As a primary means of information acquisition, information retrieval (IR) systems, such as
search engines, have integrated themselves into our daily lives. These systems also serve …

As one of the most advanced techniques in AI, Retrieval-Augmented Generation (RAG) can
offer reliable and up-to-date external knowledge, providing huge convenience for numerous …

Language Models (LMs) memorize a vast amount of factual knowledge, exhibiting strong
performance across diverse tasks and domains. However, it has been observed that the …

Retrieval-enhanced machine learning (REML) refers to the use of information retrieval
methods to support reasoning and inference in machine learning tasks. Although relatively …

Retrieval-augmented generation has gained popularity as a framework to enhance large
language models with external knowledge. However, its effectiveness hinges on the …

Retrieval-Augmented Generation (RAG) has emerged as a key paradigm for enhancing
large language models (LLMs) by incorporating external knowledge. However, current RAG …

The tool-use ability of Large Language Models (LLMs) has a profound impact on a wide
range of industrial applications. However, LLMs' self-control and calibration capability in …

Large language models (LLMs), despite their impressive capabilities in natural language
understanding tasks in open-domain, often lack effectiveness with similar tasks in enterprise …

Megagon Labs では, これまで LLM の実応用における評価を中心に研究を進めてきた. 例えば,
指示テキストの曖昧性が出力に及ぼす影響 (Zhang et al. 2024; Niwa and Iso 2024) や …