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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/facebookresearch/access
공식 코드https://github.com/facebookresearch/analyzing-uncertainty-nmt
공식 코드https://github.com/facebookresearch/asset
공식 코드https://github.com/facebookresearch/grounded-video-description
공식 코드https://github.com/facebookresearch/large_concept_model
공식 코드Large Concept Models: Language Modeling in a Sentence Representation Space
https://github.com/facebookresearch/loop
공식 코드VoiceLoop: Voice Fitting and Synthesis via a Phonological Loop
https://github.com/facebookresearch/mexma
공식 코드MEXMA: Token-level objectives improve sentence representations
https://github.com/facebookresearch/muss
공식 코드MUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases
https://github.com/facebookresearch/randsent
공식 코드No Training Required: Exploring Random Encoders for Sentence Classification
https://github.com/facebookresearch/responsiblenlp
공식 코드"I'm sorry to hear that": Finding New Biases in Language Models with a Holistic Descriptor Dataset
https://github.com/facebookresearch/sonar
공식 코드SONAR: Sentence-Level Multimodal and Language-Agnostic Representations
https://github.com/facebookresearch/stopes
공식 코드BLASER: A Text-Free Speech-to-Speech Translation Evaluation Metric
https://github.com/facebookresearch/synlm
공식 코드https://github.com/facebookresearch/text-simplification-evaluation
공식 코드Reference-less Quality Estimation of Text Simplification Systems
https://github.com/factslab/famus
공식 코드https://github.com/fajri91/discourse_probing
공식 코드https://github.com/fajri91/ffci
공식 코드FFCI: A Framework for Interpretable Automatic Evaluation of Summarization
https://github.com/fanconic/this_reads_like_that
공식 코드This Reads Like That: Deep Learning for Interpretable Natural Language Processing
https://github.com/fangbufang/sal
공식 코드Separate and Locate: Rethink the Text in Text-based Visual Question Answering
https://github.com/fanny-jourdan/FairTranslate
공식 코드https://github.com/fastnlp/nlp-dataset
공식 코드Style Transformer: Unpaired Text Style Transfer without Disentangled Latent Representation
https://github.com/fastnlp/style-transformer
공식 코드Style Transformer: Unpaired Text Style Transfer without Disentangled Latent Representation
https://github.com/fawazsammani/show-edit-tell
공식 코드https://github.com/fduyjx/rsman
공식 코드Relation-Specific Attentions over Entity Mentions for Enhanced Document-Level Relation Extraction
https://github.com/feizc/future-caption
공식 코드https://github.com/feizc/saic
공식 코드https://github.com/fenchri/walk-based-re
공식 코드https://github.com/feralvam/easse
공식 코드https://github.com/fereshtehjafarii/StructuralSentenceRepresentation
공식 코드A Self-supervised Representation Learning of Sentence Structure for Authorship Attribution
https://github.com/festivalhopper/swiss-parliaments-corpus-paper
공식 코드https://github.com/fesvhtr/DocMSU
공식 코드DocMSU: A Comprehensive Benchmark for Document-level Multimodal Sarcasm Understanding
https://github.com/fffffarmer/lsar
공식 코드Discovering Low-rank Subspaces for Language-agnostic Multilingual Representations
https://github.com/fgnt/meeteval
공식 코드MeetEval: A Toolkit for Computation of Word Error Rates for Meeting Transcription Systems
https://github.com/filemon11/discoparset-supertag
공식 코드Integrating Supertag Features into Neural Discontinuous Constituent Parsing
https://github.com/fivehills/sentence-relevance-and-sentence-surprisal
공식 코드Computational Sentence-level Metrics Predicting Human Sentence Comprehension
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.