Towards Effective In-context Cross-domain Knowledge Transfer via Domain-invariant-neurons-based Retrieval explores A retrieval method that boosts LLM reasoning by finding structurally compatible cross-domain demonstrations using domain-invariant neurons.. Commercial viability score: 7/10 in LLM Reasoning.
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Canonical route: /paper/towards-effective-in-context-cross-domain-knowledge-transfer-via-domain-invariant-neurons-based-retrieval
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Agent Handoff
Canonical ID towards-effective-in-context-cross-domain-knowledge-transfer-via-domain-invariant-neurons-based-retrieval | Route /paper/towards-effective-in-context-cross-domain-knowledge-transfer-via-domain-invariant-neurons-based-retrieval
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/towards-effective-in-context-cross-domain-knowledge-transfer-via-domain-invariant-neurons-based-retrievalMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.05383"
}
}source_context
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"query": "Towards Effective In-context Cross-domain Knowledge Transfer via Domain-invariant-neurons-based Retrieval",
"normalized_query": "2604.05383",
"route": "/paper/towards-effective-in-context-cross-domain-knowledge-transfer-via-domain-invariant-neurons-based-retrieval",
"paper_ref": "towards-effective-in-context-cross-domain-knowledge-transfer-via-domain-invariant-neurons-based-retrieval",
"topic_slug": null,
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}Paper proof page receipt window
/buildability/towards-effective-in-context-cross-domain-knowledge-transfer-via-domain-invariant-neurons-based-retrieval
Subject: Towards Effective In-context Cross-domain Knowledge Transfer via Domain-invariant-neurons-based Retrieval
Verdict
Build Now
Verdict is Build Now because viability and implementation proof cleared the Wave 1 scaffold thresholds.
Time to first demo
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Receipt path
/buildability/towards-effective-in-context-cross-domain-knowledge-transfer-via-domain-invariant-neurons-based-retrieval
Paper ref
towards-effective-in-context-cross-domain-knowledge-transfer-via-domain-invariant-neurons-based-retrieval
arXiv id
2604.05383
Generated at
2026-04-08T03:22:09.832Z
Evidence freshness
fresh
Last verification
2026-04-08T03:22:09.832Z
Sources
0
References
0
Coverage
0%
Lineage hash
c9fcd7c2ed515fc4ee14e7eafa359eeb86ad365784c89991230322c2e18a4e34
Canonical opportunity-kernel lineage hash.
External signature
unsigned_external
No founder, registry, pilot, or production-adoption signature is attached to this receipt.
Verification
not_verified
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Verification pending / evidence receipt incomplete
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Dimensions overall score 7.0
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This equation captures one of the core mathematical components of the system. rmally, each training instance is linearized into an input sequence x = (x1, . . . , x|x|) and an output sequence y = (y
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This equation captures one of the core mathematical components of the system. PS(x) ̸= PT (x) while the underlying prediction function f : X → Y is assumed
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This equation captures one of the core mathematical components of the system. (x, y) ∈X × Y. Their input distributions differ
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