ICML 2026

Deadlines
Machine Learning/CORE Unranked

ICML 2026

ICML 2026 Workshop: AI as a Tool for Mathematics, Computer Science, and Machine Learning

Jul 10 2026Seoul, South KoreaOfficial workshop site Site reachable

The ICML 2026 workshop 'AI as a Tool for Mathematics, Computer Science, and Machine Learning' focuses on how AI can enhance human research workflows in fields like machine learning, optimization, statistics, and algorithms. It emphasizes reproducible, human-AI collaborative methods—such as prompting strategies, agentic systems, and integration with proof assistants—rather than autonomous AI research, aiming to build a shared community resource of effective AI-assisted research practices.

Official CFP Back to deadlines Verified September 9, 2026

Key deadlines

Verified September 9, 2026

Full paper

May 14, 2026

AoE

Workshop timeline

Submission and decisions

Full paperKey deadline

May 14, 2026 · AoE

Paper fit

Contribution paths

A strong submission should clearly identify its contribution and evaluate it appropriately.

Full Papers

Up to 4 pages (excluding references), with supplementary material allowed after references; must follow ICML 2026 format; should describe reproducible AI-assisted research workflows with time-savings, performance improvements, and verification methods.

Research areas in scope

01

AI-Assisted Research Workflows

AI-Assisted WorkflowsIterative verification loopsFailure modes and detectionPrompting patterns for correctnessDecomposition and self-critiqueMulti-agent strategiesSwitching from informal to formal reasoningTool-Augmented ReasoningIntegrating LLMs with computation (code, symbolic algebra, numerics)Literature navigationProof assistants (e.g., Lean)Research AccelerationAI for derivationsCounterexample searchExperiment designMethods that transfer across subfieldsAI-assisted research problem formulationAI-assisted experiment design for ML researchSolving mathematical research problems with AI assistanceFormalization and verification workflowsAutomation of iterative loops

Policies worth checking twice

  • Non-archival: papers published at other venues are welcome
  • Double-blind review: submissions must be anonymized
  • Accepted papers will be presented as demos or posters; select papers may be invited for contributed talks
  • Each submission nominates one author as a reciprocal reviewer
  • Submissions must be reproducible by ML researchers within a few hours using academic-level resources
  • Workflows must avoid non-research tasks such as simple writing, basic literature search, slide/poster creation, or pure software engineering

Official sources

Compiled from the official call for papers. The organizers’ pages remain authoritative.

Official workshop site

Last verified September 9, 2026