π€π§ CALM: Revolutionizing Large Language Models with Continuous Autoregressive Learning
ποΈ 23 Nov 2025
π AI News & Trends
Large Language Models (LLMs) such as GPT, Claude and Gemini have dramatically transformed artificial intelligence. From generating natural text to assisting in code and research, these models rely on one fundamental process: autoregressive generation predicting text one token at a time. However, this sequential nature poses a critical efficiency bottleneck. Generating text token by token ...
#CALM #ContinuousAutoregressiveLearning #LargeLanguageModels #AutoregressiveGeneration #AIEfficiency #AIInnovation
ποΈ 23 Nov 2025
π AI News & Trends
Large Language Models (LLMs) such as GPT, Claude and Gemini have dramatically transformed artificial intelligence. From generating natural text to assisting in code and research, these models rely on one fundamental process: autoregressive generation predicting text one token at a time. However, this sequential nature poses a critical efficiency bottleneck. Generating text token by token ...
#CALM #ContinuousAutoregressiveLearning #LargeLanguageModels #AutoregressiveGeneration #AIEfficiency #AIInnovation
π€π§ Agent-o-rama: The End-to-End Platform Transforming LLM Agent Development
ποΈ 23 Nov 2025
π AI News & Trends
As large language models (LLMs) become more capable, developers are increasingly using them to build intelligent AI agents that can perform reasoning, automation and decision-making tasks. However, building and managing these agents at scale is far from simple. Challenges such as monitoring model behavior, debugging reasoning paths, testing reliability and tracking performance metrics can make ...
#AgentoRama #LLMAgents #EndToEndPlatform #AIIntelligence #ModelMonitoring #AIDevelopment
ποΈ 23 Nov 2025
π AI News & Trends
As large language models (LLMs) become more capable, developers are increasingly using them to build intelligent AI agents that can perform reasoning, automation and decision-making tasks. However, building and managing these agents at scale is far from simple. Challenges such as monitoring model behavior, debugging reasoning paths, testing reliability and tracking performance metrics can make ...
#AgentoRama #LLMAgents #EndToEndPlatform #AIIntelligence #ModelMonitoring #AIDevelopment
Forwarded from Machine Learning with Python
Our Group on Signal (only for Programmers)
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π€π§ DeepEyesV2: The Next Leap Toward Agentic Multimodal Intelligence
ποΈ 23 Nov 2025
π AI News & Trends
The evolution of artificial intelligence has reached a stage where models are no longer limited to understanding text or images independently. The emergence of multimodal AI systems capable of processing and reasoning across multiple types of data has transformed how machines interpret the world. Yet, most existing multimodal models remain passive observers, unable to act ...
#DeepEyesV2 #AgenticMultimodalIntelligence #MultimodalAI #AIEvolution #ActiveReasoning #AIAction
ποΈ 23 Nov 2025
π AI News & Trends
The evolution of artificial intelligence has reached a stage where models are no longer limited to understanding text or images independently. The emergence of multimodal AI systems capable of processing and reasoning across multiple types of data has transformed how machines interpret the world. Yet, most existing multimodal models remain passive observers, unable to act ...
#DeepEyesV2 #AgenticMultimodalIntelligence #MultimodalAI #AIEvolution #ActiveReasoning #AIAction
π€π§ Reducing Hallucinations in Vision-Language Models: A Step Forward with VisAlign
ποΈ 24 Nov 2025
π AI News & Trends
As artificial intelligence continues to evolve, Large Vision-Language Models (LVLMs) have revolutionized how machines understand and describe the world. These models combine visual perception with natural language understanding to perform tasks such as image captioning, visual question answering and multimodal reasoning. Despite their success, a major problem persists β hallucination. This issue occurs when a ...
#VisAlign #ReducingHallucinations #VisionLanguageModels #LVLMs #MultimodalAI #AISafety
ποΈ 24 Nov 2025
π AI News & Trends
As artificial intelligence continues to evolve, Large Vision-Language Models (LVLMs) have revolutionized how machines understand and describe the world. These models combine visual perception with natural language understanding to perform tasks such as image captioning, visual question answering and multimodal reasoning. Despite their success, a major problem persists β hallucination. This issue occurs when a ...
