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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/ramonachristen/multilingual_negation_scope_resolution_on_legal_data
공식 코드Resolving Legalese: A Multilingual Exploration of Negation Scope Resolution in Legal Documents
https://github.com/randyzhouran/melm
공식 코드MELM: Data Augmentation with Masked Entity Language Modeling for Low-Resource NER
https://github.com/ranqiu92/RecoverSAT
공식 코드Learning to Recover from Multi-Modality Errors for Non-Autoregressive Neural Machine Translation
https://github.com/raphael-sch/HC_Sentence_Summarization
공식 코드Discrete Optimization for Unsupervised Sentence Summarization with Word-Level Extraction
https://github.com/raphaelmerx/llm-bilingual-examples
공식 코드Generating bilingual example sentences with large language models as lexicography assistants
https://github.com/raphaelolivier/whisper_attack
공식 코드There is more than one kind of robustness: Fooling Whisper with adversarial examples
https://github.com/rashad101/rome
공식 코드RoMe: A Robust Metric for Evaluating Natural Language Generation
https://github.com/rasmuskaer/mdapt_supplements
공식 코드MDAPT: Multilingual Domain Adaptive Pretraining in a Single Model
https://github.com/raspberryice/gen-arg
공식 코드Document-Level Event Argument Extraction by Conditional Generation
https://github.com/rbawden/DiaBLa-dataset
공식 코드DiaBLa: A Corpus of Bilingual Spontaneous Written Dialogues for Machine Translation
https://github.com/rbawden/paraphrasing-bleu
공식 코드A Study in Improving BLEU Reference Coverage with Diverse Automatic Paraphrasing
https://github.com/recitalAI/QuestEval
공식 코드https://github.com/recombee/beeformer
공식 코드beeFormer: Bridging the Gap Between Semantic and Interaction Similarity in Recommender Systems
https://github.com/redreamality/RERE-relation-extraction
공식 코드Revisiting the Negative Data of Distantly Supervised Relation Extraction
https://github.com/rekriz11/sockeye-recipes
공식 코드Complexity-Weighted Loss and Diverse Reranking for Sentence Simplification
https://github.com/renjie-liang/emet
공식 코드Efficient Temporal Sentence Grounding in Videos with Multi-Teacher Knowledge Distillation
https://github.com/renll/sparselt
공식 코드https://github.com/resrepos/leap
공식 코드https://github.com/reubenharry/pragmatic-translation
공식 코드Lost in Machine Translation: A Method to Reduce Meaning Loss
https://github.com/revitaai/govprobing
공식 코드https://github.com/rewicks/ctxpro
공식 코드Identifying Context-Dependent Translations for Evaluation Set Production
https://github.com/rf5/transfusion-asr
공식 코드https://github.com/rhythmcao/slu-dual-learning
공식 코드Dual Learning for Semi-Supervised Natural Language Understanding
https://github.com/richardaecn/cvpr18-caption-eval
공식 코드https://github.com/richermans/AudioCaption
공식 코드https://github.com/richermans/text_based_depression
공식 코드https://github.com/rickltt/event_detection
공식 코드https://github.com/riflezhang/genco
공식 코드https://github.com/rikdz/GraphWriter
공식 코드Text Generation from Knowledge Graphs with Graph Transformers
https://github.com/ringoreality/uniblock
공식 코드uniblock: Scoring and Filtering Corpus with Unicode Block Information
https://github.com/rishibommasani/mastersthesis
공식 코드https://github.com/ritual-uh/oats-absa
공식 코드https://github.com/ritual-uh/roast-absa
공식 코드ROAST: Review-level Opinion Aspect Sentiment Target Joint Detection for ABSA
https://github.com/rivergao/ffn_composition_analysis
공식 코드Measuring Meaning Composition in the Human Brain with Composition Scores from Large Language Models
https://github.com/rizkiarm/LipNet
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.