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20212024
most citedTarget-dependent UNITER: A Transformer-Based Multimodal Language Comprehension Model for Domestic Service Robots

1 citations · 2 across the 3 of their papers we have counts for

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cs.RO2024

Co-Scale Cross-Attentional Transformer for Rearrangement Target Detection

Haruka Matsuo, Shintaro Ishikawa, Komei Sugiura

Rearranging objects (e.g. vase, door) back in their original positions is one of the most fundamental skills for domestic service robots (DSRs). In rearrangement tasks, it is cruci…

cs.RO20232 cited

Switching Head-Tail Funnel UNITER for Dual Referring Expression Comprehension with Fetch-and-Carry Tasks

Ryosuke Korekata, Motonari Kambara, Yu Yoshida +4

This paper describes a domestic service robot (DSR) that fetches everyday objects and carries them to specified destinations according to free-form natural language instructions. G…

cs.RO2023

Prototypical Contrastive Transfer Learning for Multimodal Language Understanding

Seitaro Otsuki, Shintaro Ishikawa, Komei Sugiura

Although domestic service robots are expected to assist individuals who require support, they cannot currently interact smoothly with people through natural language. For example,…

cs.RO20221 cited

Moment-based Adversarial Training for Embodied Language Comprehension

Shintaro Ishikawa, Komei Sugiura

In this paper, we focus on a vision-and-language task in which a robot is instructed to execute household tasks. Given an instruction such as "Rinse off a mug and place it in the c…

cs.RO20211 cited

Target-dependent UNITER: A Transformer-Based Multimodal Language Comprehension Model for Domestic Service Robots

Shintaro Ishikawa, Komei Sugiura

Currently, domestic service robots have an insufficient ability to interact naturally through language. This is because understanding human instructions is complicated by various a…