8 papers
Probing RLVR training instability through the lens of objective-level hacking
Yiming Dong, Kun Fu, Haoyu Li +5
Prolonged reinforcement learning with verifiable rewards (RLVR) has been shown to drive continuous improvements in the reasoning capabilities of large language models, but the trai…
An agentic framework for gravitational-wave counterpart association in the multi-messenger era
Yiming Dong, Yacheng Kang, Junjie Zhao +3
With the detection of gravitational waves (GWs), multi-messenger astronomy has opened a new window for advancing our understanding of astrophysics, dense matter, gravitation, and c…
Cracking Gravitational Wave Multiple Ringdown Modes in Space
Ziming Wang, Han Wang, Yuxin Yang +4
Ringdown signals from perturbed black holes (BHs) offer a clean window into BH spacetime, strong-field gravity, and fundamental physics. Presently the quasi-normal modes of stellar…
Inferring neutron-star Love-Q relations from gravitational waves in the hierarchical Bayesian framework
Zhihao Zheng, Ziming Wang, Jinwen Deng +2
Despite the large uncertainties in the equation of state for neutron stars (NSs), a tight universal ``Love-Q'' relation exists between their dimensionless tidal deformability, …
Lightweight posterior construction for gravitational-wave catalogs with the Kolmogorov-Arnold network
Wenshuai Liu, Yiming Dong, Ziming Wang +1
Neural density estimation has seen widespread applications in the gravitational-wave (GW) data analysis, which enables real-time parameter estimation for compact binary coalescence…
From Macro to Micro: Probing Dataset Diversity in Language Model Fine-Tuning
Haoyu Li, Xuhong Li, Yiming Dong +1
Dataset diversity plays a pivotal role for the successful training of many machine learning models, particularly in the supervised fine-tuning (SFT) stage of large language model (…