Call for Papers

We invite submissions to Agentic Systems for Molecular Sciences, a NeurIPS 2026 workshop taking place in Paris on 13 December.

Agentic systems are only as good as the representations, predictors, generative models, and simulators they orchestrate. Progress on the agentic frontier depends on progress in the underlying machine learning methods, and on honest evaluation of both. We invite submissions across the full stack, from foundational methods to end-to-end agents, including negative results, careful baselines, and benchmark contributions alongside methodological advances. We welcome participation from machine learning researchers, chemists, biologists, materials scientists, and interdisciplinary practitioners, and encourage submissions from early-career and underrepresented authors.

Topics of interest

Topics include, but are not limited to:

• Agentic and multi-agent systems for the molecular sciences; tool use, planning, and orchestration
• Benchmarks, reproducibility, negative results, and rigorous evaluation of scientific agents and their components
• Grounding LLMs via chemical databases, simulators, and experimental feedback
• Closed-loop / self-driving labs, active learning, and Bayesian optimization for experimental design
• Foundation models for chemistry, biology, and materials, and their benchmarking
• Representation learning and generative models for molecules, proteins, reactions, and materials
• Bioactivity, ADME, toxicity, and molecular property prediction
• Reaction prediction, retrosynthesis, and synthesis planning
• Structure-based and ligand-based virtual screening; docking, scoring, and protein–ligand / protein–protein interaction prediction
• Perturbation modelling, batch effect correction, domain adaptation and single-cell prediction
• Machine-learned interatomic potentials, force fields, molecular dynamics, and geometric / equivariant / physics-informed deep learning

Contributions that clarify what current methods can and cannot do, including negative results, careful ablations, and rigorous baselines, are especially welcome.

Submission guidelines

Format. Submissions must use the NeurIPS 2026 workshop LaTeX template. The main text is limited to maximum 5 content pages, including all figures and tables. References and appendices do not count toward the page limit, but reviewers are not obliged to read supplementary material — the main text must be self-contained. The NeurIPS checklist is not required. Maximum file size: 50 MB.

Anonymity. Reviewing is double-blind. Submissions must be anonymized, with author names, affiliations, and acknowledgments removed, and prior work cited in the third person.

Submission site. Submissions are managed via OpenReview. Papers remain private during review. All authors should maintain up-to-date OpenReview profiles for conflict-of-interest management and paper matching. Submission site: OpenReview

Non-archival policy. The workshop is non-archival. Papers under review elsewhere are welcome, and accepted papers may be published at other venues afterward. Work already published at NeurIPS or other archival ML venues should not be submitted; substantial extensions of prior non-ML-venue work are eligible.

Presentation. Accepted contributions are presented as posters, with a subset selected for contributed talks. Contributed-talk slots are reserved for early-career first authors. A Best Paper Award will be given for the strongest overall contribution.

Important Dates

• Call for papers: mid-July 2026
• Submission deadline: 29 August 2026 (AOE)
• Reviewing: 30 August – 24 September 2026
• Author notification: 29 September 2026
• Camera-ready deadline: 31 October 2026 (AOE)
• Workshop: 13 December 2026 · Paris

Submissions are reviewed on OpenReview. The workshop is non-archival.