5 citations · 12 across the 14 of their papers we have counts for
5 papers · 1 filter
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…
GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules
Teng Xiao, Chao Cui, Huaisheng Zhu +1
Pretraining molecular representations is crucial for drug and material discovery. Recent methods focus on learning representations from geometric structures, effectively capturing…
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…
MolBind: Multimodal Alignment of Language, Molecules, and Proteins
Teng Xiao, Chao Cui, Huaisheng Zhu +1
Recent advancements in biology and chemistry have leveraged multi-modal learning, integrating molecules and their natural language descriptions to enhance drug discovery. However,…
3M-Diffusion: Latent Multi-Modal Diffusion for Language-Guided Molecular Structure Generation
Huaisheng Zhu, Teng Xiao, Vasant G Honavar
Generating molecular structures with desired properties is a critical task with broad applications in drug discovery and materials design. We propose 3M-Diffusion, a novel multi-mo…