https://bitbucket.org/tanya14109/cqasumm
공식 코드CQASUMM: Building References for Community Question Answering Summarization Corpora
Papers with Code 아카이브
Multi-Document Summarization
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Multi-Document Summarization is a process of representing a set of documents with a short piece of text by capturing the relevant information and filtering out the redundant information. Two prominent approaches to Multi-Document Summarization are extractive and abstractive summarization. Extractive summarization systems aim to extract salient snippets, sentences or passages from documents, while abstractive summarization systems aim to concisely paraphrase the content of the documents.
Source: Multi-Document Summarization using Distributed Bag-of-Words Model
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/Alex-Fabbri/Multi-News
공식 코드Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Model
https://github.com/DhavalTaunk08/XWikiGen
공식 코드XWikiGen: Cross-lingual Summarization for Encyclopedic Text Generation in Low Resource Languages
https://github.com/Diego999/GameWikiSum
공식 코드GameWikiSum: a Novel Large Multi-Document Summarization Dataset
https://github.com/HLTCHKUST/CAiRE-COVID
공식 코드https://github.com/LCS2-IIITD/summarization_bias
공식 코드Corpora Evaluation and System Bias Detection in Multi-document Summarization
https://github.com/PaddlePaddle/Research
공식 코드Leveraging Graph to Improve Abstractive Multi-Document Summarization
https://github.com/PortNLP/FairEXTSummarizer
공식 코드Fair Summarization: Bridging Quality and Diversity in Extractive Summaries
https://github.com/THU-KEG/TWAG
공식 코드https://github.com/THUNLP-MT/TRICE
공식 코드Transfer Learning for Sequence Generation: from Single-source to Multi-source
https://github.com/UKPLab/emnlp2017-cmapsum-corpus
공식 코드Bringing Structure into Summaries: Crowdsourcing a Benchmark Corpus of Concept Maps
https://github.com/YYF-Tommy/GlobeSumm
공식 코드https://github.com/Yale-LILY/SummerTime
공식 코드https://github.com/adithya7/hybrid-rag
공식 코드Estimating Optimal Context Length for Hybrid Retrieval-augmented Multi-document Summarization
https://github.com/adithya7/scaling-mds
공식 코드Scaling Multi-Document Event Summarization: Evaluating Compression vs. Full-Text Approaches
https://github.com/allenai/ms2
공식 코드https://github.com/allenai/mslr-annotated-dataset
공식 코드Automated Metrics for Medical Multi-Document Summarization Disagree with Human Evaluations
https://github.com/allenai/primer
공식 코드PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization
https://github.com/amazon-science/SumREN
공식 코드https://github.com/ariecattan/multi_mds
공식 코드https://github.com/c-juhwan/multi_news_plus
공식 코드Multi-News+: Cost-efficient Dataset Cleansing via LLM-based Data Annotation
https://github.com/c-rajan/Multi-source-NewsSummarization
공식 코드Shaping Political Discourse using multi-source News Summarization
https://github.com/chrishokamp/dynamic-transformer-ensembles
공식 코드DynE: Dynamic Ensemble Decoding for Multi-Document Summarization
https://github.com/cliveyn/pdsum
공식 코드PDSum: Prototype-driven Continuous Summarization of Evolving Multi-document Sets Stream
https://github.com/complementizer/wcep-mds-dataset
공식 코드A Large-Scale Multi-Document Summarization Dataset from the Wikipedia Current Events Portal
https://github.com/computationalmedia/supmmd
공식 코드SupMMD: A Sentence Importance Model for Extractive Summarization using Maximum Mean Discrepancy
https://github.com/congboma/disentanglesum
공식 코드Disentangling Specificity for Abstractive Multi-document Summarization
https://github.com/damo-nlp-sg/hierencdec
공식 코드A Hierarchical Encoding-Decoding Scheme for Abstractive Multi-document Summarization
https://github.com/danielabweiss/extending-sentence-fusion-resources
공식 코드Extending Multi-Text Sentence Fusion Resources via Pyramid Annotations
https://github.com/danielabweiss/qa-align
공식 코드QA-Align: Representing Cross-Text Content Overlap by Aligning Question-Answer Propositions
https://github.com/darsh10/Nutribullets
공식 코드Nutri-bullets: Summarizing Health Studies by Composing Segments
https://github.com/eranhirs/sentence_union_generation
공식 코드Revisiting Sentence Union Generation as a Testbed for Text Consolidation
https://github.com/florianbaud/retrieval-augmented-mds
공식 코드Non-Parametric Memory Guidance for Multi-Document Summarization
https://github.com/google-research-datasets/aquamuse
공식 코드AQuaMuSe: Automatically Generating Datasets for Query-Based Multi-Document Summarization
https://github.com/google-research/longt5
공식 코드LongT5: Efficient Text-To-Text Transformer for Long Sequences
https://github.com/homealim2012/QE_Mani_Summary
공식 코드Using Query Expansion in Manifold Ranking for Query-Oriented Multi-Document Summarization
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.