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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/sotetsuk/alpha-dimt-icmlws
공식 코드Neural Sequence Model Training via $α$-divergence Minimization
https://github.com/sourajitcs/tips
공식 코드https://github.com/spacemanidol/CurriculumLearningForLanguageModels
공식 코드https://github.com/spaceml-org/expanding-sdo-capabilities
공식 코드Using U-Nets to Create High-Fidelity Virtual Observations of the Solar Corona
https://github.com/spandanagella/multisense
공식 코드https://github.com/sqflow/sqflow
공식 코드Squeeze flow of micro-droplets: convolutional neural network with trainable and tunable refinement
https://github.com/srvk/how2-dataset
공식 코드How2: A Large-scale Dataset for Multimodal Language Understanding
https://github.com/ssalazarcolores/Desmoking-laparoscopy-surgery-images-using-an-image-to-image-translation-guided-by-an-embedded-Dark-
공식 코드https://github.com/ssarfraz/SPL
공식 코드Content and Colour Distillation for Learning Image Translations with the Spatial Profile Loss
https://github.com/ssongwang/mix-domaincontrastivelearning
공식 코드Mix-Domain Contrastive Learning for Unpaired H&E-to-IHC Stain Translation
https://github.com/sssadrizadeh/NMT_Obfuscator
공식 코드NMT-Obfuscator Attack: Ignore a sentence in translation with only one word
https://github.com/sssadrizadeh/act
공식 코드A Classification-Guided Approach for Adversarial Attacks against Neural Machine Translation
https://github.com/sssadrizadeh/nmt-targeted-attack
공식 코드Targeted Adversarial Attacks against Neural Machine Translation
https://github.com/sssadrizadeh/transfool
공식 코드TransFool: An Adversarial Attack against Neural Machine Translation Models
https://github.com/st-vincent1/cornell_rich
공식 코드Reference-less Analysis of Context Specificity in Translation with Personalised Language Models
https://github.com/st-vincent1/mtcue
공식 코드https://github.com/stanford-oval/SPL
공식 코드Localizing Open-Ontology QA Semantic Parsers in a Day Using Machine Translation
https://github.com/stanford-oval/dialogues
공식 코드Zero and Few-Shot Localization of Task-Oriented Dialogue Agents with a Distilled Representation
https://github.com/stanford-oval/genie-toolkit
공식 코드Genie: A Generator of Natural Language Semantic Parsers for Virtual Assistant Commands
https://github.com/sted-byte/act4nat
공식 코드https://github.com/steinst/sentalign
공식 코드https://github.com/stephenphillips42/erl_egomotion
공식 코드https://github.com/stepjam/ARM
공식 코드Coarse-to-Fine Q-attention: Efficient Learning for Visual Robotic Manipulation via Discretisation
https://github.com/steventan0110/NMTModelAttack
공식 코드Doubly-Trained Adversarial Data Augmentation for Neural Machine Translation
https://github.com/steventan0110/diffnorm
공식 코드DiffNorm: Self-Supervised Normalization for Non-autoregressive Speech-to-speech Translation
https://github.com/stevetmat/BioInspiredFDesc
공식 코드A Novel Bio-Inspired Texture Descriptor based on Biodiversity and Taxonomic Measures
https://github.com/stofnun-arna-magnussonar/idioms_names_test_suite
공식 코드https://github.com/stt4sg/dialektsammlung-public
공식 코드SDS-200: A Swiss German Speech to Standard German Text Corpus
https://github.com/styx97/PolarizationAAAI2021
공식 코드We Don't Speak the Same Language: Interpreting Polarization through Machine Translation
https://github.com/su0315/discourse_context_mt
공식 코드Context-aware Neural Machine Translation for English-Japanese Business Scene Dialogues
https://github.com/submissionanon18/agg
공식 코드Improving Diffusion-based Image Translation using Asymmetric Gradient Guidance
https://github.com/sufe-nlp/transformer-alignment
공식 코드Accurate Word Alignment Induction from Neural Machine Translation
https://github.com/summitgao/RSIT_SRM_ISD
공식 코드https://github.com/sunbowliu/ptvsbt
공식 코드On the Complementarity between Pre-Training and Back-Translation for Neural Machine Translation
https://github.com/sunflower-the-cat/DAEA
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.