Skip to content

[2026-06-19] Performance Optimization β€” 1 paper(s)Β #289

Description

@Zhaoyang-Chu

πŸ“‹ 2026-06-19 Β· Performance Optimization β€” 1 paper(s)

Auto-processed by the arXiv crawler pipeline. Review each paper and reply with the commands below.


1. AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Authors: Zepeng Li, Jie Ren, Zhanyong Tang, Jie Zheng, Zheng Wang
Venue: arXiv 2026/06

AutoPass is a multi-agent framework that optimizes compiler performance by querying internal optimization states and analyzing intermediate representations. It iteratively refines LLVM optimization configurations based on runtime feedback to diagnose regressions and improve execution latency without requiring task-specific training.
πŸ“„ Paper


Review commands (comment on this issue):

  • /approve all β€” accept all papers
  • /approve 1,3 β€” accept papers 1 and 3
  • /reject 2 β€” discard paper 2
  • /approve 1,3 /reject 2 β€” mixed
  • /edit 1 category=code_generation β€” change category before approving
  • /edit 1 venue=ICSE 2026 β€” fix venue

Metadata

Metadata

Assignees

No one assigned

    Labels

    Type

    No type

    Fields

    No fields configured for issues without a type.

    Projects

    No projects

    Milestone

    No milestone

    Relationships

    None yet

    Development

    No branches or pull requests

    Issue actions