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

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🔭 GRES: Generalized Referring Expression Segmentation

New benchmark (GRES), which extends the classic RES to allow expressions to refer to an arbitrary number of target objects.

🖥 Github: https://github.com/henghuiding/ReLA

Paper: https://arxiv.org/abs/2306.00968

🔎 Project: https://henghuiding.github.io/GRES/

📌 New dataset: https://github.com/henghuiding/gRefCOCO

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🦍 Gorilla: Large Language Model Connected with Massive APIs

Gorilla a finetuned LLaMA-based model that surpasses the performance of GPT-4 on writing API calls.

🖥 Github: https://github.com/ShishirPatil/gorilla

📕 Paper: https://arxiv.org/abs/2305.15334

🔗 Demo: https://drive.google.com/file/d/1E0k5mG1mTiaz0kukyK1PdeohJipTFh6j/view?usp=share_link

👉 Project: https://shishirpatil.github.io/gorilla/

⭐️ Colab: https://colab.research.google.com/drive/1DEBPsccVLF_aUnmD0FwPeHFrtdC0QIUP?usp=sharing

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Segment Anything 3D

SAM-3D: A toolbox transfers 2D SAM segments into 3D scene-level point clouds.

🖥 Github: https://github.com/pointcept/segmentanything3d

Paper: https://arxiv.org/abs/2306.03908v1

📌 Dataset: https://paperswithcode.com/dataset/scannet

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🐼 PandaLM: ReProducible and Automated Language Model Assessment

Judge large language model, named PandaLM, which is trained to distinguish the superior model given several LLMs. PandaLM's focus extends beyond just the objective correctness of responses, which is the main focus of traditional evaluation datasets.

🖥 Github: https://github.com/weopenml/pandalm

📕 Paper: https://arxiv.org/abs/2306.05087v1

🔗 Dataset: https://github.com/tatsu-lab/stanford_alpaca#data-release

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📹 Video-LLaMA: An Instruction-tuned Audio-Visual Language Model for Video Understanding

LLaMA is working on empowering large language models with video and audio understanding capability.

🖥 Github: https://github.com/damo-nlp-sg/video-llama

📕 Paper: https://arxiv.org/abs/2306.02858

Demo: https://huggingface.co/spaces/DAMO-NLP-SG/Video-LLaMA

📌 Model: https://modelscope.cn/studios/damo/video-llama/summary

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A list of the best Telegram channels related to data science, programming languages, and artificial intelligence.

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🏔️ Large Language Model for Geoscience

We introduce K2 (7B), an open-source language model trained by firstly further pretraining LLaMA on collected and cleaned geoscience literature, including geoscience open-access papers and Wikipedia pages, and secondly fine-tuning with knowledge-intensive instruction tuning data (GeoSignal).

git clone https://github.com/davendw49/k2.git
cd k2
conda env create -f k2.yml
conda activate k2


🖥 Github: https://github.com/davendw49/k2

⭐️ Demo: https://huggingface.co/daven3/k2_fp_delta

📕 Paper: https://arxiv.org/abs/2306.05064v1

🔗 Dataset: https://huggingface.co/datasets/daven3/geosignal

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💲 FinGPT: Open-Source Financial Large Language Models

Unlike proprietary models, FinGPT takes a data-centric approach, providing researchers and practitioners with accessible and transparent resources to develop their FinLLMs.

🖥 Github: https://github.com/ai4finance-foundation/fingpt

⭐️ FinNLP: https://github.com/ai4finance-foundation/finnlp

📕 Paper: https://arxiv.org/abs/2306.06031v1

🔗 Project: https://ai4finance-foundation.github.io/FinNLP/

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You can now download and watch all paid data science courses for free by subscribing to our new channel

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🧔 4DHumans: Reconstructing and Tracking Humans with Transformers

Fully "transformerized" version of a network for human mesh recovery.

🖥 Github: https://github.com/shubham-goel/4D-Humans

⭐️ Colab: https://colab.research.google.com/drive/1Ex4gE5v1bPR3evfhtG7sDHxQGsWwNwby?usp=sharing

📕 Paper: https://arxiv.org/pdf/2305.20091.pdf

🔗 Project: https://shubham-goel.github.io/4dhumans/

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Galactic: Scaling End-to-End Reinforcement Learning for Rearrangement
at 100k Steps-Per-Second

🖥 Github: https://github.com/facebookresearch/galactic

Paper: https://arxiv.org/pdf/2306.07552v1.pdf

💨 Dataset: https://paperswithcode.com/dataset/vizdoom

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Macaw-LLM: Multi-Modal Language Modeling with Image, Audio, Video, and Text Integration

Macaw-LLM is a model of its kind, bringing together state-of-the-art models for processing visual, auditory, and textual information, namely CLIP, Whisper, and LLaMA.

🖥 Github: https://github.com/lyuchenyang/macaw-llm

⭐️ Model: https://tinyurl.com/yem9m4nf

📕 Paper: https://tinyurl.com/4rsexudv

🔗 Dataset: https://github.com/lyuchenyang/Macaw-LLM/blob/main/data

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