6 citations · 6 across the 7 of their papers we have counts for
8 papers
TAMA: Tool-Augmented Multimodal Agent for Procedural Activity Understanding
Kimihiro Hasegawa, Wiradee Imrattanatrai, Masaki Asada +2
Procedural activity assistants potentially support humans in a variety of settings, from our daily lives, e.g., cooking or assembling flat-pack furniture, to professional situation…
ProMQA-Assembly: Multimodal Procedural QA Dataset on Assembly
Kimihiro Hasegawa, Wiradee Imrattanatrai, Masaki Asada +5
Assistants on assembly tasks show great potential to benefit humans ranging from helping with everyday tasks to interacting in industrial settings. However, evaluation resources in…
A Video-grounded Dialogue Dataset and Metric for Event-driven Activities
Wiradee Imrattanatrai, Masaki Asada, Kimihiro Hasegawa +3
This paper presents VDAct, a dataset for a Video-grounded Dialogue on Event-driven Activities, alongside VDEval, a session-based context evaluation metric specially designed for th…
ProMQA: Question Answering Dataset for Multimodal Procedural Activity Understanding
Kimihiro Hasegawa, Wiradee Imrattanatrai, Zhi-Qi Cheng +5
Multimodal systems have great potential to assist humans in procedural activities, where people follow instructions to achieve their goals. Despite diverse application scenarios, s…
ColBERT Retrieval and Ensemble Response Scoring for Language Model Question Answering
Alex Gichamba, Tewodros Kederalah Idris, Brian Ebiyau +2
Domain-specific question answering remains challenging for language models, given the deep technical knowledge required to answer questions correctly. This difficulty is amplified…
Human-Aware Vision-and-Language Navigation: Bridging Simulation to Reality with Dynamic Human Interactions
Heng Li, Minghan Li, Zhi-Qi Cheng +6
Vision-and-Language Navigation (VLN) aims to develop embodied agents that navigate based on human instructions. However, current VLN frameworks often rely on static environments an…
Formulation Comparison for Timeline Construction using LLMs
Kimihiro Hasegawa, Nikhil Kandukuri, Susan Holm +2
Constructing a timeline requires identifying the chronological order of events in an article. In prior timeline construction datasets, temporal orders are typically annotated by ei…
Towards Artwork Explanation in Large-scale Vision Language Models
Kazuki Hayashi, Yusuke Sakai, Hidetaka Kamigaito +2
Large-scale Vision-Language Models (LVLMs) output text from images and instructions, demonstrating capabilities in text generation and comprehension. However, it has not been clari…