pith:5QJC4YEW
SlideAgent: Hierarchical Agentic Framework for Multi-Page Visual Document Understanding
SARA hybrid RAG keeps some text passages and compresses the rest into vectors to raise answer quality under fixed token limits.
arxiv:2510.26615 v4 · 2025-10-30 · cs.CL
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Record completeness
Claims
SARA consistently improves answer relevance (+17.71), answer correctness (+13.72), and semantic similarity (+15.53) across 9 datasets and 5 open-source LLMs spanning 3 model families.
The assumption that semantic compression vectors remain interpretable enough to enable effective iterative evidence reranking while preserving the benefits of the retained text snippets, as described in the hybrid framework proposal.
SARA combines natural-language snippets with semantic compression vectors in RAG to improve answer relevance, correctness, and similarity on 9 datasets across 5 LLMs.
Formal links
Receipt and verification
| First computed | 2026-06-08T01:03:50.453245Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
ec122e6096dca6fab8824dc098051a92ee5fad6d902d73370199d21ad6041be8
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/5QJC4YEW3STPVOECJXAJQBI2SL \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: ec122e6096dca6fab8824dc098051a92ee5fad6d902d73370199d21ad6041be8
Canonical record JSON
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