Taka Kato

2 papers indexed

arxivecon.EMcs.LGmath.STstat.MEstat.ML2026-07-20

Vector Search As Nearest Neighbor Matching: RAG-based Policy Learning in Causal Inference

We propose one-step and two-step methods for policy learning with retrieval-augmented generation (RAG). We formulate RAG-based action selection under the potential outcome framework. In the two-step method, vector search retrieves action-specific neighboring evidence in an embedd…

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arxivcs.SEcs.AIcs.LG2026-07-03

Which Algorithm Specification Formats Help Language Models Implement Machine Learning Algorithms?

Masahiro Kato, Taka Kato

Large language models (LLMs) are increasingly used to implement algorithms from research manuscripts, but papers often leave implementation choices implicit. This study examines how the written format of an algorithm specification affects first-pass LLM implementation accuracy. W…

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