2 papers
cs.SE2026
PerfCoder: Large Language Models for Interpretable Code Performance Optimization
Jiuding Yang, Shengyao Lu, Hongxuan Liu +4
Large language models (LLMs) have achieved remarkable progress in automatic code generation, yet their ability to produce high-performance code remains limited--a critical requirem…
cs.CV2026
Don't Show Pixels, Show Cues: Unlocking Visual Tool Reasoning in Language Models via Perception Programs
Muhammad Kamran Janjua, Hugo Silva, Di Niu +1
Multimodal language models (MLLMs) are increasingly paired with vision tools (e.g., depth, flow, correspondence) to enhance visual reasoning. However, despite access to these tool-…