Code for MIMO Activation Function
🖥 Github: https://github.com/ljy9912/mimo_nn
📕 Paper: https://arxiv.org/pdf/2309.17194v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/cifar-10
@ArtificialIntelligencedl
🔥 Datasets: https://paperswithcode.com/dataset/cifar-10
@ArtificialIntelligencedl
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Incremental Transfer Learning (ITL) Survey
🖥 Github: https://github.com/yixinghuang/itlsurvey
📕 Paper: https://arxiv.org/pdf/2309.17192v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/tiny-imagenet
@ArtificialIntelligencedl
🔥 Datasets: https://paperswithcode.com/dataset/tiny-imagenet
@ArtificialIntelligencedl
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[ICCV 2023] Multi-task View Synthesis with Neural Radiance Fields
🖥 Github: https://github.com/zsh2000/muvienerf
📕 Paper:https://arxiv.org/pdf/2309.17450v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/nerf
↪️ Tasks: https://paperswithcode.com/task/novel-view-synthesis
@ArtificialIntelligencedl
🔥 Datasets: https://paperswithcode.com/dataset/nerf
@ArtificialIntelligencedl
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STGM: Spatio-Temporal Graph Mixformer for Traffic Forecasting
🖥 Github: https://github.com/Mouradost/STGM
📕 Paper: https://www.sciencedirect.com/science/article/abs/pii/S0957417423007832?via%3Dihub
🔥 Datasets: https://paperswithcode.com/dataset/metr-la
↪️ Tasks: https://paperswithcode.com/task/traffic-prediction
@ArtificialIntelligencedl
🔥 Datasets: https://paperswithcode.com/dataset/metr-la
@ArtificialIntelligencedl
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PerturbScore: Connecting Discrete and Continuous Perturbations in NLP
🖥 Github: https://github.com/renke999/perturbscore
📕 Paper: https://arxiv.org/pdf/2310.08889v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/imdb-movie-reviews
@ArtificialIntelligencedl
🔥 Datasets: https://paperswithcode.com/dataset/imdb-movie-reviews
@ArtificialIntelligencedl
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Forwarded from Анализ данных (Data analysis)
📒 GigaChat нового поколения.
Разработчики @gigachat_bot изменили подход к обучению модели, а потому практически все умения модели были улучшены. В частности, речь идет о сокращении текстов, ответов на вопросы и генерации идей.
Появился и бот GigaChat в социальной сети «ВКонтакте» — после активации, его можно использовать для самых разных целей: от создания текстов до генерации изображений (за счет интеграции с Kandinsky).
Число уникальных пользователей GigaChat достигло 1 млн.
• Попробовать
@data_analysis_ml
Разработчики @gigachat_bot изменили подход к обучению модели, а потому практически все умения модели были улучшены. В частности, речь идет о сокращении текстов, ответов на вопросы и генерации идей.
Появился и бот GigaChat в социальной сети «ВКонтакте» — после активации, его можно использовать для самых разных целей: от создания текстов до генерации изображений (за счет интеграции с Kandinsky).
Число уникальных пользователей GigaChat достигло 1 млн.
