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Molt: A Scalable PyTorch-Native Training Framework for Agentic Reinforcement Learning research paper by NVIDIA, 2026

NVIDIA · Jul 22, 2026 · Agents and evaluation · 1 citations · 33 upvotes · unverified

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What it shows

Molt is a compact PyTorch framework for agentic reinforcement learning that enables efficient asynchronous training of multimodal and mixture-of-experts policies with minimal overhead.

UnverifiedHugging Face's summary; not yet checked by hand.

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About this paper
Authors
Jian Hu, Huiying Li, Hao Zhang and 8 more
arXiv
2607.21653 · PDF
Venue
arXiv.org
Citations
1, 0 influential · Semantic Scholar
Upvotes
33 · Hugging Face
Code
github.com/NVIDIA-NeMo/labs-molt
Lab
NVIDIA · on Companies · on Acquisitions · on Quarterly · on Paydays · on TechConf

Changes

What changed
Influential citationsfirst count: 0Sep 25, 2026
Citationsfirst count: 1Sep 25, 2026
New paperFound by the weekly scan, unverifiedSep 25, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

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