5 papers
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.…
XFlow: An Executable Protocol Programming System for Reliable Multi-Agent Workflows
Hanqi Li, Jing Peng, Zijian Wang +2
LLM-based multi-agent systems increasingly coordinate planning, reasoning, tool use, and human interaction, yet their reliability remains limited. A central source of this limitati…
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…
When Long Helps Short: How Context Length in Supervised Fine-tuning Affects Behavior of Large Language Models
Yingming Zheng, Hanqi Li, Kai Yu +1
Large language models (LLMs) have achieved impressive performance across natural language processing (NLP) tasks. As real-world applications increasingly demand longer context wind…
Converging to a Lingua Franca: Evolution of Linguistic Regions and Semantics Alignment in Multilingual Large Language Models
Hongchuan Zeng, Senyu Han, Lu Chen +1
Large language models (LLMs) have demonstrated remarkable performance, particularly in multilingual contexts. While recent studies suggest that LLMs can transfer skills learned in…