Artificial Intelligence – Telegram
Artificial Intelligence
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Artificial Intelligence

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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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⭐️ Position-guided Text Prompt for Vision-Language Pre-training

🖥 Github: https://github.com/sail-sg/ptp

Paper: https://arxiv.org/abs/2212.09737v1

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

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

$git clone git@github.com: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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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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🔥 Real-Time Dense Monocular SLAM with Neural Radiance Fields

git clone https://github.com/ToniRV/NeRF-SLAM.git --recurse-submodules
git submodule update --init --recursive


🖥 Github: https://github.com/ToniRV/NeRF-SLAM

Paper: https://arxiv.org/abs/2210.13641

➡️ Video: https://www.youtube.com/watch?v=-6ufRJugcEU

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