π Master Data Science & Programming!
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π° Machine Learning with Python
Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
https://t.iss.one/CodeProgrammer
π Machine Learning
Machine learning insights, practical tutorials, and clear explanations for beginners and aspiring data scientists. Follow the channel for models, algorithms, coding guides, and real-world ML applications.
https://t.iss.one/DataScienceM
π§ Code With Python
This channel delivers clear, practical content for developers, covering Python, Django, Data Structures, Algorithms, and DSA β perfect for learning, coding, and mastering key programming skills.
https://t.iss.one/DataScience4
π― PyData Careers | Quiz
Python Data Science jobs, interview tips, and career insights for aspiring professionals.
https://t.iss.one/DataScienceQ
πΎ Kaggle Data Hub
Your go-to hub for Kaggle datasets β explore, analyze, and leverage data for Machine Learning and Data Science projects.
https://t.iss.one/datasets1
π§βπ Udemy Coupons | Courses
The first channel in Telegram that offers free Udemy coupons
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π ML Research Hub
Advancing research in Machine Learning β practical insights, tools, and techniques for researchers.
https://t.iss.one/DataScienceT
π¬ Data Science Chat
An active community group for discussing data challenges and networking with peers.
https://t.iss.one/DataScience9
π Python Arab| Ψ¨Ψ§ΩΨ«ΩΩ ΨΉΨ±Ψ¨Ω
The largest Arabic-speaking group for Python developers to share knowledge and help.
https://t.iss.one/PythonArab
π Data Science Jupyter Notebooks
Explore the world of Data Science through Jupyter Notebooksβinsights, tutorials, and tools to boost your data journey. Code, analyze, and visualize smarter with every post.
https://t.iss.one/DataScienceN
πΊ Free Online Courses | Videos
Free online courses covering data science, machine learning, analytics, programming, and essential skills for learners.
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π Data Analytics
Dive into the world of Data Analytics β uncover insights, explore trends, and master data-driven decision making.
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π§ Learn Python Hub
Master Python with step-by-step courses β from basics to advanced projects and practical applications.
https://t.iss.one/Python53
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Admin: @HusseinSheikho
Unlock your potential with this curated list of Telegram channels. Whether you need books, datasets, interview prep, or project ideas, we have the perfect resource for you. Join the community today!
Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
https://t.iss.one/CodeProgrammer
Machine learning insights, practical tutorials, and clear explanations for beginners and aspiring data scientists. Follow the channel for models, algorithms, coding guides, and real-world ML applications.
https://t.iss.one/DataScienceM
This channel delivers clear, practical content for developers, covering Python, Django, Data Structures, Algorithms, and DSA β perfect for learning, coding, and mastering key programming skills.
https://t.iss.one/DataScience4
Python Data Science jobs, interview tips, and career insights for aspiring professionals.
https://t.iss.one/DataScienceQ
Your go-to hub for Kaggle datasets β explore, analyze, and leverage data for Machine Learning and Data Science projects.
https://t.iss.one/datasets1
The first channel in Telegram that offers free Udemy coupons
https://t.iss.one/DataScienceC
Advancing research in Machine Learning β practical insights, tools, and techniques for researchers.
https://t.iss.one/DataScienceT
An active community group for discussing data challenges and networking with peers.
https://t.iss.one/DataScience9
The largest Arabic-speaking group for Python developers to share knowledge and help.
https://t.iss.one/PythonArab
Explore the world of Data Science through Jupyter Notebooksβinsights, tutorials, and tools to boost your data journey. Code, analyze, and visualize smarter with every post.
https://t.iss.one/DataScienceN
Free online courses covering data science, machine learning, analytics, programming, and essential skills for learners.
https://t.iss.one/DataScienceV
Dive into the world of Data Analytics β uncover insights, explore trends, and master data-driven decision making.
https://t.iss.one/DataAnalyticsX
Master Python with step-by-step courses β from basics to advanced projects and practical applications.
https://t.iss.one/Python53
Professional Academic Writing & Simulation Services
https://t.iss.one/DataScienceY
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β¨From FLOPs to Footprints: The Resource Cost of Artificial Intelligence
π Summary:
This study quantifies the material footprint of AI training, analyzing Nvidia A100 GPUs heavy metal composition. Training GPT-4 demands thousands of GPUs, leading to tons of toxic waste. Optimizing hardware use and lifespan can significantly cut these material costs.
