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Agent Explorative Policy Optimization for Multimodal Agentic Reasoning research paper by NVIDIA, 2026

NVIDIA · May 27, 2026 · Agents and evaluation · 2 citations · 89 upvotes · unverified

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What it shows

Agents using vision-language models with extended reasoning face challenges in tool utilization, which are addressed through AXPO, a method that improves performance by optimizing thinking prefixes and tool call resampling.

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

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About this paper
Authors
Minki Kang, Shizhe Diao, Ryo Hachiuma and 4 more
arXiv
2605.28774 · PDF
Venue
arXiv.org
Citations
2, 0 influential · Semantic Scholar
Upvotes
89 · Hugging Face
Lab
NVIDIA · on Companies · on Acquisitions · on Quarterly · on Paydays · on TechConf

Changes

What changed
Influential citationsfirst count: 0Sep 25, 2026
Citationsfirst count: 2Sep 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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