5 citations · 16 across the 16 of their papers we have counts for
6 papers · 1 filter
MaterialBENCH: Evaluating College-Level Materials Science Problem-Solving Abilities of Large Language Models
Michiko Yoshitake, Yuta Suzuki, Ryo Igarashi +2
A college-level benchmark dataset for large language models (LLMs) in the materials science field, MaterialBENCH, is constructed. This dataset consists of problem-answer pairs, bas…
COM Kitchens: An Unedited Overhead-view Video Dataset as a Vision-Language Benchmark
Koki Maeda, Tosho Hirasawa, Atsushi Hashimoto +4
Procedural video understanding is gaining attention in the vision and language community. Deep learning-based video analysis requires extensive data. Consequently, existing works o…
SciPostLayout: A Dataset for Layout Analysis and Layout Generation of Scientific Posters
Shohei Tanaka, Hao Wang, Yoshitaka Ushiku
Scientific posters are used to present the contributions of scientific papers effectively in a graphical format. However, creating a well-designed poster that efficiently summarize…
AdaCoder: Adaptive Prompt Compression for Programmatic Visual Question Answering
Mahiro Ukai, Shuhei Kurita, Atsushi Hashimoto +2
Visual question answering aims to provide responses to natural language questions given visual input. Recently, visual programmatic models (VPMs), which generate executable program…
Crystalformer: Infinitely Connected Attention for Periodic Structure Encoding
Tatsunori Taniai, Ryo Igarashi, Yuta Suzuki +4
Predicting physical properties of materials from their crystal structures is a fundamental problem in materials science. In peripheral areas such as the prediction of molecular pro…
TNF: Tri-branch Neural Fusion for Multimodal Medical Data Classification
Tong Zheng, Shusaku Sone, Yoshitaka Ushiku +2
This paper presents a Tri-branch Neural Fusion (TNF) approach designed for classifying multimodal medical images and tabular data. It also introduces two solutions to address the c…