7 papers
LP-SFT: Keeping Plausible Alternatives Alive in Supervised Fine-Tuning
Yueyang Wang, Baolong Bi, Shuo Lu +3
Supervised fine-tuning (SFT) is widely used to adapt pretrained language models to downstream domains, but can over-specialize the model and degrade its pre-existing capabilities.…
EdgeBench: Unveiling Scaling Laws of Learning from Real-World Environments
Deyao Zhu, Xin Zhou, Shengling Qin +44
Pretraining scaling laws reveal that model capability improves predictably with data and compute. But learning from real world environments after deployment remains far less unders…
HE-SNR: Uncovering Latent Logic via Entropy for Guiding Mid-Training on SWE-bench
Yueyang Wang, Jiawei Fu, Baolong Bi +2
SWE-bench has emerged as the premier benchmark for evaluating Large Language Models on complex software engineering tasks. While these capabilities are fundamentally acquired durin…
A Graph-Retrieval-Augmented Generation Framework Enhances Decision-Making in the Circular Economy
Yang Zhao, Chengxiao Dai, Dusit Niyato +7
Large language models (LLMs) hold promise for sustainable manufacturing, but often hallucinate industrial codes and emission factors, undermining regulatory and investment decision…
Boundaries of the bounded hyperbolic components of polynomials
Yan Gao, Xiaoguang Wang, Yueyang Wang
In this paper, we study the local connectivity and Hausdorff dimension for the boundaries of the bounded hyperbolic components in the space of polynomials of degree…
Estimating Committor Functions via Deep Adaptive Sampling on Rare Transition Paths
Yueyang Wang, Kejun Tang, Xili Wang +3
The committor functions are central to investigating rare but important events in molecular simulations. It is known that computing the committor function suffers from the curse of…
Discovering Invariant Neighborhood Patterns for Heterophilic Graphs
Jinluan Yang, Ruihao Zhang, Zhengyu Chen +4
This paper studies the problem of distribution shifts on non-homophilous graphs Mosting existing graph neural network methods rely on the homophilous assumption that nodes from the…