6 papers
Persona-Pruner: Sculpting Lightweight Models for Role-Playing
Jinsu Kim, Jihoon Tack, Noah Lee +1
Language Models (LMs) have shown remarkable potential as role-playing chatbots, delivering consistent, stylized interactions when given a specification of a character or user perso…
Margin-aware Preference Optimization for Aligning Diffusion Models without Reference
Jiwoo Hong, Sayak Paul, Noah Lee +3
Modern preference alignment methods, such as DPO, rely on divergence regularization to a reference model for training stability-but this creates a fundamental problem we call "refe…
AlphaPO: Reward Shape Matters for LLM Alignment
Aman Gupta, Shao Tang, Qingquan Song +10
Reinforcement Learning with Human Feedback (RLHF) and its variants have made huge strides toward the effective alignment of large language models (LLMs) to follow instructions and…
On the Robustness of Reward Models for Language Model Alignment
Jiwoo Hong, Noah Lee, Eunki Kim +5
The Bradley-Terry (BT) model is widely practiced in reward modeling for reinforcement learning with human feedback (RLHF). Despite its effectiveness, reward models (RMs) trained wi…
The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Models
Seungone Kim, Juyoung Suk, Ji Yong Cho +29
As language models (LMs) become capable of handling a wide range of tasks, their evaluation is becoming as challenging as their development. Most generation benchmarks currently as…
Cross-lingual Transfer of Reward Models in Multilingual Alignment
Jiwoo Hong, Noah Lee, Rodrigo MartÃnez-Castaño +2
Reinforcement learning with human feedback (RLHF) is shown to largely benefit from precise reward models (RMs). However, recent studies in reward modeling schemes are skewed toward…