https://github.com/cjaep/MPO
공식 코드Model-based Preference Optimization in Abstractive Summarization without Human Feedback
Papers with Code 아카이브
Abstractive Text Summarization
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- 하위 태스크
- 3
- 평가표
- 20
- 보존된 평가 기록
- 98
Abstractive Text Summarization is the task of generating a short and concise summary that captures the salient ideas of the source text. The generated summaries potentially contain new phrases and sentences that may not appear in the source text.
Source: Generative Adversarial Network for Abstractive Text Summarization
Image credit: Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/clovaai/FocusSeq2Seq
공식 코드https://github.com/crisisltlsum/crisistimelines
공식 코드CrisisLTLSum: A Benchmark for Local Crisis Event Timeline Extraction and Summarization
https://github.com/csebuetnlp/crosssum
공식 코드CrossSum: Beyond English-Centric Cross-Lingual Summarization for 1,500+ Language Pairs
https://github.com/csebuetnlp/xl-sum
공식 코드XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages
https://github.com/damo-nlp-sg/llm_summeval
공식 코드Large Language Models are Not Yet Human-Level Evaluators for Abstractive Summarization
https://github.com/data-lang/text-summarization-sota-experiment
공식 코드Survey on Abstractive Text Summarization: Dataset, Models, and Metrics
https://github.com/dengyang17/msg
공식 코드https://github.com/dennlinger/summaries
공식 코드https://github.com/dfki-nlp/smv
공식 코드https://github.com/didi/delta
공식 코드https://github.com/dmhyun/msrp
공식 코드https://github.com/dorinapetra/summarization
공식 코드HunSum-1: an Abstractive Summarization Dataset for Hungarian
https://github.com/dropreg/R-Drop
공식 코드https://github.com/engsalem/arglegalsumm
공식 코드ArgLegalSumm: Improving Abstractive Summarization of Legal Documents with Argument Mining
https://github.com/engsalem/legalsummreranking
공식 코드Towards Argument-Aware Abstractive Summarization of Long Legal Opinions with Summary Reranking
https://github.com/esdurmus/Wikilingua
공식 코드WikiLingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarization
https://github.com/esdurmus/summary-faithfulness
공식 코드https://github.com/fahmidahossain/Report_Summarization
공식 코드CSTRL: Context-Driven Sequential Transfer Learning for Abstractive Radiology Report Summarization
https://github.com/fajri91/RSTExtractor
공식 코드https://github.com/fajri91/sum_liputan6
공식 코드Liputan6: A Large-scale Indonesian Dataset for Text Summarization
https://github.com/fkirste/gem_emnlp2022-toasts
공식 코드Analyzing Multi-Task Learning for Abstractive Text Summarization
https://github.com/fladhak/effective-faithfulness
공식 코드https://github.com/flbbb/locost-summarization
공식 코드LOCOST: State-Space Models for Long Document Abstractive Summarization
https://github.com/forrestbao/suenes
공식 코드https://github.com/ghchen18/acl22-sixtp
공식 코드Towards Making the Most of Multilingual Pretraining for Zero-Shot Neural Machine Translation
https://github.com/giganttheo/importance-based-relevance-score
공식 코드https://github.com/gonced8/document-summarization
공식 코드https://github.com/google-research-datasets/xsum_hallucination_annotations
공식 코드https://github.com/google-research/google-research
공식 코드SummAE: Zero-Shot Abstractive Text Summarization using Length-Agnostic Auto-Encoders
https://github.com/google-research/lasertagger
공식 코드https://github.com/google-research/longt5
공식 코드LongT5: Efficient Text-To-Text Transformer for Long Sequences
https://github.com/google-research/pegasus
공식 코드PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization
https://github.com/gospelnnadi/text-summarization-sota-experiment
공식 코드Survey on Abstractive Text Summarization: Dataset, Models, and Metrics
https://github.com/gsh199449/proto-summ
공식 코드https://github.com/guokan-shang/ami-and-icsi-corpora
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.