activity
20242026
most citedWeatherGFM: Learning A Weather Generalist Foundation Model via In-context Learning

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CL2026

SignDPO: Multi-level Direct Preference Optimisation for Skeleton-based Gloss-free Sign Language Translation

Muxin Pu, Xiao-Ming Wu, Mei Kuan Lim +3

We present SignDPO, a novel multi-level Direct Preference Optimisation (DPO) framework designed to enhance the alignment of skeleton-based Sign Language Translation. While current…

cs.AI2025

Probing Scientific General Intelligence of LLMs with Scientist-Aligned Workflows

Wanghan Xu, Yuhao Zhou, Yifan Zhou +104

Despite advances in scientific AI, a coherent framework for Scientific General Intelligence (SGI)-the ability to autonomously conceive, investigate, and reason across scientific do…

cs.AI2025

MSEarth: A Multimodal Benchmark for Earth Science Phenomenon Discovery with MLLMs

Xiangyu Zhao, Wanghan Xu, Bo Liu +7

The rapid advancement of multimodal large language models (MLLMs) offers new opportunities for complex scientific challenges, yet their application in earth science-especially at t…

cs.LG20241 cited

WeatherGFM: Learning A Weather Generalist Foundation Model via In-context Learning

Xiangyu Zhao, Zhiwang Zhou, Wenlong Zhang +9

The Earth's weather system encompasses intricate weather data modalities and diverse weather understanding tasks, which hold significant value to human life. Existing data-driven m…

cs.CL2024

Understanding Layer Significance in LLM Alignment

Guangyuan Shi, Zexin Lu, Xiaoyu Dong +4

Aligning large language models (LLMs) through supervised fine-tuning is essential for tailoring them to specific applications. Recent studies suggest that alignment primarily adjus…