https://github.com/jiangycTarheel/TPT-Summ
공식 코드Enriching Transformers with Structured Tensor-Product Representations for Abstractive Summarization
Papers with Code 아카이브
Text Summarization
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 12
- 평가표
- 37
- 보존된 평가 기록
- 233
Text Summarization is a natural language processing (NLP) task that involves condensing a lengthy text document into a shorter, more compact version while still retaining the most important information and meaning. The goal is to produce a summary that accurately represents the content of the original text in a concise form.
There are different approaches to text summarization, including extractive methods that identify and extract important sentences or phrases from the text, and abstractive methods that generate new text based on the content of the original text.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/jiaqisjtu/faitheval-fflm
공식 코드Zero-shot Faithfulness Evaluation for Text Summarization with Foundation Language Model
https://github.com/jingqiangchen/kbsumm
공식 코드An entity-guided text summarization framework with relational heterogeneous graph neural network
https://github.com/jingyng/label-adaptive-self-rationalization
공식 코드Take It Easy: Label-Adaptive Self-Rationalization for Fact Verification and Explanation Generation
https://github.com/jinpeng01/wgsum
공식 코드https://github.com/johpro/elske
공식 코드https://github.com/jonas-becker/text-generation
공식 코드Text Generation: A Systematic Literature Review of Tasks, Evaluation, and Challenges
https://github.com/jordiclive/ControlPrefixes
공식 코드https://github.com/joshbambrick/falsesum
공식 코드https://github.com/jpeper/pelms
공식 코드PELMS: Pre-training for Effective Low-Shot Multi-Document Summarization
https://github.com/julmaxi/summary_bias
공식 코드https://github.com/julmaxi/summary_lq_analysis
공식 코드https://github.com/jungokasai/beam_with_patience
공식 코드A Call for Clarity in Beam Search: How It Works and When It Stops
https://github.com/junpliu/condigsum
공식 코드Topic-Aware Contrastive Learning for Abstractive Dialogue Summarization
https://github.com/junqizhao888/buzz-llm
공식 코드BUZZ: Beehive-structured Sparse KV Cache with Segmented Heavy Hitters for Efficient LLM Inference
https://github.com/jxhe/self-training-text-generation
공식 코드https://github.com/jxhe/unify-parameter-efficient-tuning
공식 코드Towards a Unified View of Parameter-Efficient Transfer Learning
https://github.com/jylins/videoxum
공식 코드VideoXum: Cross-modal Visual and Textural Summarization of Videos
https://github.com/jzhou316/Unsupervised-Sentence-Summarization
공식 코드https://github.com/kakaobrain/stg
공식 코드Selective Token Generation for Few-shot Natural Language Generation
https://github.com/kamigaito/SLAHAN
공식 코드Syntactically Look-Ahead Attention Network for Sentence Compression
https://github.com/kata-ai/indosum
공식 코드IndoSum: A New Benchmark Dataset for Indonesian Text Summarization
https://github.com/katsumiok/askit-artifact
공식 코드AskIt: Unified Programming Interface for Programming with Large Language Models
https://github.com/katsumiok/pyaskit
공식 코드AskIt: Unified Programming Interface for Programming with Large Language Models
https://github.com/katsumiok/ts-askit
공식 코드AskIt: Unified Programming Interface for Programming with Large Language Models
https://github.com/kaushal0494/ZmBART
공식 코드ZmBART: An Unsupervised Cross-lingual Transfer Framework for Language Generation
https://github.com/kaushal0494/meta_xnlg
공식 코드https://github.com/kenchan0226/abs-then-ext-public
공식 코드https://github.com/kenchan0226/control-sum-cmdp
공식 코드Controllable Summarization with Constrained Markov Decision Process
https://github.com/kenchan0226/finegrainedfact
공식 코드Interpretable Automatic Fine-grained Inconsistency Detection in Text Summarization
https://github.com/kepei1106/decompeval
공식 코드DecompEval: Evaluating Generated Texts as Unsupervised Decomposed Question Answering
https://github.com/kepingbi/ARedSumSentRank
공식 코드AREDSUM: Adaptive Redundancy-Aware Iterative Sentence Ranking for Extractive Document Summarization
https://github.com/khloud-al/arnli
공식 코드ArNLI: Arabic Natural Language Inference for Entailment and Contradiction Detection
https://github.com/kiyukuta/lencon
공식 코드https://github.com/knot-fit-but/oapapers
공식 코드https://github.com/knot-fit-but/oapapersviewer
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.