activity
20242026
collaborators

14 papers

cs.AI2026

Scientific Data Skills: Enabling Agent-Ready Scientific Data Services at Scale

Xiaohan Huang, Qingqing Long, Xiaolei Du +9

Scientific data are increasingly used by AI agents, yet existing dataset representations provide limited support for autonomous discovery, interpretation, and invocation. This limi…

q-bio.GN2026

SciHorizon-GENE: Benchmarking LLM for Life Sciences Inference from Gene Knowledge to Functional Understanding

Xiaohan Huang, Meng Xiao, Chuan Qin +4

Large language models (LLMs) have shown growing promise in biomedical research, particularly for knowledge-driven interpretation tasks. However, their ability to reliably reason fr…

cs.LG2026

From Snapshots to Trajectories: Learning Single-Cell Gene Expression Dynamics via Conditional Flow Matching

Siyu Pu, Qingqing Long, Xiaohan Huang +7

Single-cell RNA sequencing (scRNA-seq) provides high-dimensional profiles of cellular states, enabling data-driven modeling of cellular dynamics over time. In practice, time-resolv…

cs.IR2026

ScienceDB AI: An LLM-Driven Agentic Recommender System for Large-Scale Scientific Data Sharing Services

Qingqing Long, Haotian Chen, Chenyang Zhao +6

The rapid growth of AI for Science (AI4S) has underscored the significance of scientific datasets, leading to the establishment of numerous national scientific data centers and sha…

cs.CL2025

Knowledge-Driven Agentic Scientific Corpus Distillation Framework for Biomedical Large Language Models Training

Meng Xiao, Xunxin Cai, Qingqing Long +3

Corpus distillation for biomedical large language models (LLMs) seeks to address the pressing challenge of insufficient quantity and quality in open-source annotated scientific cor…

cs.CL2025

Knowledge Hierarchy Guided Biological-Medical Dataset Distillation for Domain LLM Training

Xunxin Cai, Chengrui Wang, Qingqing Long +2

The rapid advancement of large language models (LLMs) in biological-medical applications has highlighted a gap between their potential and the limited scale and often low quality o…