2 papers
cs.CV2026
Just Noticeable Difference Modeling for Token Compression in Vision-Language-Action Models
Zhuoyuan Li, Rui Zhao, Jin Wang +5
Token compression has become a key technique for reducing the inference cost of large foundation models, with approaches such as token pruning and KV-cache reuse widely adopted in…
cs.SE2026
A Preliminary Study on Explaining Risk of Code Changes using LLM-Based Prediction Models
Yalin Liu, Kosay Jabre, Rui Abreu +10
Predictions by machine learning (ML) and artificial intelligence (AI) models are often received skeptically unless they are paired with intelligible explanations. In the context of…