Sentence Summarization
19 papers with code • 0 benchmarks • 0 datasets
Generating a summary of a given sentence.
Benchmarks
These leaderboards are used to track progress in Sentence Summarization
Latest papers with no code
Impossible Distillation: from Low-Quality Model to High-Quality Dataset & Model for Summarization and Paraphrasing
We present Impossible Distillation, a novel framework for paraphrasing and sentence summarization, that distills a high-quality dataset and model from a low-quality teacher that itself cannot perform these tasks.
Referee: Reference-Free Sentence Summarization with Sharper Controllability through Symbolic Knowledge Distillation
Moreover, we uniquely propose iterative distillation of knowledge, where student models from the previous iteration of distillation serve as teacher models in the next iteration.
IndicNLG Benchmark: Multilingual Datasets for Diverse NLG Tasks in Indic Languages
Natural Language Generation (NLG) for non-English languages is hampered by the scarcity of datasets in these languages.
Extract, Select and Rewrite: A New Modular Summarization Method
Prior works on supervised summarization are mainly based on end-to-end models, leading to low modularity, unfaithfulness and low interpretability.
Learning Non-Autoregressive Models from Search for Unsupervised Sentence Summarization
Text summarization aims to generate a short summary for an input text.
Bag-of-Vectors Autoencoders for Unsupervised Conditional Text Generation
We address this issue by extending their method to Bag-of-Vectors Autoencoders (BoV-AEs), which encode the text into a variable-size bag of vectors that grows with the size of the text, as in attention-based models.
ICAF: Iterative Contrastive Alignment Framework for Multimodal Abstractive Summarization
Integrating multimodal knowledge for abstractive summarization task is a work-in-progress research area, with present techniques inheriting fusion-then-generation paradigm.
Multimodal Sentence Summarization via Multimodal Selective Encoding
Thus, we propose a multimodal selective gate network that considers reciprocal relationships between textual and multi-level visual features, including global image descriptor, activation grids, and object proposals, to select highlights of the event when encoding the source sentence.
Multi-Image Summarization: Textual Summary from a Set of Cohesive Images
Multi-sentence summarization is a well studied problem in NLP, while generating image descriptions for a single image is a well studied problem in Computer Vision.
Quality of syntactic implication of RL-based sentence summarization
Work on summarization has explored both reinforcement learning (RL) optimization using ROUGE as a reward and syntax-aware models, such as models those input is enriched with part-of-speech (POS)-tags and dependency information.
