✨Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling

📝 Summary:
Visual generation models need to advance beyond appearance synthesis to incorporate structural, dynamic, and causal understanding through a five-level taxonomy spanning from atomic to world-modeling g...

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.28185
• PDF: https://arxiv.org/pdf/2604.28185

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Intern-Atlas: A Methodological Evolution Graph as Research Infrastructure for AI Scientists

📝 Summary:
Intern-Atlas presents a methodological evolution graph that captures structured relationships between research methods across AI literature, enabling automated tracking of methodological development a...

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.28158
• PDF: https://arxiv.org/pdf/2604.28158
• Project Page: https://intern-atlas.opendatalab.org.cn/

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Representation Fréchet Loss for Visual Generation

📝 Summary:
Fréchet Distance can be effectively optimized as a training objective when decoupling population size from batch size, leading to improved generator quality and alternative evaluation metrics. AI-gene...

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.28190
• PDF: https://arxiv.org/pdf/2604.28190
• Github: https://github.com/Jiawei-Yang/FD-Loss

🔹 Models citing this paper:
• https://huggingface.co/jjiaweiyang/FD-Loss

==================================

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨World2Minecraft: Occupancy-Driven Simulated Scenes Construction

📝 Summary:
World2Minecraft converts real-world scenes into structured Minecraft environments using 3D semantic occupancy prediction, with MinecraftOcc dataset enhancing occupancy prediction benchmarks for embodi...

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.27578
• PDF: https://arxiv.org/pdf/2604.27578
• Project Page: https://world2minecraft.github.io/
• Github: https://github.com/Nepenthes-zlc/World2Minecraft

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨The Last Human-Written Paper: Agent-Native Research Artifacts

📝 Summary:
S c i e n t i f i c p u b l i c a t i o n c o m p r e s s e s a b r a n c h i n g , i t e r a t i v e r e s e a r c h p r o c e s s i n t o a l i n e a r n a r r a t i v e , d i s c a r d i n g t h e ...

🔹 Publication Date: Published on Apr 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.24658
• PDF: https://arxiv.org/pdf/2604.24658
• Project Page: https://www.orchestra-research.com/ara
• Github: https://github.com/Orchestra-Research/Agent-Native-Research-Artifact

==================================

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨MoCapAnything V2: End-to-End Motion Capture for Arbitrary Skeletons

📝 Summary:
A fully end-to-end framework for arbitrary-skeleton motion capture that jointly optimizes video-to-pose and pose-to-rotation prediction while addressing rotation ambiguity through reference pose-rotat...

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.28130
• PDF: https://arxiv.org/pdf/2604.28130
• Project Page: https://animotionlab.github.io/MoCapAnythingV2/
• Github: https://github.com/animotionlab26/MocapAnything

==================================

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨PhyCo: Learning Controllable Physical Priors for Generative Motion

📝 Summary:
PhyCo enhances video diffusion models with physics-based control through a large-scale dataset, physics-supervised fine-tuning, and vision-language model guidance for improved physical consistency. AI...

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.28169
• PDF: https://arxiv.org/pdf/2604.28169
• Project Page: https://phyco-video.github.io/

==================================

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨InteractWeb-Bench: Can Multimodal Agent Escape Blind Execution in Interactive Website Generation?

📝 Summary:
InteractWeb-Bench presents the first multimodal interactive benchmark for website generation under non-expert low-code conditions, addressing semantic misalignment through diverse user agents and inte...

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.27419
• PDF: https://arxiv.org/pdf/2604.27419
• Project Page: https://interactweb-bench.wangqiyao.me/
• Github: https://github.com/AIforIP/InteractWeb-Bench

==================================

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Co-Evolving Policy Distillation

📝 Summary:
Co-Evolving Policy Distillation enables unified integration of multiple expert capabilities through parallel training and bidirectional policy distillation, outperforming existing methods in multi-mod...

🔹 Publication Date: Published on Apr 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.27083
• PDF: https://arxiv.org/pdf/2604.27083

==================================

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨ExoActor: Exocentric Video Generation as Generalizable Interactive Humanoid Control

📝 Summary:
ExoActor uses third-person video generation as a unified interface to model interaction dynamics between robots, environments, and objects, enabling task-conditioned humanoid behaviors through motion ...

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.27711
• PDF: https://arxiv.org/pdf/2604.27711
• Project Page: https://baai-agents.github.io/ExoActor/

==================================

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Leveraging Verifier-Based Reinforcement Learning in Image Editing

📝 Summary:
This paper introduces Edit-R1, a framework for image editing that uses a chain-of-thought verifier-based reasoning reward model Edit-RRM. Edit-RRM provides fine-grained, principle-based rewards, overcoming limitations of existing models. This approach significantly enhances image editing performa...

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.27505
• PDF: https://arxiv.org/pdf/2604.27505

==================================

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Length Value Model: Scalable Value Pretraining for Token-Level Length Modeling

📝 Summary:
LenVM is a token-level framework that models remaining generation length as a value estimation problem. It improves length control and efficiency in autoregressive models, significantly outperforming baselines and enabling continuous control over performance-efficiency trade-offs.

