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arXiv:cs.AI· Chaemin Jang, Jihee Kim, Dongman Lee·· 5 小时前AI 评分40

学到一个事实不等于学会如何检索它:请求形式与上下文状态如何影响事实检索

Learning a Fact Is Not Learning How to Retrieve It

AI 导读

一项 arXiv 研究通过两阶段训练分离"学习事实"与"检索事实":第一阶段让一个模型以五种请求形式接触事实、另一个仅以陈述句形式接触,第二阶段两者用相同的新事实陈述句训练。结果两者从陈述句中检索新事实的表现几乎相同,但在其他请求形式上差异显著。研究进一步发现,答案前的上下文状态可决定已学事实能否被检索,且该效应可跨事实与事实关系迁移。

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Abstract:A model trained on "The capital of X is Y" may produce "Y" after "The capital of X is" but fail after "The capital of X:". We call these different ways of eliciting the same fact request forms. To separate learning a fact from retrieving it, we train two models in two stages. In the first stage (request-form training), one model sees each fact in five forms and the other sees the same facts only as statements. In the second stage (target-fact training), both receive identical training on new facts, all as statements. Both then retrieve the new facts almost equally well from statements, but differ sharply on other request forms. Thus, a model can learn how to retrieve through a request form before it learns the facts. To understand this difference, we examine the hidden state immediately before the answer, which we call the context state. When given two different request forms for the same fact, the model trained on five forms in stage one produces more similar context states than the model trained on statements alone in that stage. Changing this state at retrieval time can enable or prevent retrieval of an already learned fact, and the same effect transfers across facts and factual relations, such as capitals and currencies. To test its role during learning, we change the context state only during target-fact training. This intervention changes later retrieval without intervention at test time. Together, these results show that later retrieval depends on earlier request-form experience and the context state during fact learning.
Subjects: Artificial Intelligence (cs.AI)
Cite as: arXiv:2610.03251 [cs.AI]
  (or arXiv:2610.03251v1 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.2610.03251

arXiv-issued DOI via DataCite (pending registration)

Submission history

From: Chaemin Jang [view email]
[v1] Fri, 2 Oct 2026 12:59:19 UTC (1,221 KB)

来源:arXiv:cs.AI · arxiv.org