✨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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✓ https://xn--r1a.website/DataScienceT

#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

✨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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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