⭐ MASTER: Multi-task Pre-trained Bottlenecked Masked Autoencoders are Better Dense Retrievers

🖥 Github: https://github.com/microsoft/simxns

⏩ Paper: https://arxiv.org/abs/2212.07841v1

➡️ Dataset: https://paperswithcode.com/dataset/natural-questions

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💨 Medfusion - Medical Denoising Diffusion Probabilistic Model

python -m venv venv
source venv/bin/activate
pip install -e .

🖥 Github: https://github.com/mueller-franzes/medfusion

⏩ Paper: https://arxiv.org/abs/2212.07501v1

➡️ Dataset: https://paperswithcode.com/dataset/chexpert

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🍪 Azimuth

Azimuth, an open-source dataset and error analysis tool for text classification, with love from ServiceNow.

pip install gdown
make download_demo
make CFG_PATH=/config/development/clinc/conf.json launch

🖥 Github: https://github.com/servicenow/azimuth

⏩ Paper: https://arxiv.org/abs/2212.08216v1

➡️ Docs: https://servicenow.github.io/azimuth

🔧 Demo: https://azimuth-demo.net/

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✔️ Query-as-context Pre-training for Dense Passage Retrieval

🖥 Github: https://github.com/caskcsg/ir

⏩ Paper: Query-as-context Pre-training for Dense Passage Retrieval

➡️ Dataset: https://paperswithcode.com/dataset/visual-genome

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📎 Open-Domain Multi-Document Summarization

pip install "git+https://github.com/allenai/open-mds.git"

🖥 Github: https://github.com/allenai/open-mds

⏩ Paper: https://arxiv.org/abs/2212.10526v1

➡️ Dataset: https://paperswithcode.com/dataset/multi-news

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⭐ Goal-oriented Autonomous Driving

🖥 Github: https://github.com/opendrivelab/uniad

⏩ Paper: https://arxiv.org/abs/2212.10156v1

➡️ Dataset: https://paperswithcode.com/dataset/nuscenes

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🌐 SHLE: Devices Tracking and Depth Filtering for Stereo-based Height Limit Esimation

$git clone [email protected]:Yang-Kaixing/SHLE.git

$cd SHLE

$pip install -r requirements.txt

🖥 Github: https://github.com/yang-kaixing/shle

⏩ Paper: https://arxiv.org/abs/2212.11538v1

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⭐️ TransPath: Learning Heuristics For Grid-Based Pathfinding via Transformers

🖥 Github: https://github.com/airi-institute/transpath

⏩ Paper: https://arxiv.org/abs/2212.11730v1

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✅ Scalable Adaptive Computation for Iterative Generation

$ pip install isab-pytorch

🖥 Github: https://github.com/lucidrains/isab-pytorch

⏩ Paper: https://arxiv.org/abs/2212.11972v1

➡️ Dataset: https://paperswithcode.com/dataset/kinetics-600

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⭐️ Revisiting Residual Networks for Adversarial Robustness: An Architectural Perspective

🖥 Github: https://github.com/zhichao-lu/robust-residual-network

⏩ Paper: https://arxiv.org/abs/2212.11005v1

➡️ Сheckpoints: https://github.com/zhichao-lu/robust-residual-network/blob/main

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🧟‍♂️ A Close Look at Spatial Modeling: From Attention to Convolution

🖥 Github: https://github.com/ma-xu/fcvit

⏩ Paper: https://arxiv.org/abs/2212.12552

➡️ Dataset: https://paperswithcode.com/dataset/coco

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📝 TextBox 2.0: A Text Generation Library with Pre-trained Language Models

git clone https://github.com/RUCAIBox/TextBox.git && cd TextBox
bash install.sh

🖥 Github: https://github.com/RUCAIBox/TextBox

⏩ Paper: https://arxiv.org/abs/2212.13005

➡️ Dataset: https://paperswithcode.com/dataset/lcsts

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On Realization of Intelligent Decision-Making in the Real World: A Foundation Decision Model Perspective


🖥 Github: https://github.com/shanghai-digital-brain-laboratory/bdm-db1

⏩ Paper: https://arxiv.org/abs/2212.12669v1

➡️ Dataset: https://paperswithcode.com/dataset/procgen

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⭐️ Cramming Language Model (Pretraining)

🖥 Github: https://github.com/jonasgeiping/cramming

⏩ Paper: https://arxiv.org/abs/2212.14034v1

➡️ Dataset: https://paperswithcode.com/dataset/glue

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End-to-End Modeling Hierarchical Time Series Using Autoregressive Transformer and Conditional Normalizing Flow based Reconciliation

🖥 Github: https://github.com/philipperemy/n-beats

⏩ Paper: https://arxiv.org/abs/1905.10437

➡️ Results: https://github.com/fecet/NBeats-M4

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✔️ Unsupervised Representation Learning from Pre-trained Diffusion Probabilistic Models (PDAE)

🖥 Github: https://github.com/ckczzj/pdae

⏩ Paper: https://arxiv.org/abs/2212.12990v1

➡️ Results: https://paperswithcode.com/dataset/mnist

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🖥 Part-Guided Relational Transformers for Fine-Grained Visual Recognition

🖥 Github: https://github.com/icvteam/part

⏩ Paper: https://arxiv.org/abs/2212.13685v1

➡️ Dataset: https://paperswithcode.com/dataset/stanford-cars

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🔥 Argoverse 2: Next Generation Datasets for Self-Driving Perception and Forecasting

pip install av2

🖥 Github: https://github.com/argoverse/av2-api

⏩ Paper: https://arxiv.org/abs/2301.00493v1

➡️ Dataset: https://github.com/argoverse/av2-api/blob/main/src/av2/datasets/sensor/README.md

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