Training Transformers in Cosine Coefficient Space explores A novel method for training transformers by parameterizing weights in cosine coefficient space, reducing parameter count while maintaining performance.. Commercial viability score: 3/10 in LLM Training.
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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/training-transformers-in-cosine-coefficient-space
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Agent Handoff
Canonical ID training-transformers-in-cosine-coefficient-space | Route /paper/training-transformers-in-cosine-coefficient-space
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/training-transformers-in-cosine-coefficient-spaceMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.04440"
}
}source_context
{
"surface": "paper",
"mode": "paper",
"query": "Training Transformers in Cosine Coefficient Space",
"normalized_query": "2604.04440",
"route": "/paper/training-transformers-in-cosine-coefficient-space",
"paper_ref": "training-transformers-in-cosine-coefficient-space",
"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 3.0
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