🔹 Publication Date: Published on Apr 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.27039
• PDF: https://arxiv.org/pdf/2604.27039
• Project Page: https://length-value-model.github.io/
• Github: https://length-value-model.github.io/demo/index.html

==================================

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Efficient Training on Multiple Consumer GPUs with RoundPipe

📝 Summary:
RoundPipe introduces a novel pipeline scheduling approach that eliminates weight binding constraints in LLM fine-tuning, enabling efficient training on consumer GPUs through dynamic stage distribution...

🔹 Publication Date: Published on Apr 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.27085
• PDF: https://arxiv.org/pdf/2604.27085
• Project Page: https://itcarrot.github.io/RoundPipe/
• Github: https://github.com/ITcarrot/RoundPipe

==================================

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨Claw-Eval-Live: A Live Agent Benchmark for Evolving Real-World Workflows

📝 Summary:
Claw-Eval-Live presents a dynamic benchmark for evaluating workflow agents that tracks evolving demands and verifies task execution through detailed logging and structured assessment methods. AI-gener...

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.28139
• PDF: https://arxiv.org/pdf/2604.28139
• Project Page: https://claw-eval-live.github.io
• Github: https://claw-eval-live.github.io

==================================

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#AI #DataScience #MachineLearning #HuggingFace #Research

✨ViPO: Visual Preference Optimization at Scale

📝 Summary:
ViPO scales visual preference optimization using Poly-DPO for noisy data and constructing ViPO, a large high-quality dataset. This dual approach yields superior performance, emphasizing that algorithmic adaptability and data quality are crucial.

🔹 Publication Date: Published on Apr 29

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.24953
• PDF: https://arxiv.org/pdf/2604.24953
• Project Page: https://liming-ai.github.io/ViPO
• Github: https://liming-ai.github.io/ViPO

==================================

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#VisualAI #MachineLearning #DeepLearning #Optimization #DataScience

✨Learning from Noisy Preferences: A Semi-Supervised Learning Approach to Direct Preference Optimization

📝 Summary:
Semi-DPO addresses label noise in multi-dimensional visual preference learning. It treats consistent data as clean and conflicting data as noisy, using iterative refinement via pseudo-labeling. This improves alignment with complex human preferences and achieves state-of-the-art results.

🔹 Publication Date: Published on Apr 27

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.24952
• PDF: https://arxiv.org/pdf/2604.24952
• Project Page: https://liming-ai.github.io/SemiDPO
• Github: https://liming-ai.github.io/SemiDPO

==================================

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#MachineLearning #SemiSupervisedLearning #DPO #NoisyData #PreferenceLearning

✨FlashRT: Towards Computationally and Memory Efficient Red-Teaming for Prompt Injection and Knowledge Corruption

📝 Summary:
FlashRT significantly enhances the efficiency of optimization-based prompt injection and knowledge corruption attacks for long-context LLMs. It delivers 2x-7x speedup and 2x-4x GPU memory reduction, enabling systematic and scalable security evaluations.

🔹 Publication Date: Published on Apr 30

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2604.28157
• PDF: https://arxiv.org/pdf/2604.28157
• Github: https://github.com/wang-yanting/FlashRT

==================================

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✨SignRoundV2: Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs

📝 Summary:
SignRoundV2 is a post-training quantization method for LLMs. It achieves competitive, near full-precision accuracy even at extremely low-bits like 2-bits. This is done via layer-wise bit allocation and pre-tuning scale search.

🔹 Publication Date: Published on Dec 4, 2025

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2512.04746
• PDF: https://arxiv.org/pdf/2512.04746
• Project Page: https://github.com/intel/auto-round
• Github: https://github.com/intel/auto-round

🔹 Models citing this paper:
• https://huggingface.co/Intel/MiroThinker-v1.5-30B-gguf-q2ks-mixed-AutoRound
• https://huggingface.co/Intel/DeepSeek-R1-0528-Qwen3-8B-int4-AutoRound

==================================

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#LLMs #Quantization #DeepLearning #AI #MachineLearning

Found an easy way to learn math for ML: Mathematics for Machine Learning 🎓📚

This is a curated collection on GitHub, including books, research papers, video lectures, and basic materials on math for studying and reviewing the mathematical foundations of machine learning. 📖📊

It helps build a stronger knowledge base by bringing together trusted resources around topics that machine learning engineers constantly encounter: linear algebra, mathematical analysis, probability theory, statistics, information theory, matrix calculus, and deep learning mathematics. 🧮🤖

Free public repository on GitHub. 💻✨

https://github.com/dair-ai/Mathematics-for-ML

#MachineLearning #Mathematics #DataScience #Learning #GitHub #AI

🔖 A huge open-source course on AI Engineering from scratch

In the repository, we've collected:
— 435 lessons;
— 320+ hours of content;
— Python, TypeScript, and Rust;
— AI agents, MCP servers, prompts, and AI skills.

Moreover, almost every lesson includes practical tasks, so this isn't just theory, but a full-fledged roadmap for AI Engineering. 🚀

⛓️ Link to the repository
https://github.com/rohitg00/ai-engineering-from-scratch

#AI #MachineLearning #Python #Rust #OpenSource #Tech

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