collaborators

6 papers

cs.AI2026

A Unified Per-Token Gating Family for On-Policy Distillation: FKL/RKL Mixing with Multi-Channel and Bias Coefficients

Suwan Wu, Yumeng Lin, Pengcheng Yuan +1

Per-token gating of forward/reverse KL losses has become a standard technique for on-policy knowledge distillation (OPD), but existing methods such as EOPD (Jin et al., 2026) and T…

cs.AI2026

SIRF: A Spec-Internalized Risk Foundation Model for Industrial Content Risk Control

Suwan Wu, Yumeng Lin, Pengcheng Yuan +1

For industrial content risk control, the real deployment constraint is not average accuracy but how much risk can be auto-handled under high precision and second-level latency. We…

cs.AI2026

AdaSTORM: Scaling LLM Reasoning on Dynamic Graphs via Adaptive Spatio-Temporal Multi-Agent Collaboration

Bing Hao, Ruijie Wang, Haodong Qian +5

Large Language Models (LLMs) demonstrate remarkable potential in dynamic graph reasoning, but suffer from a scaling bottleneck: current models can only handle graphs with tens of n…

cs.CL2026

SPOT: Span-level Pause-of-Thought for Efficient and Interpretable Latent Reasoning in Large Language Models

Yunlong Chu, Minglai Shao, Yuhang Liu +4

Explicit Chain-of-Thought improves the reasoning performance of large language models but often incurs high inference cost due to verbose token-level traces. While recent approache…

cs.CL2026

RouteGoT: Node-Adaptive Routing for Cost-Efficient Graph of Thoughts Reasoning

Yuhang Liu, Ruijie Wang, Yunlong Chu +4

Large Language Models (LLMs) excel at multi-step reasoning, yet increasing the structural complexity of inference does not consistently improve system-level returns. Methods such a…

cs.CV2025

Face4FairShifts: A Large Image Benchmark for Fairness and Robust Learning across Visual Domains

Yumeng Lin, Dong Li, Xintao Wu +4

Ensuring fairness and robustness in machine learning models remains a challenge, particularly under domain shifts. We present Face4FairShifts, a large-scale facial image benchmark…