most citedA Survey of Scientific Large Language Models: From Data Foundations to Agent Frontiers

1 citations · 1 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CE2025

Finetuning Large Language Model as an Effective Symbolic Regressor

Yingfan Hua, Ruikun Li, Jun Yao +5

Deriving governing equations from observational data, known as Symbolic Regression (SR), is a cornerstone of scientific discovery. Large Language Models, (LLMs) have shown promise…

cs.CL2025

SciReasoner: Laying the Scientific Reasoning Ground Across Disciplines

Yizhou Wang, Chen Tang, Han Deng +29

We present a scientific reasoning foundation model that aligns natural language with heterogeneous scientific representations. The model is pretrained on a 206B-token corpus spanni…

cs.CL2025★ 1 cited

A Survey of Scientific Large Language Models: From Data Foundations to Agent Frontiers

Ming Hu, Chenglong Ma, Wei Li +117

Scientific Large Language Models (Sci-LLMs) are transforming how knowledge is represented, integrated, and applied in scientific research, yet their progress is shaped by the compl…

cs.CV2025

High Performance Space Debris Tracking in Complex Skylight Backgrounds with a Large-Scale Dataset

Guohang Zhuang, Weixi Song, Jinyang Huang +3

With the rapid development of space exploration, space debris has attracted more attention due to its potential extreme threat, leading to the need for real-time and accurate debri…

cs.CV2025

STAR: A Benchmark for Astronomical Star Fields Super-Resolution

Kuo-Cheng Wu, Guohang Zhuang, Jinyang Huang +3

Super-resolution (SR) advances astronomical imaging by enabling cost-effective high-resolution capture, crucial for detecting faraway celestial objects and precise structural analy…

cs.SI2024

Dynamic Information Dissemination Model Incorporating Non-Adjacent Node Interaction

Xinyu Li, Jinyang Huang, Xiang Zhang +5

Describing the dynamics of information dissemination within social networks poses a formidable challenge. Despite multiple endeavors aimed at addressing this issue, only a limited…