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LLMs Interpret, Embeddings Organize, Graphs Emerge: Agent-Driven Compilation of Scientific Knowledge

Paper recorded by Signals 4 on 2026-08-30 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-08-30 on arXiv · recorded by Signals 4 on 2026-09-01

Category: cs.AI · 人工智能 · first seen 2026-09-01

Abstract

Sustained scientific work requires a knowledge substrate that carries interpretation across tasks and preserves paths to source evidence. We call this process \emph{scientific knowledge compilation} and implement it in ASKS, the \emph{Agent-Driven Scientific Knowledge System}. For each source, an LLM produces a readable Wiki view and machine-facing semantics. Deterministic checks convert the latte

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#269 most recent of 300 cs.AI papers we have recorded · ↑ newer: Forward-Deployed Full-Stack Engineering for Autonomous Cloud MLOps · ↓ older: Wide Learning: Learning to Reach Evidence
Cite this page: LLMs Interpret, Embeddings Organize, Graphs Emerge: Agent-Driven Compilation of Scientific Knowledge: the #269 most recent of 300 cs.AI papers we have recorded (as of 2026-08-30). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/llms-interpret-embeddings-organize-graphs-emerge-agent-driven-compilation-of-sci.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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