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태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/hologerry/SoCo
공식 코드Aligning Pretraining for Detection via Object-Level Contrastive Learning
https://github.com/hongyuanluke/chain-of-dictionary
공식 코드Chain-of-Dictionary Prompting Elicits Translation in Large Language Models
https://github.com/horrible-dong/CCT-Net
공식 코드Comparison Knowledge Translation for Generalizable Image Classification
https://github.com/hou-yz/DA_visualization
공식 코드https://github.com/hou-yz/mvdetr
공식 코드Multiview Detection with Shadow Transformer (and View-Coherent Data Augmentation)
https://github.com/how2sign/how2sign.github.io
공식 코드How2Sign: A Large-scale Multimodal Dataset for Continuous American Sign Language
https://github.com/howardchenhd/Syntax-awared-NMT
공식 코드Improved Neural Machine Translation with a Syntax-Aware Encoder and Decoder
https://github.com/hpc-fortran2cpp/fortran2cpp
공식 코드https://github.com/hpcaitech/fastfold
공식 코드FastFold: Reducing AlphaFold Training Time from 11 Days to 67 Hours
https://github.com/hplt-project/opuscleaner
공식 코드https://github.com/hplt-project/opustrainer
공식 코드https://github.com/hrishavbakulbarua/llm-hdr
공식 코드https://github.com/hsianktin/ttc
공식 코드Stochastic dynamics and ribosome-RNAP interactions in Transcription-Translation Coupling
https://github.com/hsm316/llm_wikipedia
공식 코드https://github.com/huangqiusheng/bridgegan
공식 코드https://github.com/huawei-noah/Pretrained-Language-Model
공식 코드Universal Conditional Masked Language Pre-training for Neural Machine Translation
https://github.com/hubreb/imitkd_ast
공식 코드https://github.com/hudenjear/rploss
공식 코드https://github.com/huggingface/transformers/blob/master/examples/seq2seq/README.md
공식 코드https://github.com/huiguanlab/nrccr
공식 코드Cross-Lingual Cross-Modal Retrieval with Noise-Robust Learning
https://github.com/hujiecpp/VisualFeatureTranslation
공식 코드https://github.com/hulianyuyy/corrnet_plus
공식 코드CorrNet+: Sign Language Recognition and Translation via Spatial-Temporal Correlation
https://github.com/husseinmozannar/SOQAL
공식 코드https://github.com/huthlab/rep_structure
공식 코드Low-Dimensional Structure in the Space of Language Representations is Reflected in Brain Responses
https://github.com/hwatahiki/portable-latent-policy
공식 코드Cross-Domain Policy Transfer by Representation Alignment via Multi-Domain Behavioral Cloning
https://github.com/hwazni/qcoref
공식 코드Towards Transparency in Coreference Resolution: A Quantum-Inspired Approach
https://github.com/hwichan0720/pruning_for_multilinguality
공식 코드Pruning Multilingual Large Language Models for Multilingual Inference
https://github.com/hwijeen/OffensEval2020
공식 코드NLPDove at SemEval-2020 Task 12: Improving Offensive Language Detection with Cross-lingual Transfer
https://github.com/hyperplane-lab/ACL-GAN
공식 코드Unpaired Image-to-Image Translation using Adversarial Consistency Loss
https://github.com/i-machine-think/compositionality_paradox_mt
공식 코드The paradox of the compositionality of natural language: a neural machine translation case study
https://github.com/i-need-sleep/eval_attack
공식 코드Robustness Tests for Automatic Machine Translation Metrics with Adversarial Attacks
https://github.com/iacercalixto/variational_mmt
공식 코드https://github.com/iamalexkorotin/KernelNeuralOptimalTransport
공식 코드https://github.com/iamalexkorotin/neuraloptimaltransport
공식 코드https://github.com/iamcreateai/cyclevar
공식 코드CycleVAR: Repurposing Autoregressive Model for Unsupervised One-Step Image Translation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.