6 papers · 1 filter
Argument Mining as a Text-to-Text Generation Task
Masayuki Kawarada, Tsutomu Hirao, Wataru Uchida +1
Argument Mining(AM) aims to uncover the argumentative structures within a text. Previous methods require several subtasks, such as span identification, component classification, an…
GAIN: A Benchmark for Goal-Aligned Decision-Making of Large Language Models under Imperfect Norms
Masayuki Kawarada, Kodai Watanabe, Soichiro Murakami
We introduce GAIN (Goal-Aligned Decision-Making under Imperfect Norms), a benchmark designed to evaluate how large language models (LLMs) balance adherence to norms against busines…
Multimodal Task Interference: A Benchmark and Analysis of History-Target Mismatch in Multimodal LLMs
Masayuki Kawarada, Tatsuya Ishigaki, Hiroya Takamura
Task interference, the performance degradation caused by task switches within a single conversation, has been studied exclusively in text-only settings despite the growing prevalen…
A Comparative Study of Demonstration Selection for Practical Large Language Models-based Next POI Prediction
Ryo Nishida, Masayuki Kawarada, Tatsuya Ishigaki +2
This paper investigates demonstration selection strategies for predicting a user's next point-of-interest (POI) using large language models (LLMs), aiming to accurately forecast a…
QCoder Benchmark: Bridging Language Generation and Quantum Hardware through Simulator-Based Feedback
Taku Mikuriya, Tatsuya Ishigaki, Masayuki Kawarada +9
Large language models (LLMs) have increasingly been applied to automatic programming code generation. This task can be viewed as a language generation task that bridges natural lan…
Prompting for Numerical Sequences: A Case Study on Market Comment Generation
Masayuki Kawarada, Tatsuya Ishigaki, Hiroya Takamura
Large language models (LLMs) have been applied to a wide range of data-to-text generation tasks, including tables, graphs, and time-series numerical data-to-text settings. While re…