Multimodal Chain-of-Thought Reasoning in Language Models
🖥 Github: https://github.com/amazon-science/mm-cot
⏩ Paper: https://arxiv.org/abs/2302.00923v1
➡️ Dataset: https://paperswithcode.com/dataset/scienceqa
ArtificialIntelligencedl
ArtificialIntelligencedl
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Neural Collapse Inspired Feature-Classifier Alignment for Few-Shot Class-Incremental Learning
🖥 Github: https://github.com/NeuralCollapseApplications/FSCIL
⏩ Paper: https://openreview.net/pdf?id=y5W8tpojhtJ
➡️ Dataset: https://paperswithcode.com/dataset/mini-imagenet
ArtificialIntelligence
ArtificialIntelligence
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Tab2KG: Semantic Table Interpretation with Lightweight Semantic Profiles
🖥 Github:https://github.com/sgottsch/tab2kg
⏩ Paper: https://arxiv.org/pdf/2302.01150v1.pdf
➡️ Dataset: https://paperswithcode.com/dataset/dbpedia
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🖥 Github:https://github.com/sgottsch/tab2kg
⏩ Paper: https://arxiv.org/pdf/2302.01150v1.pdf
➡️ Dataset: https://paperswithcode.com/dataset/dbpedia
ArtificialIntelligence
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Top-Down Beats Bottom-Up in 3D Instance Segmentation
🖥 Github: https://github.com/samsunglabs/td3d
⏩ Paper: https://arxiv.org/abs/2302.02871v1
➡️ Dataset: https://paperswithcode.com/dataset/scannet
ArtificialIntelligence
ArtificialIntelligence
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Expert Language Models (ELM)
🖥 Github: https://github.com/joeljang/elm
⏩ Paper: https://arxiv.org/abs/2302.03202v1
➡️ Dataset: https://paperswithcode.com/dataset/big-bench
ArtificialIntelligence
ArtificialIntelligence
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Сбер решил сделать подарок всем любителям научного знания и запустил сайт ко Дню российской науки. На сайте можно найти информацию об исследованиях и разработках (R&D) Сбербанка за последние годы.
Также там можно почитать об открытиях и проектах 10 лабораторий Сбера по топовым направлениям науки, в частности:
➡️блокчейн
➡️нейронауки
➡️AR/VR
➡️геймификация
➡️интернет вещей
➡️кибербезопасность
➡️искусственный интеллект
Кроме того можно узнать о партнёрских проектах лабораторий Сбера с ведущими вузами страны и центрами искусственного интеллекта на базе ВШЭ, Сколтеха и МФТИ, присоединиться к мероприятиям, которые проводят исследователи Сбера.
Кому мало, могут посетить специальный проект для всех, кто интересуется наукой.
ArtificialIntelligencedl
Также там можно почитать об открытиях и проектах 10 лабораторий Сбера по топовым направлениям науки, в частности:
➡️блокчейн
➡️нейронауки
➡️AR/VR
➡️геймификация
➡️интернет вещей
➡️кибербезопасность
➡️искусственный интеллект
Кроме того можно узнать о партнёрских проектах лабораторий Сбера с ведущими вузами страны и центрами искусственного интеллекта на базе ВШЭ, Сколтеха и МФТИ, присоединиться к мероприятиям, которые проводят исследователи Сбера.
Кому мало, могут посетить специальный проект для всех, кто интересуется наукой.
