Robust Explanations for User Trust in Enterprise NLP Systems explores A framework for evaluating the robustness of LLM explanations in black-box enterprise systems, enabling better user trust and compliance.. Commercial viability score: 7/10 in LLM Explainability.
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This route is the stable paper-level surface for citations, viability, references, and downstream handoffs. Use it as the proof layer behind Signal Canvas, workspace creation, and launch-pack generation.
Freshness
Canonical route: /paper/robust-explanations-for-user-trust-in-enterprise-nlp-systems
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Agent Handoff
Canonical ID robust-explanations-for-user-trust-in-enterprise-nlp-systems | Route /paper/robust-explanations-for-user-trust-in-enterprise-nlp-systems
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/robust-explanations-for-user-trust-in-enterprise-nlp-systemsMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.12069"
}
}source_context
{
"surface": "paper",
"mode": "paper",
"query": "Robust Explanations for User Trust in Enterprise NLP Systems",
"normalized_query": "2604.12069",
"route": "/paper/robust-explanations-for-user-trust-in-enterprise-nlp-systems",
"paper_ref": "robust-explanations-for-user-trust-in-enterprise-nlp-systems",
"topic_slug": null,
"benchmark_ref": null,
"dataset_ref": null
}Constellation, claims, and market context stay visible on the paper proof page even when commercialization rails are held back for incomplete proof receipts.
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Dimensions overall score 7.0
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