Search Results for author:
Found 7 papers, 4 papers with code
Unsupervised Neural Single-Document Summarization of Reviews via Learning Latent Discourse Structure and its Ranking
This paper focuses on the end-to-end abstractive summarization of a single product review without supervision.
SciReviewGen: A Large-scale Dataset for Automatic Literature Review Generation
Automatic literature review generation is one of the most challenging tasks in natural language processing.
Unsupervised Abstractive Opinion Summarization by Generating Sentences with Tree-Structured Topic Guidance
This paper presents a novel unsupervised abstractive summarization method for opinionated texts.
Differentiable Instruction Optimization for Cross-Task Generalization
Instruction tuning has been attracting much attention to achieve generalization ability across a wide variety of tasks.
Extractive Summarization Using Multi-Task Learning with Document Classification
The need for automatic document summarization that can be used for practical applications is increasing rapidly.
Tree-Structured Neural Topic Model
This paper presents a tree-structured neural topic model, which has a topic distribution over a tree with an infinite number of branches.
Unlearning Reveals the Influential Training Data of Language Models
This paper presents UnTrac, which estimates the influence of a training dataset by unlearning it from the trained model.
