2 citations · 2 across the 2 of their papers we have counts for
4 papers · 1 filter
Hierarchical Data Selection via Manifold Coverage and Sparse Feature Coverage in LLM Post-training
Peng Sun, Yi Yang, Antong Zhang +7
As supervised fine-tuning data continues to scale, selecting high-value subsets from large candidate pools is crucial for reducing training cost and improving model performance. Ex…
Data-DPO: Direct Preference Optimization for Target Model Data Selection in LLM Post-Training
Peng Sun, Yi Yang, Antong Zhang +7
Data selection in supervised fine-tuning aims to select a small set of effective samples from large-scale candidate data, reducing training cost while preserving model performance.…
MS-BART: Unified Modeling of Mass Spectra and Molecules for Structure Elucidation
Yang Han, Pengyu Wang, Kai Yu +2
Mass spectrometry (MS) plays a critical role in molecular identification, significantly advancing scientific discovery. However, structure elucidation from MS data remains challeng…
ChemDFM-X: Towards Large Multimodal Model for Chemistry
Zihan Zhao, Bo Chen, Jingpiao Li +10
Rapid developments of AI tools are expected to offer unprecedented assistance to the research of natural science including chemistry. However, neither existing unimodal task-specif…