Search Results for author:
Found 11 papers, 4 papers with code
Automating Horizon Scanning in Future Studies
The contributions are: 1) we propose document retrieval and comment generation tasks for horizon scanning, 2) create and analyze a new dataset, and 3) report the performance of several models and show that comment generation tasks are challenging.
Generating Racing Game Commentary from Vision, Language, and Structured Data
In this study, we introduce a new large-scale dataset that contains aligned video data, structured numerical data, and transcribed commentaries that consist of 129, 226 utterances in 1, 389 races in a game.
Pretraining and Updating Language- and Domain-specific Large Language Model: A Case Study in Japanese Business Domain
This study explores the combination of a non-English language and a high-demand industry domain, focusing on a Japanese business-specific LLM.
Prompting for Numerical Sequences: A Case Study on Market Comment Generation
Large language models (LLMs) have been applied to a wide range of data-to-text generation tasks, including tables, graphs, and time-series numerical data-to-text settings.
Training Generative Question-Answering on Synthetic Data Obtained from an Instruct-tuned Model
This paper presents a simple and cost-effective method for synthesizing data to train question-answering systems.
Learning with Contrastive Examples for Data-to-Text Generation
Existing models for data-to-text tasks generate fluent but sometimes incorrect sentences e. g., {``}Nikkei gains{''} is generated when {``}Nikkei drops{''} is expected.
Controlling Contents in Data-to-Document Generation with Human-Designed Topic Labels
We propose a data-to-document generator that can easily control the contents of output texts based on a neural language model.
Discourse-Aware Hierarchical Attention Network for Extractive Single-Document Summarization
To incorporate the information of a discourse tree structure into the neural network-based summarizers, we propose a discourse-aware neural extractive summarizer which can explicitly take into account the discourse dependency tree structure of the source document.
Learning to Select, Track, and Generate for Data-to-Text
We propose a data-to-text generation model with two modules, one for tracking and the other for text generation.
Generating Market Comments Referring to External Resources
Comments on a stock market often include the reason or cause of changes in stock prices, such as {``}Nikkei turns lower as yen{'}s rise hits exporters.
