Tagged articles

Text Summarization

13 articles · Page 1 of 1

Dec 8, 2025 · Artificial Intelligence

A Complete Guide to the Top 3 NLP Models (Llama, ChatGLM, T5) with Hands‑On Deployment for Beginners

This article breaks down the core principles, architectures, and formulas of Llama, ChatGLM, and T5, compares their strengths and weaknesses, and provides a zero‑data, no‑VPN beginner project that trains and evaluates all three models on sentiment analysis and summarization, visualizes the results, and offers practical deployment tips.

ChatGLMLlamaNLP

0 likes · 24 min read

A Complete Guide to the Top 3 NLP Models (Llama, ChatGLM, T5) with Hands‑On Deployment for Beginners

DataFunSummit

Sep 23, 2022 · Artificial Intelligence

A Comprehensive Overview of Automatic Text Summarization: Methods, Datasets, Evaluation, and Future Directions

This article surveys automatic text summarization, detailing system classifications, extractive, abstractive and hybrid techniques, notable recent research, multi‑document and cross‑lingual challenges, major datasets, evaluation metrics, and promising future research avenues in the field.

NLPText Summarizationabstractive

0 likes · 21 min read

A Comprehensive Overview of Automatic Text Summarization: Methods, Datasets, Evaluation, and Future Directions

Laiye Technology Team

Sep 23, 2022 · Artificial Intelligence

Overview of Automatic Text Summarization: Methods, Datasets, and Future Directions

This article provides a comprehensive overview of automatic text summarization, covering extractive, abstractive, and hybrid methods, system classifications, applications, datasets, evaluation metrics, and future research directions within the field of artificial intelligence.

NLPText Summarizationabstractive

0 likes · 23 min read

Overview of Automatic Text Summarization: Methods, Datasets, and Future Directions

Alibaba Cloud Big Data AI Platform

Sep 21, 2022 · Artificial Intelligence

Unlocking PEGASUS: How EasyNLP Simplifies Text Summarization with Pre‑Training

This article explains the importance of text generation, introduces the PEGASUS model’s gap‑sentence pre‑training for abstractive summarization, and shows how the EasyNLP framework integrates PEGASUS and other Chinese and English summarization models with step‑by‑step installation, data preparation, and training commands.

EasyNLPNLPPEGASUS

0 likes · 22 min read

Unlocking PEGASUS: How EasyNLP Simplifies Text Summarization with Pre‑Training

360 Quality & Efficiency

Jun 10, 2022 · Artificial Intelligence

Overview of Modern Text Summarization Techniques

This article reviews contemporary text summarization methods, covering extractive approaches such as TextRank and clustering, abstractive models like Seq2Seq with attention, pointer‑generator networks, and recent pre‑trained transformers including BART, CPT and PEGASUS, highlighting their strengths, limitations, and combined strategies.

Text Summarizationabstractive modelsextractive methods

0 likes · 13 min read

Overview of Modern Text Summarization Techniques

Python Programming Learning Circle

Jan 12, 2022 · Artificial Intelligence

Building a Streamlit Web Application for NLP Tasks: Sentiment Analysis, Entity Extraction, and Text Summarization

This tutorial demonstrates how to create a lightweight Streamlit web app in Python that lets users select and run common NLP services—sentiment analysis, named‑entity recognition, and text summarization—by integrating libraries such as TextBlob, spaCy, and Gensim, with clear code examples and visual output.

PythonStreamlitText Summarization

0 likes · 13 min read

Building a Streamlit Web Application for NLP Tasks: Sentiment Analysis, Entity Extraction, and Text Summarization

JD Tech

Feb 2, 2021 · Artificial Intelligence

Advances and Trends in Multimodal Digital Content Generation and Automatic Text Summarization

The article reviews recent research on multimodal digital content generation and automatic text summarization, outlining the evolution from extractive to abstractive methods, highlighting four key technology trends such as pretrained language models, transformer dominance, knowledge‑enhanced generation, and multimodal‑knowledge joint modeling, and describing an industrial e‑commerce application built on these advances.

Generative ModelsKnowledge IntegrationText Summarization

0 likes · 12 min read

Advances and Trends in Multimodal Digital Content Generation and Automatic Text Summarization

DataFunTalk

Jun 10, 2019 · Artificial Intelligence

BERT Applications Across NLP Domains: Progress, Challenges, and Future Directions

This article surveys the rapid proliferation of BERT-based research over the past six months, analyzing its impact on various NLP tasks such as question answering, information retrieval, dialog systems, summarization, data augmentation, classification, and sequence labeling, while also discussing the model's strengths, limitations, and future research opportunities.

BERTData AugmentationNLP

0 likes · 52 min read

BERT Applications Across NLP Domains: Progress, Challenges, and Future Directions

Alibaba Cloud Developer

Jan 15, 2019 · Artificial Intelligence

How Alibaba Engineers Boost SEO with Reinforcement Learning and Attention Models

This article details Alibaba.com engineers' application of reinforcement learning, attention mechanisms, and weakly supervised techniques to extract product summaries, improve content quality, and significantly raise SEO rankings, supported by offline experiments, online A/B testing, and future research directions.

AlibabaSEOText Summarization

0 likes · 16 min read

How Alibaba Engineers Boost SEO with Reinforcement Learning and Attention Models

Alibaba Cloud Developer

Dec 26, 2018 · Artificial Intelligence

Can AI Generate Perfect Short Product Titles? A Multi-Source Pointer Network Approach

This article investigates the challenge of generating concise e‑commerce product short titles by formalizing it as a constrained text‑summarization task, proposes a Multi‑Source Pointer Network that leverages both title and background knowledge encoders, and demonstrates its superiority through extensive offline and online experiments.

Text Summarizatione-commerceextractive summarization

0 likes · 17 min read

Can AI Generate Perfect Short Product Titles? A Multi-Source Pointer Network Approach

Alibaba Cloud Developer

Nov 30, 2018 · Artificial Intelligence

How Multi‑Source Pointer Networks Transform E‑Commerce Product Title Generation

This article presents a multi‑source pointer network approach for generating concise, brand‑preserving product short titles in e‑commerce, detailing problem formalization, model architecture, extensive offline and online experiments, and demonstrating significant improvements over traditional truncation and seq2seq baselines.

Text Summarizationdeep learninge-commerce

0 likes · 16 min read

How Multi‑Source Pointer Networks Transform E‑Commerce Product Title Generation

Alibaba Cloud Developer

Aug 17, 2018 · Artificial Intelligence

Can Multi‑Task Learning Shorten E‑Commerce Titles Without Losing Sales?

This paper proposes a multi‑task learning approach that compresses overly long e‑commerce product titles into concise short titles using a Pointer Network, while simultaneously generating user search queries with an attention‑based encoder‑decoder, achieving higher readability, informativeness, and conversion rates than traditional methods.

Attention MechanismSequence-to-SequenceText Summarization

0 likes · 11 min read

Can Multi‑Task Learning Shorten E‑Commerce Titles Without Losing Sales?

GF Securities FinTech

Sep 7, 2016 · Artificial Intelligence

How Google’s Open‑Source TensorFlow Model Generates Accurate Summaries for Long Texts

Google Brain’s open‑source TensorFlow model tackles long‑text summarization by extracting key information and generating concise headlines, demonstrating state‑of‑the‑art extractive and abstractive techniques, with released code, hyper‑parameter details, and examples that illustrate its performance on news articles.

TensorFlowText Summarizationabstractive summarization

0 likes · 6 min read

How Google’s Open‑Source TensorFlow Model Generates Accurate Summaries for Long Texts