πΉ Publication Date: Published on Dec 3
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.04142
β’ PDF: https://arxiv.org/pdf/2512.04142
β¨ Spaces citing this paper:
β’ https://huggingface.co/spaces/sophia-falk/flops-2-footprints
==================================
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β https://t.iss.one/DataScienceT
#AIFootprint #AISustainability #GreenAI #ElectronicWaste #TechEthics
π Summary:
This study quantifies the material footprint of AI training, analyzing Nvidia A100 GPUs heavy metal composition. Training GPT-4 demands thousands of GPUs, leading to tons of toxic waste. Optimizing hardware use and lifespan can significantly cut these material costs.
πΉ Publication Date: Published on Dec 3
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.04142
β’ PDF: https://arxiv.org/pdf/2512.04142
β¨ Spaces citing this paper:
β’ https://huggingface.co/spaces/sophia-falk/flops-2-footprints
==================================
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β https://t.iss.one/DataScienceT
#AIFootprint #AISustainability #GreenAI #ElectronicWaste #TechEthics
β€1
β¨Active Video Perception: Iterative Evidence Seeking for Agentic Long Video Understanding
π Summary:
Active Video Perception AVP improves long video understanding by actively seeking query-relevant evidence. It uses an iterative plan-observe-reflect process, acquiring compact evidence directly from pixels. This achieves higher accuracy with reduced computational cost.
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05774
β’ PDF: https://arxiv.org/pdf/2512.05774
==================================
For more data science resources:
β https://t.iss.one/DataScienceT
#VideoUnderstanding #ActiveLearning #ComputerVision #AIResearch #DeepLearning
π Summary:
Active Video Perception AVP improves long video understanding by actively seeking query-relevant evidence. It uses an iterative plan-observe-reflect process, acquiring compact evidence directly from pixels. This achieves higher accuracy with reduced computational cost.
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05774
β’ PDF: https://arxiv.org/pdf/2512.05774
==================================
For more data science resources:
β https://t.iss.one/DataScienceT
#VideoUnderstanding #ActiveLearning #ComputerVision #AIResearch #DeepLearning
β¨Taxonomy-Adaptive Moderation Model with Robust Guardrails for Large Language Models
π Summary:
Roblox Guard 1.0 is an instruction fine-tuned LLM that enhances safety through comprehensive input-output moderation. It uses a pipeline of LLMs, generalizes to new safety taxonomies, and performs strongly on out-of-domain benchmarks. A new evaluation benchmark, RobloxGuard-Eval, is also released.
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05339
β’ PDF: https://arxiv.org/pdf/2512.05339
==================================
For more data science resources:
β https://t.iss.one/DataScienceT
#LLM #AISafety #AI #MachineLearning #NLP
π Summary:
Roblox Guard 1.0 is an instruction fine-tuned LLM that enhances safety through comprehensive input-output moderation. It uses a pipeline of LLMs, generalizes to new safety taxonomies, and performs strongly on out-of-domain benchmarks. A new evaluation benchmark, RobloxGuard-Eval, is also released.
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05339
β’ PDF: https://arxiv.org/pdf/2512.05339
==================================
For more data science resources:
β https://t.iss.one/DataScienceT
#LLM #AISafety #AI #MachineLearning #NLP
β€1
β¨From Segments to Scenes: Temporal Understanding in Autonomous Driving via Vision-Language Model
π Summary:
The TAD benchmark is introduced to evaluate temporal understanding in autonomous driving, addressing a gap where current VLMs perform poorly. It reveals that state-of-the-art models show substandard accuracy in this domain. Two training-free solutions, Scene-CoT and TCogMap, are proposed, improvi...