#VisAlign #ReducingHallucinations #VisionLanguageModels #LVLMs #MultimodalAI #AISafety
π€π§ LEANN: The Bright Future of Lightweight, Private, and Scalable Vector Databases
ποΈ 24 Nov 2025
π AI News & Trends
In the rapidly expanding world of artificial intelligence, data storage and retrieval efficiency have become major bottlenecks for scalable AI systems. The growth of Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) has further intensified the demand for fast, private and space-efficient vector databases. Traditional systems like FAISS or Milvus while powerful, are resource-heavy and ...
#LEANN #LightweightVectorDatabases #PrivateAI #ScalableAI #RAG #AIDataStorage
ποΈ 24 Nov 2025
π AI News & Trends
In the rapidly expanding world of artificial intelligence, data storage and retrieval efficiency have become major bottlenecks for scalable AI systems. The growth of Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) has further intensified the demand for fast, private and space-efficient vector databases. Traditional systems like FAISS or Milvus while powerful, are resource-heavy and ...
#LEANN #LightweightVectorDatabases #PrivateAI #ScalableAI #RAG #AIDataStorage
π€π§ Omnilingual ASR: Metaβs Breakthrough in Multilingual Speech Recognition for 1600+ Languages
ποΈ 24 Nov 2025
π AI News & Trends
In an increasingly connected world, speech technology plays a vital role in bridging communication gaps across languages and cultures. Yet, despite rapid progress in Automatic Speech Recognition (ASR), most commercial systems still cater to only a few dozen major languages. Billions of people who speak lesser-known or low-resource languages remain excluded from the benefits of ...
#OmnilingualASR #MultilingualSpeechRecognition #MetaAI #LowResourceLanguages #SpeechTechnology #GlobalCommunication
ποΈ 24 Nov 2025
π AI News & Trends
In an increasingly connected world, speech technology plays a vital role in bridging communication gaps across languages and cultures. Yet, despite rapid progress in Automatic Speech Recognition (ASR), most commercial systems still cater to only a few dozen major languages. Billions of people who speak lesser-known or low-resource languages remain excluded from the benefits of ...
#OmnilingualASR #MultilingualSpeechRecognition #MetaAI #LowResourceLanguages #SpeechTechnology #GlobalCommunication
β€1
π€π§ Whisper by OpenAI: The Revolution in Multilingual Speech Recognition
ποΈ 25 Nov 2025
π AI News & Trends
Speech recognition has evolved rapidly over the past decade, transforming the way we interact with technology. From voice assistants to transcription services and real-time translation tools, the ability of machines to understand human speech has redefined accessibility, communication and automation. However, one of the major challenges that persisted for years was achieving robust, multilingual and ...
#Whisper #MultilingualSpeechRecognition #OpenAI #SpeechRecognition #AIAccessibility #VoiceTechnology
ποΈ 25 Nov 2025
π AI News & Trends
Speech recognition has evolved rapidly over the past decade, transforming the way we interact with technology. From voice assistants to transcription services and real-time translation tools, the ability of machines to understand human speech has redefined accessibility, communication and automation. However, one of the major challenges that persisted for years was achieving robust, multilingual and ...
#Whisper #MultilingualSpeechRecognition #OpenAI #SpeechRecognition #AIAccessibility #VoiceTechnology
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β¨A Survey of Large Language Models in Medicine: Principles, Applications, and Challenges
π Summary:
This survey comprehensively explores large language models LLMs in medicine. It covers their principles, applications, challenges, and offers guidance for their effective construction and use in clinical practice.
πΉ Publication Date: Published on Nov 9, 2023
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2311.05112
β’ PDF: https://arxiv.org/pdf/2311.05112
β’ Github: https://github.com/ai-in-health/medllmspracticalguide
β¨ Datasets citing this paper:
β’ https://huggingface.co/datasets/BAAI/SurveyScope
==================================
For more data science resources:
β https://t.me/DataScienceT
#LLM #AIinMedicine #HealthcareAI #MedicalAI #DigitalHealth
π Summary:
This survey comprehensively explores large language models LLMs in medicine. It covers their principles, applications, challenges, and offers guidance for their effective construction and use in clinical practice.
