Fine-Tuning Small Reasoning Models for Quantum Field Theory explores This study fine-tunes small reasoning models for Quantum Field Theory using a novel data generation pipeline and publicly releases the data, pipeline, and reasoning traces.. Commercial viability score: 5/10 in LLM Fine-Tuning.
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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.
Page Freshness
Canonical route: /paper/fine-tuning-small-reasoning-models-for-quantum-field-theory
Page-specific freshness sourced from this paper's evidence receipt and score bundle.
Agent Handoff
Canonical ID fine-tuning-small-reasoning-models-for-quantum-field-theory | Route /paper/fine-tuning-small-reasoning-models-for-quantum-field-theory
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/fine-tuning-small-reasoning-models-for-quantum-field-theoryMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.18936"
}
}source_context
{
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"mode": "paper",
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"route": "/paper/fine-tuning-small-reasoning-models-for-quantum-field-theory",
"paper_ref": "fine-tuning-small-reasoning-models-for-quantum-field-theory",
"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 5.0
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