πΉ Publication Date: Published on Dec 4
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05277
β’ PDF: https://arxiv.org/pdf/2512.05277
β’ Github: https://github.com/vbdi/tad_bench
==================================
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β https://t.iss.one/DataScienceT
#AutonomousDriving #VisionLanguageModels #ComputerVision #AIResearch #DeepLearning
π Summary:
The TAD benchmark is introduced to evaluate temporal understanding in autonomous driving, addressing a gap where current VLMs perform poorly. It reveals that state-of-the-art models show substandard accuracy in this domain. Two training-free solutions, Scene-CoT and TCogMap, are proposed, improvi...
πΉ Publication Date: Published on Dec 4
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05277
β’ PDF: https://arxiv.org/pdf/2512.05277
β’ Github: https://github.com/vbdi/tad_bench
==================================
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β https://t.iss.one/DataScienceT
#AutonomousDriving #VisionLanguageModels #ComputerVision #AIResearch #DeepLearning
β€3
π€π§ Distil-Whisper: Faster, Smaller, and Smarter Speech Recognition by Hugging Face
ποΈ 08 Dec 2025
π AI News & Trends
The evolution of Automatic Speech Recognition (ASR) has reshaped how humans interact with technology. From dictation tools and live transcription to smart assistants and media captioning, ASR technology continues to bridge the gap between speech and digital communication. However, achieving real-time, high-accuracy transcription often comes at the cost of heavy computational requirements until now. Enter ...
#DistilWhisper #FasterSpeechRecognition #SmallerModels #HuggingFace #ASRTechnology #RealTimeTranscription
ποΈ 08 Dec 2025
π AI News & Trends
The evolution of Automatic Speech Recognition (ASR) has reshaped how humans interact with technology. From dictation tools and live transcription to smart assistants and media captioning, ASR technology continues to bridge the gap between speech and digital communication. However, achieving real-time, high-accuracy transcription often comes at the cost of heavy computational requirements until now. Enter ...
#DistilWhisper #FasterSpeechRecognition #SmallerModels #HuggingFace #ASRTechnology #RealTimeTranscription
β¨Colon-X: Advancing Intelligent Colonoscopy from Multimodal Understanding to Clinical Reasoning
π Summary:
Colon-X introduces ColonR1, a novel reasoning-centric model for intelligent colonoscopy. It achieves 56.61% accuracy, outperforming traditional methods by 25.22% under data scarcity, by leveraging new comprehensive multimodal datasets.
πΉ Publication Date: Published on Dec 3
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.03667
β’ PDF: https://arxiv.org/pdf/2512.03667
β’ Github: https://github.com/ai4colonoscopy/Colon-X
==================================
For more data science resources:
β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
Colon-X introduces ColonR1, a novel reasoning-centric model for intelligent colonoscopy. It achieves 56.61% accuracy, outperforming traditional methods by 25.22% under data scarcity, by leveraging new comprehensive multimodal datasets.
πΉ Publication Date: Published on Dec 3
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.03667
β’ PDF: https://arxiv.org/pdf/2512.03667
β’ Github: https://github.com/ai4colonoscopy/Colon-X
==================================
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β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
β¨DoVer: Intervention-Driven Auto Debugging for LLM Multi-Agent Systems
π Summary:
DoVer is an intervention-driven debugging approach for LLM multi-agent systems. It validates failure hypotheses and measures progress via targeted interventions, improving reliability. DoVer converts 18-49% of failed tasks into successes, offering an outcome-oriented debugging method.
πΉ Publication Date: Published on Dec 7
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.06749
β’ PDF: https://arxiv.org/pdf/2512.06749
β’ Project Page: https://aka.ms/DoVer
==================================
For more data science resources:
β https://t.iss.one/DataScienceT
#LLM #MultiAgentSystems #Debugging #AI #Research
π Summary:
DoVer is an intervention-driven debugging approach for LLM multi-agent systems. It validates failure hypotheses and measures progress via targeted interventions, improving reliability. DoVer converts 18-49% of failed tasks into successes, offering an outcome-oriented debugging method.
