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Found 7 papers, 4 papers with code
Monash-Summ@LongSumm 20 SciSummPip: An Unsupervised Scientific Paper Summarization Pipeline
The Scholarly Document Processing (SDP) workshop is to encourage more efforts on natural language understanding of scientific task.
Large Language Models for Scientific Synthesis, Inference and Explanation
We present a method for using general-purpose large language models to make inferences from scientific datasets of the form usually associated with special-purpose machine learning algorithms.
ChatRule: Mining Logical Rules with Large Language Models for Knowledge Graph Reasoning
Logical rules are essential for uncovering the logical connections between relations, which could improve reasoning performance and provide interpretable results on knowledge graphs (KGs).
How Far are We from Robust Long Abstractive Summarization?
For long document abstractive models, we show that the constant strive for state-of-the-art ROUGE results can lead us to generate more relevant summaries but not factual ones.
An Empirical Survey on Long Document Summarization: Datasets, Models and Metrics
The empirical analysis includes a study on the intrinsic characteristics of benchmark datasets, a multi-dimensional analysis of summarization models, and a review of the summarization evaluation metrics.
Leveraging Information Bottleneck for Scientific Document Summarization
This paper presents an unsupervised extractive approach to summarize scientific long documents based on the Information Bottleneck principle.
SciSummPip: An Unsupervised Scientific Paper Summarization Pipeline
The Scholarly Document Processing (SDP) workshop is to encourage more efforts on natural language understanding of scientific task.
