Distilling Answer-Set Programming Rules from LLMs for Neurosymbolic Visual Question Answering

Distilling Answer-Set Programming Rules from LLMs for Neurosymbolic Visual Question Answering | Signal Canvas | ScienceToStartup

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Canonical route: /signal-canvas/distilling-answer-set-programming-rules-from-llms-for-neurosymbolic-visual-question-answering

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Proof freshness: fresh
Proof status: partial
Display score: 5/10
Last proof check: 2026-06-03
Score updated: 2026-06-03
Score fresh until: 2026-07-03
References: 0
Source count: 4
Coverage: 83%

Page-specific freshness sourced from this paper's evidence receipt and score bundle.

Agent Handoff

Canonical ID distilling-answer-set-programming-rules-from-llms-for-neurosymbolic-visual-question-answering | Route /signal-canvas/distilling-answer-set-programming-rules-from-llms-for-neurosymbolic-visual-question-answering

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/distilling-answer-set-programming-rules-from-llms-for-neurosymbolic-visual-question-answering

MCP example

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    "query_text": "Summarize Distilling Answer-Set Programming Rules from LLMs for Neurosymbolic Visual Question Answering"
  }
}

source_context

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Evidence Receipt

Route status: building

Claims: 1

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: Distilling Answer-Set Programming Rules from LLMs for Neurosymbolic Visual Question Answering

PDF: https://arxiv.org/pdf/2606.03269v1

Repository: https://github.com/pudumagico/KDASP

Source count: 4

Coverage: 83%

Last proof check: 2026-06-03T20:32:59.802Z

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Subject: Distilling Answer-Set Programming Rules from LLMs for Neurosymbolic Visual Question Answering

Verdict

Distilling Answer-Set Programming Rules from LLMs for Neurosymbolic Visual Question Answering

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