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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/YangLi1221/CoRA
공식 코드Improving Long-Tail Relation Extraction with Collaborating Relation-Augmented Attention
https://github.com/YatinChaudhary/NCLM
공식 코드Explainable and Discourse Topic-aware Neural Language Understanding
https://github.com/YatinChaudhary/RDoC_Task
공식 코드https://github.com/YerevaNN/JointUD
공식 코드Towards JointUD: Part-of-speech Tagging and Lemmatization using Recurrent Neural Networks
https://github.com/YichenGong/Densely-Interactive-Inference-Network
공식 코드https://github.com/Yifan-Gao/explicit_memory_tracker
공식 코드EMT: Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading
https://github.com/YinpeiDai/NAUM
공식 코드https://github.com/YouzhiTian/Structured-Content-Preservation-for-Unsupervised-Text-Style-Transfer
공식 코드Structured Content Preservation for Unsupervised Text Style Transfer
https://github.com/YuanEZhou/Grounded-Image-Captioning
공식 코드More Grounded Image Captioning by Distilling Image-Text Matching Model
https://github.com/Yufang-Liu/category-generator
공식 코드https://github.com/Yushi-Hu/PromptCap
공식 코드https://github.com/Yusser96/Exploring-Paracrawl-for-Document-level-Neural-Machine-Translation
공식 코드Exploring Paracrawl for Document-level Neural Machine Translation
https://github.com/YuweiYin/CROP
공식 코드https://github.com/ZBWpro/CSE-SFP
공식 코드CSE-SFP: Enabling Unsupervised Sentence Representation Learning via a Single Forward Pass
https://github.com/ZBWpro/CoT-BERT
공식 코드CoT-BERT: Enhancing Unsupervised Sentence Representation through Chain-of-Thought
https://github.com/ZBWpro/Pcc-tuning
공식 코드Pcc-tuning: Breaking the Contrastive Learning Ceiling in Semantic Textual Similarity
https://github.com/ZBWpro/STS-Regression
공식 코드https://github.com/ZackHodari/average_prosody
공식 코드Using generative modelling to produce varied intonation for speech synthesis
https://github.com/ZeweiChu/DiscoEval
공식 코드Evaluation Benchmarks and Learning Criteria for Discourse-Aware Sentence Representations
https://github.com/ZhangShiyue/ChrEn
공식 코드ChrEn: Cherokee-English Machine Translation for Endangered Language Revitalization
https://github.com/ZhangShiyue/ChrEnTranslate
공식 코드https://github.com/ZhenYangIACAS/NMT_GAN
공식 코드Improving Neural Machine Translation with Conditional Sequence Generative Adversarial Nets
https://github.com/ZhenYangIACAS/unsupervised-NMT
공식 코드https://github.com/ZhihongShao/Planning-based-Hierarchical-Variational-Model
공식 코드Long and Diverse Text Generation with Planning-based Hierarchical Variational Model
https://github.com/ZhixiuYe/Intra-Bag-and-Inter-Bag-Attentions
공식 코드Distant Supervision Relation Extraction with Intra-Bag and Inter-Bag Attentions
https://github.com/ZhouYuxuanYX/Benchmarking-and-Guiding-Adaptive-Sampling-Decoding-for-LLMs
공식 코드https://github.com/Zied130/Tweet_Sentiment-
공식 코드Tweet Sentiment Extraction using Viterbi Algorithm with Transfer Learning
https://github.com/Zminghua/SentEncoding
공식 코드Learning Universal Sentence Representations with Mean-Max Attention Autoencoder
https://github.com/ZovanZhou/MLRN
공식 코드https://github.com/ZurichNLP/20min-XD
공식 코드https://github.com/ZurichNLP/ContraPro
공식 코드https://github.com/ZzZZCHS/WS-3DVG
공식 코드Distilling Coarse-to-Fine Semantic Matching Knowledge for Weakly Supervised 3D Visual Grounding
https://github.com/a1da4/svp-sdml
공식 코드A Semantic Distance Metric Learning approach for Lexical Semantic Change Detection
https://github.com/aVariengien/esn-vs-lstm-on-cross-situationnal-learning
공식 코드https://github.com/aa200647963/sgg-dhl
공식 코드Dual-branch Hybrid Learning Network for Unbiased Scene Graph Generation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.