5 citations · 12 across the 7 of their papers we have counts for
7 papers
EgoOops: A Dataset for Mistake Action Detection from Egocentric Videos referring to Procedural Texts
Yuto Haneji, Taichi Nishimura, Hirotaka Kameko +7
Mistake action detection is crucial for developing intelligent archives that detect workers' errors and provide feedback. Existing studies have focused on visually apparent mistake…
BioVL-QR: Egocentric Biochemical Vision-and-Language Dataset Using Micro QR Codes
Tomohiro Nishimoto, Taichi Nishimura, Koki Yamamoto +11
This paper introduces BioVL-QR, a biochemical vision-and-language dataset comprising 23 egocentric experiment videos, corresponding protocols, and vision-and-language alignments. A…
Automatic Construction of a Large-Scale Corpus for Geoparsing Using Wikipedia Hyperlinks
Keyaki Ohno, Hirotaka Kameko, Keisuke Shirai +2
Geoparsing is the task of estimating the latitude and longitude (coordinates) of location expressions in texts. Geoparsing must deal with the ambiguity of the expressions that indi…
Vision-Language Interpreter for Robot Task Planning
Keisuke Shirai, Cristian C. Beltran-Hernandez, Masashi Hamaya +6
Large language models (LLMs) are accelerating the development of language-guided robot planners. Meanwhile, symbolic planners offer the advantage of interpretability. This paper pr…
Towards Flow Graph Prediction of Open-Domain Procedural Texts
Keisuke Shirai, Hirotaka Kameko, Shinsuke Mori
Machine comprehension of procedural texts is essential for reasoning about the steps and automating the procedures. However, this requires identifying entities within a text and re…
Visual Recipe Flow: A Dataset for Learning Visual State Changes of Objects with Recipe Flows
Keisuke Shirai, Atsushi Hashimoto, Taichi Nishimura +4
We present a new multimodal dataset called Visual Recipe Flow, which enables us to learn each cooking action result in a recipe text. The dataset consists of object state changes a…
Neural Text Generation with Artificial Negative Examples
Keisuke Shirai, Kazuma Hashimoto, Akiko Eriguchi +2
Neural text generation models conditioning on given input (e.g. machine translation and image captioning) are usually trained by maximum likelihood estimation of target text. Howev…