4 papers · 1 filter
R-WoM: Retrieval-augmented World Model For Computer-use Agents
Kai Mei, Jiang Guo, Shuaichen Chang +4
Large Language Models (LLMs) can serve as world models to enhance agent decision-making in digital environments by simulating future states and predicting action outcomes, potentia…
On Synthetic Data Strategies for Domain-Specific Generative Retrieval
Haoyang Wen, Jiang Guo, Yi Zhang +2
This paper investigates synthetic data generation strategies in developing generative retrieval models for domain-specific corpora, thereby addressing the scalability challenges in…
You Only Read Once (YORO): Learning to Internalize Database Knowledge for Text-to-SQL
Hideo Kobayashi, Wuwei Lan, Peng Shi +5
While significant progress has been made on the text-to-SQL task, recent solutions repeatedly encode the same database schema for every question, resulting in unnecessary high infe…
Towards a Holistic Evaluation of LLMs on Factual Knowledge Recall
Jiaqing Yuan, Lin Pan, Chung-Wei Hang +5
Large language models (LLMs) have shown remarkable performance on a variety of NLP tasks, and are being rapidly adopted in a wide range of use cases. It is therefore of vital impor…