ML Research Hub
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Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.

Admin: @HusseinSheikho || @Hussein_Sheikho
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🎞 Graph Neural Networks with Missing Node Features
 
💥 Free recorded tutorial by Emanuele Rossi

💾 https://youtu.be/xe5A-xQTBdM 
 
https://t.iss.one/DataScienceT ⭐️
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Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders

Paper: https://arxiv.org/pdf/2408.15998v1.pdf

Code: https://github.com/nvlabs/eagle

https://t.iss.one/DataScienceT ⭐️
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SGLang: Efficient Execution of Structured Language Model Programs

Paper: https://arxiv.org/pdf/2312.07104v2.pdf

Code: https://github.com/sgl-project/sglang

Datasets: MMLU | HellaSwag | LLaVA-Bench

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WavTokenizer: an Efficient Acoustic Discrete Codec Tokenizer for Audio Language Modeling

Paper: https://arxiv.org/pdf/2408.16532v1.pdf

Code: https://github.com/jishengpeng/wavtokenizer

Dataset: AudioSet LibriTTS SLURP

https://t.iss.one/DataScienceT ⭐️
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Eagle: Exploring The Design Space for Multimodal LLMs with Mixture of Encoders

Paper: https://arxiv.org/pdf/2408.15998v1.pdf

Code: https://github.com/nvlabs/eagle

https://t.iss.one/DataScienceT ⭐️
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Text2SQL is Not Enough: Unifying AI and Databases with TAG

Paper: https://arxiv.org/pdf/2408.14717v1.pdf

Code: https://github.com/tag-research/tag-bench

https://t.iss.one/DataScienceT ⭐️
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Mini-Omni: Language Models Can Hear, Talk While Thinking in Streaming

Paper: https://arxiv.org/pdf/2408.16725v2.pdf

Code: https://github.com/gpt-omni/mini-omni

Dataset: LibriSpeech

https://t.iss.one/DataScienceT ⭐️
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DGR-MIL: Exploring Diverse Global Representation in Multiple Instance Learning for Whole Slide Image Classification

Paper:https://arxiv.org/pdf/2407.03575v1.pdf

Code: https://github.com/chongqingnosubway/dgr-mil

https://t.iss.one/DataScienceT ⭐️
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Coursera has launched a collaboration with the MAJOR platform to enable students to self-fund using the MAJOR platform.

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aTENNuate: is a network that can be configured for real-time speech enhancement on raw audio waveforms.

🖥 Github: https://github.com/Brainchip-Inc/aTENNuate

📕 Paper: https://arxiv.org/abs/2409.03377v1

🚀 Datasethttps://paperswithcode.com/dataset/deep-noise-suppression-2020
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BEST AI RESEARCH PAPER SUMMARIZERS



Paperguide - Provides tools for extracting key insights, managing references, and annotating documents within PDFs to enhance study and research.

Tenorshare AI PDF Tool - Quickly analyzes and condenses papers using AI, and features an interactive chat interface powered by ChatGPT.

Elicit - Improves how users find and summarize academic papers using intelligent search and natural language processing to generate concise summaries.

QuillBot - Leverages AI for its Summarizer tool to analyze documents and generate extractive summaries, customizing length and format.

Semantic Scholar - An AI-powered academic search engine that generates one-sentence paper summaries and identifies influential citations.

IBM Watson Discovery - Harnesses cognitive computing to understand context within texts and enable precise searches across large document libraries for summarization.

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Coursera has launched a collaboration with the MAJOR platform to enable students to self-fund using the MAJOR platform.

Students can now access free Coursera scholarships through MAJOR.

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LLaMA-Omni: Seamless Speech Interaction with Large Language Models

Paper: https://arxiv.org/pdf/2409.06666v1.pdf

Code: https://github.com/ictnlp/llama-omni

https://t.iss.one/DataScienceT ⭐️
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Mini-Omni: Language Models Can Hear, Talk While Thinking in Streaming

Paper: https://arxiv.org/pdf/2408.16725v2.pdf

Code: https://github.com/gpt-omni/mini-omni

Dataset: LibriSpeech

https://t.iss.one/DataScienceT ⭐️
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MemoRAG: Moving towards Next-Gen RAG Via Memory-Inspired Knowledge Discovery

Paper: https://arxiv.org/pdf/2409.05591v2.pdf

Code: https://github.com/qhjqhj00/memorag

Dataset: GovReport

https://t.iss.one/DataScienceT ⭐️
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Data Science Cheat Sheets
Quick help to make a data scientist's life easier

About Dataset
A collection of cheat sheets for various data-science related languages and topics


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💡 #deeplearning #AI #ML #python
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