πΉ Publication Date: Published on Dec 7
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.06749
β’ PDF: https://arxiv.org/pdf/2512.06749
β’ Project Page: https://aka.ms/DoVer
==================================
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β https://t.iss.one/DataScienceT
#LLM #MultiAgentSystems #Debugging #AI #Research
β¨Beyond Real: Imaginary Extension of Rotary Position Embeddings for Long-Context LLMs
π Summary:
The paper proposes a method to enhance Rotary Position Embeddings by utilizing both the real and imaginary components of the complex-valued dot product, improving long-context modeling in Large Langua...
πΉ Publication Date: Published on Dec 8
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.07525
β’ PDF: https://arxiv.org/pdf/2512.07525
β’ Github: https://github.com/OpenMOSS/rope_pp
==================================
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β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
The paper proposes a method to enhance Rotary Position Embeddings by utilizing both the real and imaginary components of the complex-valued dot product, improving long-context modeling in Large Langua...
πΉ Publication Date: Published on Dec 8
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.07525
β’ PDF: https://arxiv.org/pdf/2512.07525
β’ Github: https://github.com/OpenMOSS/rope_pp
==================================
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β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
β¨LongCat-Image Technical Report
π Summary:
LongCat-Image is a bilingual open-source foundation model for image generation that addresses multilingual text rendering, photorealism, and deployment efficiency through rigorous data curation, compa...
πΉ Publication Date: Published on Dec 8
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.07584
β’ PDF: https://arxiv.org/pdf/2512.07584
β’ Project Page: https://longcat.chat/
β’ Github: https://github.com/meituan-longcat/LongCat-Image
==================================
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β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
LongCat-Image is a bilingual open-source foundation model for image generation that addresses multilingual text rendering, photorealism, and deployment efficiency through rigorous data curation, compa...
πΉ Publication Date: Published on Dec 8
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.07584
β’ PDF: https://arxiv.org/pdf/2512.07584
β’ Project Page: https://longcat.chat/
β’ Github: https://github.com/meituan-longcat/LongCat-Image
==================================
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β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
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β¨EgoEdit: Dataset, Real-Time Streaming Model, and Benchmark for Egocentric Video Editing
π Summary:
EgoEdit is a real-time, instruction-following egocentric video editor that addresses challenges in handling egomotion and hand-object interactions, outperforming existing methods on egocentric editing...
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.06065
β’ PDF: https://arxiv.org/pdf/2512.06065
β’ Project Page: https://snap-research.github.io/EgoEdit/
β’ Github: https://github.com/snap-research/EgoEdit
==================================
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β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
EgoEdit is a real-time, instruction-following egocentric video editor that addresses challenges in handling egomotion and hand-object interactions, outperforming existing methods on egocentric editing...
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.06065
β’ PDF: https://arxiv.org/pdf/2512.06065
β’ Project Page: https://snap-research.github.io/EgoEdit/
β’ Github: https://github.com/snap-research/EgoEdit
==================================
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β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
β¨Scaling Zero-Shot Reference-to-Video Generation
π Summary:
Saber is a scalable zero-shot framework for reference-to-video generation that uses video-text pairs to learn identity-consistent representations and outperforms models trained with explicit reference...
πΉ Publication Date: Published on Dec 7
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.06905
β’ PDF: https://arxiv.org/pdf/2512.06905
β’ Project Page: https://franciszzj.github.io/Saber/
==================================
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β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
Saber is a scalable zero-shot framework for reference-to-video generation that uses video-text pairs to learn identity-consistent representations and outperforms models trained with explicit reference...
πΉ Publication Date: Published on Dec 7
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.06905
β’ PDF: https://arxiv.org/pdf/2512.06905
β’ Project Page: https://franciszzj.github.io/Saber/
==================================
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β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
β¨Rethinking Training Dynamics in Scale-wise Autoregressive Generation
π Summary:
Self-Autoregressive Refinement (SAR) improves the quality of autoregressive generative models by addressing exposure bias through Stagger-Scale Rollout and Contrastive Student-Forcing Loss, leading to...