• Попробовать
@data_analysis_ml
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PHA
🖥 Github: https://github.com/bumble666/pha
📕 Paper: https://arxiv.org/pdf/2310.11670v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/glue
@ArtificialIntelligencedl
cd PHA
pip install -r requirements.txt🔥 Datasets: https://paperswithcode.com/dataset/glue
@ArtificialIntelligencedl
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Zero-shot Faithfulness Evaluation for Text Summarization with Foundation Language Model
🖥 Github: https://github.com/jiaqisjtu/faitheval-fflm
📕 Paper: https://arxiv.org/pdf/2310.11648v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/cnn-daily-mail-1
@ArtificialIntelligencedl
CUDA_VISIBLE_DEVICES=0 python3 main.py🔥 Datasets: https://paperswithcode.com/dataset/cnn-daily-mail-1
@ArtificialIntelligencedl
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DD-Net
🖥 Github: https://github.com/fandulu/DD-Net
📕 Paper: https://arxiv.org/pdf/1907.09658.pdf
🔥 Datasets: https://paperswithcode.com/dataset/gtea
@ArtificialIntelligencedl
🔥 Datasets: https://paperswithcode.com/dataset/gtea
@ArtificialIntelligencedl
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SplitGNN
🖥 Github: https://github.com/blackboxo/SplitGNN
📕 Paper: https://dl.acm.org/doi/pdf/10.1145/3583780.3615067
🔥 Datasets: https://paperswithcode.com/dataset/fdcompcn
@ArtificialIntelligencedl
🔥 Datasets: https://paperswithcode.com/dataset/fdcompcn
@ArtificialIntelligencedl
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SALMONN: Speech Audio Language Music Open Neural Network
🖥 Github: https://github.com/bytedance/salmonn
📕 Paper: https://arxiv.org/pdf/2310.13289v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/librispeech
@ArtificialIntelligencedl
🔥 Datasets: https://paperswithcode.com/dataset/librispeech
@ArtificialIntelligencedl
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[NeurIPS 2023] Global Structure-Aware Diffusion Process for Low-Light Image Enhancement
🖥 Github: https://github.com/jinnh/GSAD
📕 Paper: https://arxiv.org/pdf/2310.17577.pdf
🔥 Datasets: https://paperswithcode.com/dataset/lol
@ArtificialIntelligencedl
🔥 Datasets: https://paperswithcode.com/dataset/lol
@ArtificialIntelligencedl
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Human-Guided Complexity-Controlled Abstractions
🖥 Github: https://github.com/mycal-tucker/human-guided-abstractions
📕 Paper: https://arxiv.org/pdf/2310.17550v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/fashion-mnist
@ArtificialIntelligencedl
🔥 Datasets: https://paperswithcode.com/dataset/fashion-mnist
@ArtificialIntelligencedl
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DialogLLMScenic
🖥 Github: https://github.com/avmb/dialogllmscenic
📕 Paper: https://arxiv.org/pdf/2310.17372v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/carla
⭐ Tasks: https://paperswithcode.com/task/self-driving-cars
@ArtificialIntelligencedl
🔥 Datasets: https://paperswithcode.com/dataset/carla
@ArtificialIntelligencedl
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PETA: Evaluating the Impact of Protein Transfer Learning with Sub-word Tokenization on Downstream Applications
🖥 Github: hhttps://github.com/ginnm/proteinpretraining
📕 Paper: https://arxiv.org/pdf/2310.17415v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/peta-protein
⭐ Tasks: https://paperswithcode.com/task/language-modelling
@ArtificialIntelligencedl
🔥 Datasets: https://paperswithcode.com/dataset/peta-protein
@ArtificialIntelligencedl
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Bilingual Corpus Mining and Multistage Fine-Tuning for Improving Machine Translation of Lecture Trannoscripts
🖥 Github: https://github.com/shyyhs/CourseraParallelCorpusMining
📕 Paper: https://arxiv.org/abs/2311.03696v1
🔥 Datasets: https://paperswithcode.com/dataset/aspec
@ArtificialIntelligencedl
🔥 Datasets: https://paperswithcode.com/dataset/aspec
@ArtificialIntelligencedl
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Quantized Distillation for Driver Activity Recognition
🖥 Github: https://github.com/calvintanama/qd-driver-activity-reco
📕 Paper: https://arxiv.org/pdf/2311.05970v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/drive-act
✨ Tasks: https://paperswithcode.com/task/activity-recognition
@ArtificialIntelligencedl
🔥 Datasets: https://paperswithcode.com/dataset/drive-act
@ArtificialIntelligencedl
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Inherently Interpretable Time Series Classification via Multiple Instance Learning (MILLET)
🖥 Github: https://github.com/jaearly/miltimeseriesclassification
📕 Paper: https://arxiv.org/pdf/2311.10049v1.pdf
✨ Tasks: https://paperswithcode.com/task/decision-making
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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