πΉ Publication Date: Published on Nov 9, 2023
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2311.05112
β’ PDF: https://arxiv.org/pdf/2311.05112
β’ Github: https://github.com/ai-in-health/medllmspracticalguide
β¨ Datasets citing this paper:
β’ https://huggingface.co/datasets/BAAI/SurveyScope
==================================
For more data science resources:
β https://t.me/DataScienceT
#LLM #AIinMedicine #HealthcareAI #MedicalAI #DigitalHealth
β€1
β¨EditThinker: Unlocking Iterative Reasoning for Any Image Editor
π Summary:
EditThinker proposes a deliberative framework for image editing, simulating human iterative critique and refinement of instructions. It uses an MLLM as a reasoning engine to enhance instruction-following capability. This significantly improves the performance of any image editor.
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05965
β’ PDF: https://arxiv.org/pdf/2512.05965
β’ Project Page: https://appletea233.github.io/think-while-edit/
==================================
For more data science resources:
β https://t.me/DataScienceT
#ImageEditing #MLLM #AI #Reasoning #ComputerVision
π Summary:
EditThinker proposes a deliberative framework for image editing, simulating human iterative critique and refinement of instructions. It uses an MLLM as a reasoning engine to enhance instruction-following capability. This significantly improves the performance of any image editor.
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05965
β’ PDF: https://arxiv.org/pdf/2512.05965
β’ Project Page: https://appletea233.github.io/think-while-edit/
==================================
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β https://t.me/DataScienceT
#ImageEditing #MLLM #AI #Reasoning #ComputerVision
β¨ReVSeg: Incentivizing the Reasoning Chain for Video Segmentation with Reinforcement Learning
π Summary:
ReVSeg enhances video object segmentation. It uses sequential reasoning within pretrained vision language models, optimized by reinforcement learning. This achieves state-of-the-art results and provides interpretable reasoning.
πΉ Publication Date: Published on Dec 2
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.02835
β’ PDF: https://arxiv.org/pdf/2512.02835
β’ Project Page: https://clementine24.github.io/ReVSeg/
β’ Github: https://github.com/Clementine24/ReVSeg
==================================
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β https://t.me/DataScienceT
#VideoSegmentation #ReinforcementLearning #VisionLanguageModels #ComputerVision #DeepLearning
π Summary:
ReVSeg enhances video object segmentation. It uses sequential reasoning within pretrained vision language models, optimized by reinforcement learning. This achieves state-of-the-art results and provides interpretable reasoning.
πΉ Publication Date: Published on Dec 2
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.02835
β’ PDF: https://arxiv.org/pdf/2512.02835
β’ Project Page: https://clementine24.github.io/ReVSeg/
β’ Github: https://github.com/Clementine24/ReVSeg
==================================
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β https://t.me/DataScienceT
#VideoSegmentation #ReinforcementLearning #VisionLanguageModels #ComputerVision #DeepLearning
β¨ProPhy: Progressive Physical Alignment for Dynamic World Simulation
π Summary:
ProPhy is a two-stage framework that enhances video generation by explicitly incorporating physics-aware conditioning and anisotropic generation. It uses a Mixture-of-Physics-Experts mechanism to extract fine-grained physical priors, improving physical consistency and realism in dynamic world sim...
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05564
β’ PDF: https://arxiv.org/pdf/2512.05564
==================================
For more data science resources:
β https://t.me/DataScienceT
#VideoGeneration #PhysicsAI #DynamicSimulation #DeepLearning #ComputerVision
π Summary:
ProPhy is a two-stage framework that enhances video generation by explicitly incorporating physics-aware conditioning and anisotropic generation. It uses a Mixture-of-Physics-Experts mechanism to extract fine-grained physical priors, improving physical consistency and realism in dynamic world sim...
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05564
β’ PDF: https://arxiv.org/pdf/2512.05564
==================================
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β https://t.me/DataScienceT
#VideoGeneration #PhysicsAI #DynamicSimulation #DeepLearning #ComputerVision
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β¨World Models That Know When They Don't Know: Controllable Video Generation with Calibrated Uncertainty
π Summary:
C3 is an uncertainty quantification method for training controllable video models that provides dense confidence estimation and out-of-distribution detection, addressing hallucination issues. AI-gener...
