Full papers
Original research submissions presenting novel methods or significant advances in discrete diffusion or flow models for generation.
Machine Learning/CORE Unranked
BeNTo Workshop NeurIPS 2026
Beyond Next Token Prediction: Diffusion and Flow Models for Next-Generation Decoding
BeNTo is a NeurIPS 2026 workshop focused on discrete diffusion and flow models for parallel, non-causal generation, moving beyond next-token prediction in generative models. It aims to bring together researchers working on next-generation decoding architectures in machine learning and AI for scientific applications.
Key deadlines
Verified September 9, 2026Full paper
September 6, 2026
AoE
Workshop timeline
Submission and decisions
Full paperKey deadline
September 6, 2026 · AoE
Paper fit
Contribution paths
A strong submission should clearly identify its contribution and evaluate it appropriately.
Short papers
Concise contributions such as preliminary results, system demos, or position papers.
Journal track
Extended versions of previously published work suitable for journal submission, with additional analysis or evaluation.
Research areas in scope
01
Workshop Topics
Discrete diffusion modelsFlow models for generationParallel non-causal decodingNext-generation generative architecturesApplications in biosciencesEfficient inference and training methods
Policies worth checking twice
- Submissions must be anonymized for blind review.
- Papers must not be under review at any other conference or journal during the BeNTo review period.
- Author lists cannot be changed after the submission deadline.
- Use of AI tools in writing must be disclosed in a separate statement.
- All submissions must adhere to the NeurIPS 2026 formatting guidelines.
Official sources
Compiled from the official call for papers. The organizers’ pages remain authoritative.
Last verified September 9, 2026