3 papers
cs.LG2025
Efficient Parallel Samplers for Recurrent-Depth Models and Their Connection to Diffusion Language Models
Jonas Geiping, Xinyu Yang, Guinan Su
Language models with recurrent depth, also referred to as universal or looped when considering transformers, are defined by the capacity to increase their computation through the r…
cs.CR2025
When "Correct" Is Not Safe: Can We Trust Functionally Correct Patches Generated by Code Agents?
Yibo Peng, James Song, Lei Li +6
Code agents are increasingly trusted to autonomously fix bugs on platforms such as GitHub, yet their security evaluation focuses almost exclusively on functional correctness. In th…
cs.LG2025
APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding
Xinyu Yang, Tianqi Chen, Beidi Chen
Context-augmented generation (CAG) techniques, including RAG and ICL, require the efficient combination of multiple contexts to generate responses to user queries. Directly inputti…