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05927
β’ PDF: https://arxiv.org/pdf/2512.05927
β’ Project Page: https://c-cubed-uq.github.io/
==================================
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β https://t.me/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
C3 is an uncertainty quantification method for training controllable video models that provides dense confidence estimation and out-of-distribution detection, addressing hallucination issues. AI-gener...
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05927
β’ PDF: https://arxiv.org/pdf/2512.05927
β’ Project Page: https://c-cubed-uq.github.io/
==================================
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β https://t.me/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
β¨Self-Improving VLM Judges Without Human Annotations
π Summary:
A framework for self-training a Vision-Language Model (VLM) judge using self-synthesized data improves judge accuracy on VL-RewardBench, surpassing larger models in several dimensions. AI-generated su...
πΉ Publication Date: Published on Dec 2
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05145
β’ PDF: https://arxiv.org/pdf/2512.05145
==================================
For more data science resources:
β https://t.me/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
A framework for self-training a Vision-Language Model (VLM) judge using self-synthesized data improves judge accuracy on VL-RewardBench, surpassing larger models in several dimensions. AI-generated su...
πΉ Publication Date: Published on Dec 2
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05145
β’ PDF: https://arxiv.org/pdf/2512.05145
==================================
For more data science resources:
β https://t.me/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
β¨Entropy Ratio Clipping as a Soft Global Constraint for Stable Reinforcement Learning
π Summary:
This paper introduces Entropy Ratio Clipping ERC to stabilize reinforcement learning. ERC uses the entropy ratio between policies as a global metric, imposing constraints to address distributional shifts overlooked by PPO-Clip. Experiments show consistent performance improvements.
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05591
β’ PDF: https://arxiv.org/pdf/2512.05591
==================================
For more data science resources:
β https://t.me/DataScienceT
#ReinforcementLearning #MachineLearning #DeepLearning #AI #ERC
π Summary:
This paper introduces Entropy Ratio Clipping ERC to stabilize reinforcement learning. ERC uses the entropy ratio between policies as a global metric, imposing constraints to address distributional shifts overlooked by PPO-Clip. Experiments show consistent performance improvements.
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05591
β’ PDF: https://arxiv.org/pdf/2512.05591
==================================
For more data science resources:
β https://t.me/DataScienceT
#ReinforcementLearning #MachineLearning #DeepLearning #AI #ERC
β¨Joint 3D Geometry Reconstruction and Motion Generation for 4D Synthesis from a Single Image
π Summary:
MoRe4D generates high-quality 4D scenes from a single image by jointly performing motion generation and geometric reconstruction. It uses a diffusion-based 4D Scene Trajectory Generator and depth-guided motion normalization for consistent dynamic details.
πΉ Publication Date: Published on Dec 4
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05044
β’ PDF: https://arxiv.org/pdf/2512.05044
β’ Project Page: https://ivg-yanranzhang.github.io/MoRe4D/
β’ Github: https://github.com/Zhangyr2022/MoRe4D
==================================
For more data science resources:
β https://t.me/DataScienceT
#4DSynthesis #3DReconstruction #MotionGeneration #ComputerVision #GenerativeAI
π Summary:
MoRe4D generates high-quality 4D scenes from a single image by jointly performing motion generation and geometric reconstruction. It uses a diffusion-based 4D Scene Trajectory Generator and depth-guided motion normalization for consistent dynamic details.
πΉ Publication Date: Published on Dec 4
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05044
β’ PDF: https://arxiv.org/pdf/2512.05044
β’ Project Page: https://ivg-yanranzhang.github.io/MoRe4D/
β’ Github: https://github.com/Zhangyr2022/MoRe4D
==================================
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β https://t.me/DataScienceT
#4DSynthesis #3DReconstruction #MotionGeneration #ComputerVision #GenerativeAI
β¨COOPER: A Unified Model for Cooperative Perception and Reasoning in Spatial Intelligence
π Summary:
COOPER is a unified MLLM that integrates depth and segmentation modalities to enhance spatial intelligence. It uses adaptive interleaved reasoning, improving spatial reasoning by 6.91%. Learning to generate auxiliary modalities also strengthens spatial understanding, boosting distance and size es...
