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cs.LG2026
Localizing Credit at the Divergence: Path-Conditioned Self-Distillation for LLM Reasoning
Yu Li, Shu Hong, Tian Lan
Reinforcement learning from verifiable rewards assigns a single scalar to each rollout, leaving token-level credit assignment underspecified in long reasoning traces. On-policy sel…
cs.LG2025
Global Optimization on Graph-Structured Data via Gaussian Processes with Spectral Representations
Shu Hong, Yongsheng Mei, Mahdi Imani +1
Bayesian optimization (BO) is a powerful framework for optimizing expensive black-box objectives, yet extending it to graph-structured domains remains challenging due to the discre…
cs.LG2025
AnalogFed: Privacy-Preserving Discovery of Analog Circuits at Scale with Federated Generative AI
Qiufeng Li, Shu Hong, Tian Lan +1
Recent advances in generative AI (GenAI) have shown transformative potential for modern hardware design. However, existing GenAI-driven approaches fall short of enabling large-scal…