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From Parameters to Answers: How LLMs Retrieve and Use Their Internal Knowledge

arxiv.org/abs/2609.11859

quality89

Updated 2 h ago · first seen 12 Sept 2026

paper_01M29X34QKRM8DWNKMSBZ94SEJ

Published
12 Sept 2026
T1 · 2 h ago
arXiv
2609.11859
T1 · 2 h ago
Category
cs.AI
T1 · 2 h ago

Abstract

How does a language model's dependence on query-routing information and target knowledge change as it answers a question? We study this question through layerwise interventions on the hidden state at the end of the question. Across Qwen, Llama, and Gemma, we compare country-continent questions with noun, adjective, and code answers while keeping several fitted measurements distinct. A pair-conditioned request direction describes which country is queried in natural single-country questions; a global request direction describes first- versus second-country requests in paired questions; separate selection candidates test control among contents already available in the hidden state. A diagnostic reanalysis of frozen Qwen natural-question states shows that the pair-conditioned direction grows stronger before interventions on it begin to alter later fitted knowledge, with this causal window opening while answer-supporting content is still forming. The paired three-model trajectories are not uniform: Gemma shows a partially overlapping mid-layer routing-content profile, whereas Llama has no sustained routing-effect window under the same gates. In the paired protocol, dependence on the global request direction decreases from fixed earlier to later layer sets while dependence on fitted content persists. A matched Qwen comparison shows that the pair-conditioned direction retains a late effect, so this operational handoff concerns the global fitted direction rather than all request information. These results separate early readability, natural strength, causal steering, and later content dependence.

Authors 5

Hong Cheng, Renhe Jiang, Wenkang Wei, Xingtong Yu, Yuan Fang

Specification

Official page

Source:arXiv (Atom API + RSS)T1observed 2 h agohigh

Arxiv announce type
new

Source:arXiv (Atom API + RSS)T1observed 2 h agohigh

arXiv id
2609.11859

Source:arXiv (Atom API + RSS)T1observed 2 h agohigh

Categories
cs.AI

Source:arXiv (Atom API + RSS)T1observed 2 h agohigh

PDF

Source:arXiv (Atom API + RSS)T1observed 2 h agohigh

Primary category
cs.AI

Source:arXiv (Atom API + RSS)T1observed 2 h agohigh

Published
12 Sept 2026

Source:arXiv (Atom API + RSS)T1observed 2 h agohigh

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Provenance

Attributed facts

9

Source tiers

T19

Freshest observation

2 h ago

Conflicts

None