EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models

EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models | Signal Canvas | ScienceToStartup

Page Freshness

Signal Canvas proof surface

Canonical route: /signal-canvas/expo-ft-sample-efficient-reinforcement-learning-finetuning-for-vision-language-action-models

stale

Proof freshness: stale
Proof status: unverified
Display score: 0/10
Last proof check: 2026-05-27
Score updated: 2026-05-26
Score fresh until: 2026-06-25
References: 0
Source count: 3
Coverage: 50%

This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.

Agent Handoff

Canonical ID expo-ft-sample-efficient-reinforcement-learning-finetuning-for-vision-language-action-models | Route /signal-canvas/expo-ft-sample-efficient-reinforcement-learning-finetuning-for-vision-language-action-models

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/expo-ft-sample-efficient-reinforcement-learning-finetuning-for-vision-language-action-models

MCP example

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    "query_text": "Summarize EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models"
  }
}

source_context

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  "query": "EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models",
  "normalized_query": "2605.25477",
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  "paper_ref": "expo-ft-sample-efficient-reinforcement-learning-finetuning-for-vision-language-action-models",
  "topic_slug": null,
  "benchmark_ref": null,
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Evidence Receipt

Route status: building

Claims: 1

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models

PDF: https://arxiv.org/pdf/2605.25477v1

Source count: 3

Coverage: 50%

Last proof check: 2026-05-27T00:07:10.775Z

Signal Canvas receipt window

Not build-ready: EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models

/buildability/expo-ft-sample-efficient-reinforcement-learning-finetuning-for-vision-language-action-models

Ignoreblocked

Subject: EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models

Verdict

Ignore

Verdict is Ignore because current viability and proof state do not clear the buildability gate.

EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models

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