https://github.com/milanlproc/language-invariant-properties
공식 코드Language Invariant Properties in Natural Language Processing
Papers with Code 아카이브
Paraphrase Generation
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Paraphrase Generation involves transforming a natural language sentence to a new sentence, that has the same semantic meaning but a different syntactic or lexical surface form.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/mingdachen/mVGVAE
공식 코드Exemplar-Controllable Paraphrasing and Translation using Bitext
https://github.com/monisha-jega/paraphrasing_embedding_outputs
공식 코드Improving the Diversity of Unsupervised Paraphrasing with Embedding Outputs
https://github.com/ngwgsang/visp
공식 코드https://github.com/nil-zhuang/ld4pg
공식 코드Improved Paraphrase Generation via Controllable Latent Diffusion
https://github.com/njunlp/knn-box
공식 코드kNN-BOX: A Unified Framework for Nearest Neighbor Generation
https://github.com/qijimrc/robustoie
공식 코드Syntactically Robust Training on Partially-Observed Data for Open Information Extraction
https://github.com/sf-wa-326/phrase-bert-topic-model
공식 코드Phrase-BERT: Improved Phrase Embeddings from BERT with an Application to Corpus Exploration
https://github.com/shadowkiller33/parascore
공식 코드https://github.com/sharif-slpl/se-2024-task-06-shroom
공식 코드SLPL SHROOM at SemEval2024 Task 06: A comprehensive study on models ability to detect hallucination
https://github.com/shininglab/action-controlled-paraphrasing
공식 코드https://github.com/shirawein/amr-translationese
공식 코드Lost in Translationese? Reducing Translation Effect Using Abstract Meaning Representation
https://github.com/skp1999/SMAB
공식 코드https://github.com/tagoyal/sow-reap-paraphrasing
공식 코드Neural Syntactic Preordering for Controlled Paraphrase Generation
https://github.com/thompsonb/prism
공식 코드https://github.com/tomhosking/hrq-vae
공식 코드https://github.com/tomhosking/separator
공식 코드Factorising Meaning and Form for Intent-Preserving Paraphrasing
https://github.com/uclanlp/paraamr
공식 코드ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation
https://github.com/uclanlp/pip
공식 코드PIP: Parse-Instructed Prefix for Syntactically Controlled Paraphrase Generation
https://github.com/uclanlp/synpg
공식 코드Generating Syntactically Controlled Paraphrases without Using Annotated Parallel Pairs
https://github.com/uhh-lt/par4Acad
공식 코드https://github.com/vinairesearch/lampat
공식 코드LAMPAT: Low-Rank Adaption for Multilingual Paraphrasing Using Adversarial Training
https://github.com/vipulraheja/coedit
공식 코드https://github.com/wyu-du/gp-vae
공식 코드Diverse Text Generation via Variational Encoder-Decoder Models with Gaussian Process Priors
https://github.com/xzhang00/qstr
공식 코드A Quality-based Syntactic Template Retriever for Syntactically-controlled Paraphrase Generation
https://github.com/yafuly/syntacticgen
공식 코드https://huggingface.co/datasets/facebook/content_rephrasing
공식 코드https://github.com/arvind385801/paraphrasegen
https://github.com/bengittelson/sow-reap-paraphrasing
Neural Syntactic Preordering for Controlled Paraphrase Generation
https://github.com/jpwahle/emnlp23-citation-field-influence
How Large Language Models are Transforming Machine-Paraphrased Plagiarism
https://github.com/jpwahle/emnlp24-prompt-paraphrase
https://github.com/jpwahle/prompt-paraphrase
https://github.com/lyh6560new/p3sum
https://github.com/memray/llm_phrase_semantics
Phrase-BERT: Improved Phrase Embeddings from BERT with an Application to Corpus Exploration
https://github.com/pluslabnlp/aesop
https://github.com/pushpendughosh/Stock-market-forecasting
Neural Paraphrase Generation with Stacked Residual LSTM Networks
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.