ArtificialIntelligencedl
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NASiam: Efficient Representation Learning using Neural Architecture Search for Siamese Networks
🖥 Github:https://github.com/aheuillet/nasiam
⏩ Paper: https://arxiv.org/pdf/2302.00059v1.pdf
➡️ Dataset:https://paperswithcode.com/dataset/cifar-100
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🖥 Github:https://github.com/aheuillet/nasiam
⏩ Paper: https://arxiv.org/pdf/2302.00059v1.pdf
➡️ Dataset:https://paperswithcode.com/dataset/cifar-100
ArtificialIntelligenceу
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FakeSV: A Multimodal Benchmark with Rich Social Context for Fake News Detection on Short Video Platforms
🖥 Github: https://github.com/ictmcg/fakesv
⏩ Paper: https://arxiv.org/abs/2302.03242v1
➡️ Data Processing: https://github.com/YaoFANGUK/video-subtitle-extractor
ArtificialIntelligenceу
ArtificialIntelligenceу
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PySlowFast
🖥 Github: https://github.com/facebookresearch/SlowFast
⏩ Paper: https://arxiv.org/abs/2302.04869v1
➡️ Dataset: https://paperswithcode.com/dataset/kinetics-400-1
ArtificialIntelligenceу
ArtificialIntelligenceу
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ManiSkill2: A Unified Benchmark for Generalizable Manipulation Skills
🖥 Github: https://github.com/haosulab/maniskill2
🖥 Colab: https://colab.research.google.com/github/haosulab/ManiSkill2/blob/main/examples/tutorials/1_quickstart.ipynb
📎 Docs: https://haosulab.github.io/ManiSkill2
⏩ Paper: https://arxiv.org/abs/2302.04659v1
➡️ Dataset: https://paperswithcode.com/dataset/plasticinelab
ArtificialIntelligenceу
📎 Docs: https://haosulab.github.io/ManiSkill2
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Polynomial Neural Fields for Subband Decomposition and Manipulation
🖥 Github: https://github.com/stevenygd/pnf
⏩ Paper: https://arxiv.org/abs/2302.04862v1
➡️ Dataset: https://paperswithcode.com/dataset/div2k
ArtificialIntelligenceу
ArtificialIntelligenceу
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Better Diffusion Models Further Improve Adversarial Training
🖥 Github: https://github.com/wzekai99/dm-improves-at
⏩ Paper: https://arxiv.org/abs/2302.04638v1
➡️ Dataset: https://paperswithcode.com/dataset/robustbench
ArtificialIntelligenceу
ArtificialIntelligenceу
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Raising the Cost of AI-Powered Image Editing via Adversarial Perturbations
🖥 Github: https://github.com/madrylab/photoguard
🖥 Colab: https://colab.research.google.com/drive/1pwfeSe6MUjD7UfqdWxurMSWWZhic9TPl?usp=sharing
⏩ Paper: https://arxiv.org/abs/2302.06588v1
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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Espaloma Charge
🖥 Github: https://github.com/choderalab/espaloma_charge
🖥 Colab: https://colab.research.google.com/drive/1e14EkNyidPI0wXBGcewh9m9LC1imSRWZ?usp=sharing
⏩ Paper: https://arxiv.org/abs/2302.06758v1
➡️ Dataset: https://paperswithcode.com/dataset/spice
@ArtificialIntelligencedl
$ pip install espaloma_charge@ArtificialIntelligencedl
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YOWOv2: A Stronger yet Efficient Multi-level Detection Framework for Real-time Spatio-temporal Action Detection
🖥 Github: https://github.com/yjh0410/YOWOv2
⏩ Paper: https://arxiv.org/abs/2302.06848v1
➡️ Dataset: https://paperswithcode.com/dataset/ava
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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Complex-Valued Neural Networks in Keras with Tensorflow
🖥 Github: https://github.com/JesperDramsch/keras-complex
⏩ Paper: https://arxiv.org/abs/2302.08286v1
➡️ Docs: https://keras-complex.readthedocs.io/math.html
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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A Bayesian optimization toolbox built on TensorFlow. Trieste supports onwards and uses semantic versioning.
$ pip install trieste@ArtificialIntelligencedl
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CluCDD:Contrastive Dialogue Disentanglement via Clustering
🖥 Github: https://github.com/gaojingsheng/clucdd
⏩ Paper: https://arxiv.org/abs/2302.08146v1
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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Swapped goal-conditioned offline reinforcement learning
🖥 Github: https://github.com/jasonma2016/gofar
⏩ Paper: https://arxiv.org/abs/2302.08865v1
➡️ Project: https://jasonma2016.github.io/GoFAR/
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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A Survey on Semi-Supervised Semantic Segmentation
🖥 Github: https://github.com/charlesCXK/TorchSemiSeg
⏩ Paper: https://arxiv.org/abs/2302.09899v1
➡️ Dataset: https://paperswithcode.com/dataset/sbd
@ArtificialIntelligencedl
@ArtificialIntelligencedl
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