⏺ZHEM: An Integrated Data Processing Framework for Pretraining Foundation Models

🖥 Github: https://github.com/emanual20/zhem

💤 Paper: https://arxiv.org/pdf/2402.16358v1.pdf

🔥 Dataset: https://paperswithcode.com/dataset/wikitext-2

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📚 NATURAL LANGUAGE PROCESSING (2023)

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​​🧐 FIND: Interface Foundation Models' Embeddings

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💐 ArXiv: https://arxiv.org/pdf/2312.07532.pdf

Placing Objects in Context via Inpainting for Out-of-distribution Segmentation

⌨️ Github: https://github.com/naver/poc

🔖 Paper: https://arxiv.org/pdf/2402.16392v1.pdf

🔥 Dataset: https://paperswithcode.com/dataset/cityscapes

💫 Tasks: https://paperswithcode.com/task/segmentation

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🔥SOTA: Stable Diffusion 3: out ! 🔥

Stable Diffusion 3 is SOTA's new text to image technology.

The new Multimodal Diffusion Transformer (MM Bit) architecture uses separate sets of weights for images and language, improving text/spelling comprehension capabilities.

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✅ Largest models are superior to open SOTA models such as SDXL

🤥 Blog : https://stability.ai/news/stable-diffusion-3-research-paper

✅️ Paper : https://stabilityai-public-packages.s3.us-west-2.amazonaws.com/Stable+Diffusion+3+Paper.pdf

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RENT (Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning, ICLR 2024)

🖥 Github: https://github.com/BaeHeeSun/RENT

🔖 Paper: https://arxiv.org/pdf/2403.02690v1.pdf

🔥 Dataset: https://paperswithcode.com/dataset/cifar-10

✨ Tasks: https://paperswithcode.com/task/learning-with-noisy-labels

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🖼️ Differential Diffusion: Giving Each Pixel Its Strength 🔥

✅ code: github.com/exx8/differential-diffusion

✅ page: differential-diffusion.github.io

✅ paper: arxiv.org/abs/2306.00950

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💡 ResAdapter: Domain Consistent Resolution Adapter for Diffusion Models

New framework designed for diffusion models (eg SD) to create images at any resolution and aspect ratio.
Unlike other resolution generation methods that process images with post-processing, ResAdapter directly generates images at a given resolution.

💥 page : https://res-adapter.github.io

🫧 paper : https://arxiv.org/abs/2403.02084

⭐️ code : https://github.com/bytedance/res-adapter

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📁Machine Learning Techniques Applied to the Study of Drug Transporters

📕 Journal: Molecules (I.F.= 4.6)
📅 Publish year: 2023

🧑‍💻 Authors: Xiaorui Kong, Kexin Lin,Gaolei Wu
🤖 University: Department of Pharmacy, Dalian Medical University, China

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Recall-Oriented-CL-Framework

⌨️ Github: https://github.com/bigdata-inha/recall-oriented-cl-framework

📕 Paper: https://arxiv.org/pdf/2403.03082v1.pdf

🔥 Dataset: https://paperswithcode.com/dataset/cifar-10

✨ Tasks: https://paperswithcode.com/task/continual-learning

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🏎 TripoSR: Fast 3D Object Reconstruction from a Single Image

A state-of-the-art open source model for fast 3D reconstruction from a single image.

The model produces high-quality 3D models in less than 0.5 seconds on the NVIDIA A100 GPU.

🟢 page: https://tripo3d.ai

🟢 paper : https://drive.google.com/file/d/1LWlZPT2aASi9jHiGVhDSr4YCTANoFW5t/view

🟢 code : https://github.com/VAST-AI-Research/TripoSR

🫥 Deep Learning for Genomics: From Early Neural Nets to Modern Large Language Models

📕 Journal: International Journal of Molecular Sciences (I.F.= 5.6)
📅 Publish year: 2023

🧑‍💻 Authors: Tianwei Yue,Yuanxin Wang,Longxiang Zhang, ...
🟢 University: Carnegie Mellon University, & Johns Hopkins University, & Michigan State University, USA

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📃 A Guide for the Bioinformatic Analysis of Metabolomics Data

🗓 Publish year: 2024

🧑‍💻Authors: Guillem Santamaria and Francisco R Pinto
⭐️ University: University of Lisbon, Portugal

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VTG-GPT

🖥 Github: https://github.com/YoucanBaby/VTG-GPT

📕 Paper: https://arxiv.org/pdf/2403.02076v1.pdf

🔥 Dataset: https://paperswithcode.com/dataset/activitynet-captions

✨ Tasks: https://paperswithcode.com/task/zero-shot-moment-retrieval

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☄️ Trends in using deep learning algorithms in biomedical prediction systems

➡️ Journal: Frontiers in Neuroscience (I.F.= 4.3)
🗓 Publish year: 2023

🧑‍💻 Authors: Yanbu Wang, Linqing Liu, Chao Wang
👀 University: Beijing Sport University-Peking University, Beijing, China

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Arbitrary-Scale Point Cloud Upsampling by Voxel-Based Network with Latent Geometric-Consistent Learning

🖥 Github: https://github.com/hikvision-research/3dvision

📕 Paper: https://arxiv.org/abs/2403.05117v1

🔥 Dataset: https://paperswithcode.com/dataset/scanobjectnn

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📝 Progress and Opportunities of Foundation Models in Bioinformatics

🗓 Publish year: 2023

🧑‍💻Authors: Qing Li, Zhihang Hu, Yixuan Wang, ...
🏘 University: University of Hong Kong, Hong Kong SAR - ChinaBioMap, Beijing, China

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👉 Paper: arxiv.org/pdf/2403.06862.pdf

👉 Project: www.zhengyiluo.com/SimXR/

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