Modular Representation Compression: Adapting LLMs for Efficient and Effective Recommendations explores MARC is a novel framework that compresses LLM representations for recommendation systems by controlling modularity, achieving significant online A/B test lift.. Commercial viability score: 7/10 in Recommendation Systems.
Use This Via API or MCP
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/modular-representation-compression-adapting-llms-for-efficient-and-effective-recommendations
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.
Commercialization rails stay hidden until proof clears: proof_status, references_count.
Search indexing stays off until proof clears: proof_status, references_count.
Agent Handoff
Canonical ID modular-representation-compression-adapting-llms-for-efficient-and-effective-recommendations | Route /paper/modular-representation-compression-adapting-llms-for-efficient-and-effective-recommendations
REST example
curl https://sciencetostartup.com/api/v1/agent-handoff/paper/modular-representation-compression-adapting-llms-for-efficient-and-effective-recommendationsMCP example
{
"tool": "get_paper",
"arguments": {
"arxiv_id": "2604.18146"
}
}source_context
{
"surface": "paper",
"mode": "paper",
"query": "Modular Representation Compression: Adapting LLMs for Efficient and Effective Recommendations",
"normalized_query": "2604.18146",
"route": "/paper/modular-representation-compression-adapting-llms-for-efficient-and-effective-recommendations",
"paper_ref": "modular-representation-compression-adapting-llms-for-efficient-and-effective-recommendations",
"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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