3 papers
cs.CL2026
Beyond Token-Level Guidance: Inference-Time Alignment of Specialized LLMs via Cross-Family Representation Steering
Jin Gan, Xin Li, Jun Luo
Large language models (LLMs) finetuned for specialized domains represent crucial high-impact applications. Inference-time alignment improves safety degraded from specialization fin…
cs.LG2026
To Intervene or Not: Guiding Inference-time Alignment with Probabilistic Model Blending
Jin Gan, Xin Li, Jun Luo
The wide deployment of LLMs has made model alignment necessary to make newly trained models safely and effectively respond to user instructions. Among different methods, inference-…
cs.CV2024
MST: Adaptive Multi-Scale Tokens Guided Interactive Segmentation
Long Xu, Shanghong Li, Yongquan Chen +2
Interactive segmentation has gained significant attention for its application in human-computer interaction and data annotation. To address the target scale variation issue in inte…