πΉ Publication Date: Published on Dec 6
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.06421
β’ PDF: https://arxiv.org/pdf/2512.06421
β’ Project Page: https://gengzezhou.github.io/SAR/
==================================
For more data science resources:
β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
Self-Autoregressive Refinement (SAR) improves the quality of autoregressive generative models by addressing exposure bias through Stagger-Scale Rollout and Contrastive Student-Forcing Loss, leading to...
πΉ Publication Date: Published on Dec 6
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.06421
β’ PDF: https://arxiv.org/pdf/2512.06421
β’ Project Page: https://gengzezhou.github.io/SAR/
==================================
For more data science resources:
β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
β¨Embodied Referring Expression Comprehension in Human-Robot Interaction
π Summary:
A large-scale dataset and multimodal model improve embodied interaction comprehension in robots by addressing perspective bias and enhancing multimodal signal integration. AI-generated summary As robo...
πΉ Publication Date: Published on Dec 6
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.06558
β’ PDF: https://arxiv.org/pdf/2512.06558
==================================
For more data science resources:
β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
A large-scale dataset and multimodal model improve embodied interaction comprehension in robots by addressing perspective bias and enhancing multimodal signal integration. AI-generated summary As robo...
πΉ Publication Date: Published on Dec 6
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.06558
β’ PDF: https://arxiv.org/pdf/2512.06558
==================================
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β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
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β¨Unified Video Editing with Temporal Reasoner
π Summary:
VideoCoF, a Chain-of-Frames approach, improves video editing precision and instruction-to-region mapping by using reasoning tokens without requiring user-provided masks. AI-generated summary Existing ...
πΉ Publication Date: Published on Dec 8
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.07469
β’ PDF: https://arxiv.org/pdf/2512.07469
β’ Project Page: https://videocof.github.io/
β’ Github: https://github.com/knightyxp/VideoCoF
πΉ Models citing this paper:
β’ https://huggingface.co/XiangpengYang/VideoCoF
==================================
For more data science resources:
β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
VideoCoF, a Chain-of-Frames approach, improves video editing precision and instruction-to-region mapping by using reasoning tokens without requiring user-provided masks. AI-generated summary Existing ...
πΉ Publication Date: Published on Dec 8
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.07469
β’ PDF: https://arxiv.org/pdf/2512.07469
β’ Project Page: https://videocof.github.io/
β’ Github: https://github.com/knightyxp/VideoCoF
πΉ Models citing this paper:
β’ https://huggingface.co/XiangpengYang/VideoCoF
==================================
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β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
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β¨Relational Visual Similarity
π Summary:
Vision-Language models fine-tuned on anonymized image captions can capture relational similarity between images, a capability lacking in current visual similarity metrics. AI-generated summary Humans ...
πΉ Publication Date: Published on Dec 8
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.07833
β’ PDF: https://arxiv.org/pdf/2512.07833
β’ Project Page: https://thaoshibe.github.io/relsim/
β’ Github: https://github.com/thaoshibe/relsim
==================================
For more data science resources:
β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
Vision-Language models fine-tuned on anonymized image captions can capture relational similarity between images, a capability lacking in current visual similarity metrics. AI-generated summary Humans ...
πΉ Publication Date: Published on Dec 8
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.07833
β’ PDF: https://arxiv.org/pdf/2512.07833
β’ Project Page: https://thaoshibe.github.io/relsim/
β’ Github: https://github.com/thaoshibe/relsim
==================================
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β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
β¨Group Representational Position Encoding
π Summary:
GRAPE is a unified positional encoding framework that combines multiplicative rotations and additive logit biases, extending existing methods like RoPE and ALiBi. AI-generated summary We present GRAPE...
πΉ Publication Date: Published on Dec 8
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.07805
β’ PDF: https://model-architectures.github.io/GRAPE/GRAPE.pdf
β’ Github: https://model-architectures.github.io/GRAPE/
==================================
For more data science resources:
β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
GRAPE is a unified positional encoding framework that combines multiplicative rotations and additive logit biases, extending existing methods like RoPE and ALiBi. AI-generated summary We present GRAPE...
