4 papers
Routing by Analogy: kNN-Augmented Expert Assignment for Mixture-of-Experts
Boxuan Lyu, Soichiro Murakami, Hidetaka Kamigaito +1
Mixture-of-Experts (MoE) architectures scale large language models efficiently by employing a parametric ``router'' to dispatch tokens to a sparse subset of experts. Typically, thi…
Distilling Many-Shot In-Context Learning into a Cheat Sheet
Ukyo Honda, Soichiro Murakami, Peinan Zhang
Recent advances in large language models (LLMs) enable effective in-context learning (ICL) with many-shot examples, but at the cost of high computational demand due to longer input…
AdParaphrase v2.0: Generating Attractive Ad Texts Using a Preference-Annotated Paraphrase Dataset
Soichiro Murakami, Peinan Zhang, Hidetaka Kamigaito +2
Identifying factors that make ad text attractive is essential for advertising success. This study proposes AdParaphrase v2.0, a dataset for ad text paraphrasing, containing human p…
AdParaphrase: Paraphrase Dataset for Analyzing Linguistic Features toward Generating Attractive Ad Texts
Soichiro Murakami, Peinan Zhang, Hidetaka Kamigaito +2
Effective linguistic choices that attract potential customers play crucial roles in advertising success. This study aims to explore the linguistic features of ad texts that influen…