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Naoki Kobayashi

7 accepted papers

2024

Video Discourse Parsing and Its Application to Multimodal Summarization: A Dataset and Baseline Approaches

EMNLP 2024finding

This paper tackles a new task: discourse parsing for videos, inspired by text discourse parsing based on Rhetorical Structure Theory (RST). The task aims to construct an RST tree for a video to represent its storyline and illustrate the event relationships. We first construct a benchmark dataset by…

2023

Dataset Distillation with Attention Labels for Fine-tuning BERT

ACL 2023short

Dataset distillation aims to create a small dataset of informative synthetic samples to rapidly train neural networks that retain the performance of the original dataset. In this paper, we focus on constructing distilled few-shot datasets for natural language processing (NLP) tasks to fine-tune pre-…

Cited by 20SourcePDFScholar
2022

A Simple and Strong Baseline for End-to-End Neural RST-style Discourse Parsing

EMNLP 2022finding

To promote and further develop RST-style discourse parsing models, we need a strong baseline that can be regarded as a reference for reporting reliable experimental results. This paper explores a strong baseline by integrating existing simple parsing strategies, top-down and bottom-up, with various…

2022

Integration of Variable-height and Hopping Strategies for Humanoid Push Recovery

IROS 2022poster

In this study, we present a framework to en-sure seamless transition in humanoid push recovery involving hopping strategy. We propose a method to adaptively change the time constant that integrated the ankle strategy and variable height strategy. This framework excites a hopping motion against a lar…

Cited by 2SourceScholar
2021

Considering Nested Tree Structure in Sentence Extractive Summarization with Pre-trained Transformer

EMNLP 2021main

Sentence extractive summarization shortens a document by selecting sentences for a summary while preserving its important contents. However, constructing a coherent and informative summary is difficult using a pre-trained BERT-based encoder since it is not explicitly trained for representing the inf…

2021

Improving Neural RST Parsing Model with Silver Agreement Subtrees

NAACL 2021long

Most of the previous Rhetorical Structure Theory (RST) parsing methods are based on supervised learning such as neural networks, that require an annotated corpus of sufficient size and quality. However, the RST Discourse Treebank (RST-DT), the benchmark corpus for RST parsing in English, is small du…