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Found 15 papers, 12 papers with code
MemSum-DQA: Adapting An Efficient Long Document Extractive Summarizer for Document Question Answering
We introduce MemSum-DQA, an efficient system for document question answering (DQA) that leverages MemSum, a long document extractive summarizer.
SciLit: A Platform for Joint Scientific Literature Discovery, Summarization and Citation Generation
We propose SciLit, a pipeline that automatically recommends relevant papers, extracts highlights, and suggests a reference sentence as a citation of a paper, taking into consideration the user-provided context and keywords.
Unsupervised Scientific Abstract Segmentation with Normalized Mutual Information
This implicit nature of conclusion positions makes the automatic segmentation of scientific abstracts into premises and conclusions a challenging task.
Balanced Deep CCA for Bird Vocalization Detection
The key objective of this work is to learn useful embeddings associated with high performance in downstream event detection tasks when labeled data is scarce and the audio events of interest (songbird vocalizations) are sparse.
Controllable Citation Sentence Generation with Language Models
Citation generation aims to generate a citation sentence that refers to a chosen paper in the context of a manuscript.
Local Citation Recommendation with Hierarchical-Attention Text Encoder and SciBERT-based Reranking
The goal of local citation recommendation is to recommend a missing reference from the local citation context and optionally also from the global context.
Ranked #1 on
Citation Recommendation
on FullTextPeerRead
MemSum: Extractive Summarization of Long Documents Using Multi-Step Episodic Markov Decision Processes
We introduce MemSum (Multi-step Episodic Markov decision process extractive SUMmarizer), a reinforcement-learning-based extractive summarizer enriched at each step with information on the current extraction history.
Ranked #1 on
Extractive Text Summarization
on GovReport
Embedding-based Scientific Literature Discovery in a Text Editor Application
Each claim in a research paper requires all relevant prior knowledge to be discovered, assimilated, and appropriately cited.
Character-Level Translation with Self-attention
We explore the suitability of self-attention models for character-level neural machine translation.
Estimation of Z-Thickness and XY-Anisotropy of Electron Microscopy Images using Gaussian Processes
Serial section electron microscopy (ssEM) is a widely used technique for obtaining volumetric information of biological tissues at nanometer scale.
Abstractive Document Summarization without Parallel Data
Abstractive summarization typically relies on large collections of paired articles and summaries.
Summary Refinement through Denoising
We propose a simple method for post-processing the outputs of a text summarization system in order to refine its overall quality.
Large-scale Hierarchical Alignment for Data-driven Text Rewriting
We propose a simple unsupervised method for extracting pseudo-parallel monolingual sentence pairs from comparable corpora representative of two different text styles, such as news articles and scientific papers.
Character-level Chinese-English Translation through ASCII Encoding
Character-level Neural Machine Translation (NMT) models have recently achieved impressive results on many language pairs.
Data-driven Summarization of Scientific Articles
Data-driven approaches to sequence-to-sequence modelling have been successfully applied to short text summarization of news articles.
