Advances in Text Summarization: Pointer-Generator, Coverage Mechanisms, Entity Knowledge Integration, and Non-Autoregressive Models

This article reviews recent advances in abstractive summarization, covering pointer‑generator networks with coverage loss, integration of entity knowledge, strategies to mitigate repetition such as unlikelihood training and nucleus sampling, and emerging non‑autoregressive approaches like the Levenshtein Transformer.

NLPPointer-Generatorcoverage

0 likes · 15 min read

Advances in Text Summarization: Pointer-Generator, Coverage Mechanisms, Entity Knowledge Integration, and Non-Autoregressive Models

58 Tech

Mar 5, 2021 · Artificial Intelligence

Intelligent Job Title Generation with Pipeline and Seq2Seq Approaches

This article presents a comprehensive study on generating recruitment job titles by combining a rule‑based pipeline with advanced seq2seq models—including BiLSTM‑Attention, Pointer‑Generator, and a Field‑Gate Dual‑Attention architecture—demonstrating significant performance gains on real‑world hiring data.

NLPPipelinePointer-Generator

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Intelligent Job Title Generation with Pipeline and Seq2Seq Approaches

Alibaba Cloud Developer

Aug 22, 2018 · Artificial Intelligence

How Smart Copy Generation Boosts 1688 B2B Sales: From Seq2Seq to Coverage Attention

This article analyzes the challenges of generating product copy for the 1688 B2B platform, proposes enhancements to attention‑based Seq2Seq and Pointer‑Generator models—including TextCNN classification, convolutional inputs, coverage attention, and beam‑search constraints—and demonstrates significant gains in accuracy, diversity, and reduced repetition through extensive experiments.

Copy GenerationCoverage AttentionNLG

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How Smart Copy Generation Boosts 1688 B2B Sales: From Seq2Seq to Coverage Attention