πΉ Publication Date: Published on Dec 4
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.04563
β’ PDF: https://arxiv.org/pdf/2512.04563
β’ Github: https://github.com/zhangzef/COOPER
πΉ Models citing this paper:
β’ https://huggingface.co/Starrrrrry/COOPER-AMG
β’ https://huggingface.co/Starrrrrry/COOPER
β¨ Datasets citing this paper:
β’ https://huggingface.co/datasets/Starrrrrry/COOPER_Train_Set
==================================
For more data science resources:
β https://t.me/DataScienceT
#MLLM #SpatialIntelligence #ComputerVision #AI #DeepLearning
π Summary:
COOPER is a unified MLLM that integrates depth and segmentation modalities to enhance spatial intelligence. It uses adaptive interleaved reasoning, improving spatial reasoning by 6.91%. Learning to generate auxiliary modalities also strengthens spatial understanding, boosting distance and size es...
πΉ Publication Date: Published on Dec 4
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.04563
β’ PDF: https://arxiv.org/pdf/2512.04563
β’ Github: https://github.com/zhangzef/COOPER
πΉ Models citing this paper:
β’ https://huggingface.co/Starrrrrry/COOPER-AMG
β’ https://huggingface.co/Starrrrrry/COOPER
β¨ Datasets citing this paper:
β’ https://huggingface.co/datasets/Starrrrrry/COOPER_Train_Set
==================================
For more data science resources:
β https://t.me/DataScienceT
#MLLM #SpatialIntelligence #ComputerVision #AI #DeepLearning
β¨From Imitation to Discrimination: Toward A Generalized Curriculum Advantage Mechanism Enhancing Cross-Domain Reasoning Tasks
π Summary:
CAPO, a curriculum advantage policy optimization, enhances reinforcement learning for large language models by strategically introducing positive and negative advantage signals, improving reasoning ca...
πΉ Publication Date: Published on Dec 2
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.02580
β’ PDF: https://arxiv.org/pdf/2512.02580
==================================
For more data science resources:
β https://t.me/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
CAPO, a curriculum advantage policy optimization, enhances reinforcement learning for large language models by strategically introducing positive and negative advantage signals, improving reasoning ca...
πΉ Publication Date: Published on Dec 2
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.02580
β’ PDF: https://arxiv.org/pdf/2512.02580
==================================
For more data science resources:
β https://t.me/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
β¨AI & Human Co-Improvement for Safer Co-Superintelligence
π Summary:
The focus should be on collaborative co-improvement between humans and AI systems to achieve safer and accelerated AI research and development. AI-generated summary Self-improvement is a goal currentl...
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05356
β’ PDF: https://arxiv.org/pdf/2512.05356
==================================
For more data science resources:
β https://t.me/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
The focus should be on collaborative co-improvement between humans and AI systems to achieve safer and accelerated AI research and development. AI-generated summary Self-improvement is a goal currentl...
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05356
β’ PDF: https://arxiv.org/pdf/2512.05356
==================================
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β https://t.me/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
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β¨SpaceControl: Introducing Test-Time Spatial Control to 3D Generative Modeling
π Summary:
SpaceControl enables explicit spatial control of 3D generation using various geometric inputs, outperforming existing methods in geometric faithfulness while maintaining visual quality. AI-generated s...
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05343
β’ PDF: https://arxiv.org/pdf/2512.05343
==================================
For more data science resources:
β https://t.me/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research
π Summary:
SpaceControl enables explicit spatial control of 3D generation using various geometric inputs, outperforming existing methods in geometric faithfulness while maintaining visual quality. AI-generated s...
πΉ Publication Date: Published on Dec 5
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2512.05343
β’ PDF: https://arxiv.org/pdf/2512.05343
==================================
For more data science resources:
β https://t.me/DataScienceT
#AI #DataScience #MachineLearning #HuggingFace #Research