A Two-Stage LLM Framework for Accessible and Verified XAI Explanations
Compared to this week’s papers
Verification pending
Use This Via API or MCP
Use Signal Canvas as the narrative proof surface
Signal Canvas is the citation-first public layer for turning one paper into a structured commercialization narrative. Use it to hand off into REST, MCP, Build Loop, and launch-pack execution without losing source lineage.
Freshness
Signal Canvas proof surface
Canonical route: /signal-canvas/a-two-stage-llm-framework-for-accessible-and-verified-xai-explanations
- Observed
- 2026-04-15
- Fresh until
- 2026-04-29
- Coverage
- 50%
- Source count
- 3
- Stale after
- 2026-04-29
Verification is still converging across references, source coverage, and proof checks.
Proof Quality
One canonical proof ledger now drives the badge, counts, indexing, and commercialization gating.
- Last verified
- 2026-04-15
- References
- 0
- Sources
- 3
- Coverage
- 50%
Commercialization rails stay hidden until proof clears: proof_status, references_count.
Search indexing stays off until proof clears: proof_status, references_count.
Agent Handoff
A Two-Stage LLM Framework for Accessible and Verified XAI Explanations
Canonical ID a-two-stage-llm-framework-for-accessible-and-verified-xai-explanations | Route /signal-canvas/a-two-stage-llm-framework-for-accessible-and-verified-xai-explanations
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/a-two-stage-llm-framework-for-accessible-and-verified-xai-explanationsMCP example
{
"tool": "search_signal_canvas",
"arguments": {
"mode": "paper",
"paper_ref": "a-two-stage-llm-framework-for-accessible-and-verified-xai-explanations",
"query_text": "Summarize A Two-Stage LLM Framework for Accessible and Verified XAI Explanations"
}
}source_context
{
"surface": "signal_canvas",
"mode": "paper",
"query": "A Two-Stage LLM Framework for Accessible and Verified XAI Explanations",
"normalized_query": "2604.12543",
"route": "/signal-canvas/a-two-stage-llm-framework-for-accessible-and-verified-xai-explanations",
"paper_ref": "a-two-stage-llm-framework-for-accessible-and-verified-xai-explanations",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Evidence Receipt
Route status: buildingClaims: 0
References: Pending verification
Proof: Verification pending
Freshness state: computing
Source paper: A Two-Stage LLM Framework for Accessible and Verified XAI Explanations
PDF: https://arxiv.org/pdf/2604.12543v1
Source count: 3
Coverage: 50%
Last proof check: 2026-04-15T16:59:18.533Z
Paper Conversation
Citation-first answers with explicit evidence receipts, disagreement handling, commercialization framing, and next actions.
A Two-Stage LLM Framework for Accessible and Verified XAI Explanations
Canonical Paper Receipt
Last verification: 2026-04-15T16:59:18.533ZFreshness: fresh
Proof: unverified
Repo: missing
References: 0
Sources: 3
Coverage: 50%
- - repo_url
- - references
- - proof_status
- - proof verification has not been recorded yet
Preparing verified analysis
Dimensions overall score 7.0
GitHub Code Pulse
No public code linked for this paper yet.
Claim map
No public claim map is available for this paper yet.
Startup potential card
Related Resources
- explainable AI (XAI)(glossary)
- How can continual learning contribute to the development of explainable AI (XAI)?(question)
- How does LLM interpretability contribute to explainable AI (XAI) initiatives?(question)
- What is the role of explainable AI (XAI) in building trust for industrial AI applications?(question)
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