5 papers
StepAudio 2.5 Technical Report
Bin Lin, Bo Zhao, Boyong Wu +98
Unified audio-language modeling has emerged as a prominent trend in modern speech systems, promising to bring the reasoning capabilities of large language models to auditory tasks.…
On a Connection Between Imitation Learning and RLHF
Teng Xiao, Yige Yuan, Mingxiao Li +2
This work studies the alignment of large language models with preference data from an imitation learning perspective. We establish a close theoretical connection between reinforcem…
SimPER: A Minimalist Approach to Preference Alignment without Hyperparameters
Teng Xiao, Yige Yuan, Zhengyu Chen +4
Existing preference optimization objectives for language model alignment require additional hyperparameters that must be extensively tuned to achieve optimal performance, increasin…
Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment
Teng Xiao, Yige Yuan, Huaisheng Zhu +2
We study the problem of aligning large language models (LLMs) with human preference data. Contrastive preference optimization has shown promising results in aligning LLMs with avai…
How to Leverage Demonstration Data in Alignment for Large Language Model? A Self-Imitation Learning Perspective
Teng Xiao, Mingxiao Li, Yige Yuan +3
This paper introduces a novel generalized self-imitation learning () framework, which effectively and efficiently aligns large language models with offline demonstra…