rethinking External Slow-Thinking: From Snowball Errors to Probability of Correct Reasoning
by: Gan, Zeyu, et al.
Published: (2025)

Dataset Reset Policy Optimization for RLHF
by: Chang, Jonathan D., et al.
Published: (2024)

RLHF Can Speak Many Languages: Unlocking Multilingual Preference Optimization for LLMs
by: Dang, John, et al.
Published: (2024)