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Research2026-08-09 · source-backed
Instead of feeding retrieved text to an LLM and hoping the reasoning holds, arXiv 2608.06292 synthesizes a Prolog module per chunk, generating predicates encoding Boolean claims that may depend on user-specific facts, then retrieves and composes them into queries using joint natural-language/code embeddings. A symbolic knowledge-gap detector identifies missing user facts whose truth value would change the outcome and automatically triggers a follow-up question. That's a real answer to the "agent guesses instead of asking" problem, and it's decidable rather than vibes-based. 61.1% versus 42.8% for a same-model RAG baseline, no domain-specific training, and every answer ships an execution trace linking each step to its source.
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Simon Willison released LLM / Shared entity: RAG / Same source domain / Shared topic / Earlier coverage
Linked by a graph relationship (Simon Willison released LLM); both cover RAG; reported by the same outlet (arxiv.org).
LLM uses OpenAI / Shared entities / Earlier coverage / Tension
Linked by a graph relationship (LLM uses OpenAI); both cover LLM, RAG; earlier LLM coverage from 2026-07-27.
Simon Willison released LLM / Shared entity: LLM / Shared topic / Earlier coverage
Linked by a graph relationship (Simon Willison released LLM); both cover LLM; overlapping topics (agent, code).
Simon Willison released LLM / Shared entity: LLM / Earlier coverage / Tension
Linked by a graph relationship (Simon Willison released LLM); both cover LLM; earlier LLM coverage from 2026-06-19.
Linked by a graph relationship (Simon Willison released LLM); both cover LLM; earlier LLM coverage from 2026-06-18.
LLM uses OpenAI / Same source domain / Shared topic
Linked by a graph relationship (LLM uses OpenAI); reported by the same outlet (arxiv.org); overlapping topics (agent, code).
Simon Willison released LLM / Same source domain / Shared topic
Linked by a graph relationship (Simon Willison released LLM); reported by the same outlet (arxiv.org); overlapping topics (agent, code).
LLM uses OpenAI / Shared entity: LLM / Earlier coverage
Linked by a graph relationship (LLM uses OpenAI); both cover LLM; earlier LLM coverage from 2026-07-31.