8 papers
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.…
OmniMatBench: A Human-Calibrated Multimodal Reasoning Benchmark Across 19 Materials Science Subfields
Wanhao Liu, Jiaqing Xie, Qian Tan +10
As multimodal language models play an increasingly important role in scientific research, materials science offers a critical testbed due to its interdisciplinary, multimodal, and…
ChemDFM-R: A Chemical Reasoning LLM Enhanced with Atomized Chemical Knowledge
Zihan Zhao, Ziping Wan, Lu Chen +12
Atomized chemical knowledge, such as functional group information of molecules and reactions, plays a pivotal intermediate role in the reasoning process that connects molecular str…
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…
Developing ChemDFM as a large language foundation model for chemistry
Zihan Zhao, Da Ma, Lu Chen +11
Artificial intelligence (AI) has played an increasingly important role in chemical research. However, most models currently used in chemistry are specialist models that require tra…