πΉ Publication Date: Published on Dec 8
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.07805
β’ PDF: https://model-architectures.github.io/GRAPE/GRAPE.pdf
β’ Github: https://model-architectures.github.io/GRAPE/
==================================
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β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
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β¨Voxify3D: Pixel Art Meets Volumetric Rendering
π Summary:
Voxify3D is a two-stage framework that combines 3D mesh optimization with 2D pixel art supervision to generate high-quality voxel art with semantic preservation, pixel-art aesthetics, and discrete col...
πΉ Publication Date: Published on Dec 8
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.07834
β’ PDF: https://arxiv.org/pdf/2512.07834
β’ Project Page: https://yichuanh.github.io/Voxify-3D/
==================================
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β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
Voxify3D is a two-stage framework that combines 3D mesh optimization with 2D pixel art supervision to generate high-quality voxel art with semantic preservation, pixel-art aesthetics, and discrete col...
πΉ Publication Date: Published on Dec 8
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.07834
β’ PDF: https://arxiv.org/pdf/2512.07834
β’ Project Page: https://yichuanh.github.io/Voxify-3D/
==================================
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β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
β¨On the Interplay of Pre-Training, Mid-Training, and RL on Reasoning Language Models
π Summary:
A controlled experimental framework isolates and evaluates the contributions of pre-training, mid-training, and reinforcement learning in improving language model reasoning, demonstrating the necessit...
πΉ Publication Date: Published on Dec 8
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.07783
β’ PDF: https://arxiv.org/pdf/2512.07783
β’ Github: https://github.com/Interplay-LM-Reasoning/Interplay-LM-Reasoning
==================================
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β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
A controlled experimental framework isolates and evaluates the contributions of pre-training, mid-training, and reinforcement learning in improving language model reasoning, demonstrating the necessit...
πΉ Publication Date: Published on Dec 8
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.07783
β’ PDF: https://arxiv.org/pdf/2512.07783
β’ Github: https://github.com/Interplay-LM-Reasoning/Interplay-LM-Reasoning
==================================
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β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
β¨Vector Quantization using Gaussian Variational Autoencoder
π Summary:
Gaussian Quant (GQ) converts Gaussian VAE to VQ-VAE without training, outperforming previous VQ-VAEs and Gaussian VAE discretization methods across different architectures. AI-generated summary Vector...
πΉ Publication Date: Published on Dec 7
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.06609
β’ PDF: https://arxiv.org/pdf/2512.06609
β’ Github: https://github.com/Stability-AI/generative-models
πΉ Models citing this paper:
β’ https://huggingface.co/xutongda/GQModel
==================================
For more data science resources:
β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
Gaussian Quant (GQ) converts Gaussian VAE to VQ-VAE without training, outperforming previous VQ-VAEs and Gaussian VAE discretization methods across different architectures. AI-generated summary Vector...
πΉ Publication Date: Published on Dec 7
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.06609
β’ PDF: https://arxiv.org/pdf/2512.06609
β’ Github: https://github.com/Stability-AI/generative-models
πΉ Models citing this paper:
β’ https://huggingface.co/xutongda/GQModel
==================================
For more data science resources:
β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
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β¨VideoVLA: Video Generators Can Be Generalizable Robot Manipulators
π Summary:
VideoVLA uses a multi-modal Diffusion Transformer to predict actions and visual outcomes from language and image inputs, enabling strong generalization in robotic manipulation tasks. AI-generated summ...
πΉ Publication Date: Published on Dec 7
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.06963
β’ PDF: https://arxiv.org/pdf/2512.06963
β’ Project Page: https://videovla-nips2025.github.io/
==================================
For more data science resources:
β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
VideoVLA uses a multi-modal Diffusion Transformer to predict actions and visual outcomes from language and image inputs, enabling strong generalization in robotic manipulation tasks. AI-generated summ...
πΉ Publication Date: Published on Dec 7
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.06963
β’ PDF: https://arxiv.org/pdf/2512.06963
β’ Project Page: https://videovla-nips2025.github.io/
==================================
For more data science resources:
β https://t.iss.one/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
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