https://github.com/facebookresearch/imvotenet
공식 코드ImVoteNet: Boosting 3D Object Detection in Point Clouds with Image Votes
Papers with Code 아카이브
Open-Ended Question Answering
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Open-ended questions are defined as those that simply pose the question, without imposing any constraints on the format of the response. This distinguishes them from questions with a predetermined answer format.
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/facebookresearch/vip
공식 코드VIP: Towards Universal Visual Reward and Representation via Value-Implicit Pre-Training
https://github.com/flair-iisc/watermark_tradeoffs
공식 코드https://github.com/floklimm/graphon
공식 코드https://github.com/florisvb/windobs
공식 코드https://github.com/frankkramer-lab/ensmic
공식 코드https://github.com/frederickszk/LRNet
공식 코드Improving the Efficiency and Robustness of Deepfakes Detection through Precise Geometric Features
https://github.com/fromm-m/aaai2021-am-peer-reviews
공식 코드https://github.com/gdebarghya/Network-TwoSampleTesting
공식 코드https://github.com/gengdavid/slca
공식 코드SLCA: Slow Learner with Classifier Alignment for Continual Learning on a Pre-trained Model
https://github.com/georgestod/sparsistent_model_disco
공식 코드https://github.com/giganticode/probes
공식 코드https://github.com/globosco/A-learned-sorted-table-search-library
공식 코드Learned Sorted Table Search and Static Indexes in Small Model Space
https://github.com/gmftbyGMFTBY/HashRetrieval
공식 코드https://github.com/google-deepmind/neptune
공식 코드Neptune: The Long Orbit to Benchmarking Long Video Understanding
https://github.com/gradslam/gradslam
공식 코드https://github.com/greenaiproject/ict4s22
공식 코드https://github.com/hamzakeurti/homomorphismvae
공식 코드Homomorphism Autoencoder -- Learning Group Structured Representations from Observed Transitions
https://github.com/harvardnlp/encoder-agnostic-adaptation
공식 코드Encoder-Agnostic Adaptation for Conditional Language Generation
https://github.com/houtan-ghaffari/SSCCSLR
공식 코드An Efficient Method for the Classification of Croplands in Scarce-Label Regions
https://github.com/hplt-project/monolingual-multilingual-instruction-tuning
공식 코드Monolingual or Multilingual Instruction Tuning: Which Makes a Better Alpaca
https://github.com/i-machine-think/diagnnose
공식 코드https://github.com/ibayashi-hikaru/msml_experiments
공식 코드Exponential escape efficiency of SGD from sharp minima in non-stationary regime
https://github.com/idiap/rethinking-saliency
공식 코드Rethinking the Role of Gradient-Based Attribution Methods for Model Interpretability
https://github.com/in-dist-adversarials/in_distribution_adversarial_examples
공식 코드In-distribution adversarial attacks on object recognition models using gradient-free search
https://github.com/jasonzhang929/BVFT_empirical_experiments
공식 코드Towards Hyperparameter-free Policy Selection for Offline Reinforcement Learning
https://github.com/jgorham/stochastic_stein_discrepancy
공식 코드https://github.com/jhwjhw0123/streaming-regret-minimization-mabs
공식 코드Tight Regret Bounds for Single-pass Streaming Multi-armed Bandits
https://github.com/jinghanY/physicalAttackImageComposition
공식 코드https://github.com/jitaishik/revenue_comparisonhc
공식 코드A Revenue Function for Comparison-Based Hierarchical Clustering
https://github.com/jmerullo/limber
공식 코드https://github.com/kennymckormick/Triplet-Representation-of-human-Body
공식 코드TRB: A Novel Triplet Representation for Understanding 2D Human Body
https://github.com/kenshohara/3D-ResNets-PyTorch
공식 코드Would Mega-scale Datasets Further Enhance Spatiotemporal 3D CNNs?
https://github.com/kobayashikanna01/chain-of-discussion
공식 코드Chain-of-Discussion: A Multi-Model Framework for Complex Evidence-Based Question Answering
https://github.com/ksreenivasan/OOD_Federated_Learning
공식 코드Attack of the Tails: Yes, You Really Can Backdoor Federated Learning
https://github.com/law-ai/summarization
공식 코드Legal Case Document Summarization: Extractive and Abstractive Methods and their Evaluation
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.