🤖🧠 Microsoft Data Formulator: Revolutionizing AI-Powered Data Visualization
🗓️ 28 Oct 2025
📚 AI News & Trends
In today’s data-driven world, visualization is everything. Whether you’re a business analyst, data scientist or researcher, the ability to convert raw data into meaningful visuals can define the success of your decisions. That’s where Microsoft’s Data Formulator steps in a cutting-edge, open-source platform designed to empower analysts to create rich, AI-assisted visualizations effortlessly. Developed by ...
#Microsoft #DataVisualization #AI #DataScience #OpenSource #Analytics
🗓️ 28 Oct 2025
📚 AI News & Trends
In today’s data-driven world, visualization is everything. Whether you’re a business analyst, data scientist or researcher, the ability to convert raw data into meaningful visuals can define the success of your decisions. That’s where Microsoft’s Data Formulator steps in a cutting-edge, open-source platform designed to empower analysts to create rich, AI-assisted visualizations effortlessly. Developed by ...
#Microsoft #DataVisualization #AI #DataScience #OpenSource #Analytics
🤖🧠 Google’s GenAI MCP Toolbox for Databases: Transforming AI-Powered Data Management
🗓️ 28 Oct 2025
📚 AI News & Trends
In the era of artificial intelligence, where data fuels innovation and decision-making, the need for efficient and intelligent data management tools has never been greater. Traditional methods of database management often require deep technical expertise and manual oversight, slowing down development cycles and creating operational bottlenecks. To address these challenges, Google has introduced the GenAI ...
#Google #GenAI #Database #AIPowered #DataManagement #MachineLearning
🗓️ 28 Oct 2025
📚 AI News & Trends
In the era of artificial intelligence, where data fuels innovation and decision-making, the need for efficient and intelligent data management tools has never been greater. Traditional methods of database management often require deep technical expertise and manual oversight, slowing down development cycles and creating operational bottlenecks. To address these challenges, Google has introduced the GenAI ...
#Google #GenAI #Database #AIPowered #DataManagement #MachineLearning
🤖🧠 Wren AI: Transforming Business Intelligence with Generative AI
🗓️ 28 Oct 2025
📚 AI News & Trends
In the evolving world of data and analytics, one thing is certain — the ability to transform raw data into actionable insights defines success. Organizations today are generating more data than ever before, yet accessing and understanding that data remains a significant challenge. Traditional business intelligence tools require technical expertise, SQL knowledge and manual configuration. ...
#WrenAI #GenerativeAI #BusinessIntelligence #DataAnalytics #AI #Insights
🗓️ 28 Oct 2025
📚 AI News & Trends
In the evolving world of data and analytics, one thing is certain — the ability to transform raw data into actionable insights defines success. Organizations today are generating more data than ever before, yet accessing and understanding that data remains a significant challenge. Traditional business intelligence tools require technical expertise, SQL knowledge and manual configuration. ...
#WrenAI #GenerativeAI #BusinessIntelligence #DataAnalytics #AI #Insights
🔹 Title: VL-SAE: Interpreting and Enhancing Vision-Language Alignment with a Unified Concept Set
🔹 Publication Date: Published on Oct 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.21323
• PDF: https://arxiv.org/pdf/2510.21323
• Github: https://github.com/ssfgunner/VL-SAE
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🔹 Publication Date: Published on Oct 24
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.21323
• PDF: https://arxiv.org/pdf/2510.21323
• Github: https://github.com/ssfgunner/VL-SAE
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🔹 Title: Tongyi DeepResearch Technical Report
🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24701
• PDF: https://arxiv.org/pdf/2510.24701
• Project Page: https://tongyi-agent.github.io/blog/introducing-tongyi-deep-research/
• Github: https://github.com/Alibaba-NLP/DeepResearch
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🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24701
• PDF: https://arxiv.org/pdf/2510.24701
• Project Page: https://tongyi-agent.github.io/blog/introducing-tongyi-deep-research/
• Github: https://github.com/Alibaba-NLP/DeepResearch
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🔹 Title: ReplicationBench: Can AI Agents Replicate Astrophysics Research Papers?
🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24591
• PDF: https://arxiv.org/pdf/2510.24591
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🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24591
• PDF: https://arxiv.org/pdf/2510.24591
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🔹 Title: OSWorld-MCP: Benchmarking MCP Tool Invocation In Computer-Use Agents
🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24563
• PDF: https://arxiv.org/pdf/2510.24563
• Project Page: https://osworld-mcp.github.io/
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🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24563
• PDF: https://arxiv.org/pdf/2510.24563
• Project Page: https://osworld-mcp.github.io/
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🔹 Title: RoboOmni: Proactive Robot Manipulation in Omni-modal Context
🔹 Publication Date: Published on Oct 27
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.23763
• PDF: https://arxiv.org/pdf/2510.23763
• Project Page: https://OpenMOSS.github.io/RoboOmni
• Github: https://github.com/OpenMOSS/RoboOmni
🔹 Datasets citing this paper:
• https://huggingface.co/datasets/fnlp/OmniAction
• https://huggingface.co/datasets/fnlp/OmniAction-LIBERO
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🔹 Publication Date: Published on Oct 27
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.23763
• PDF: https://arxiv.org/pdf/2510.23763
• Project Page: https://OpenMOSS.github.io/RoboOmni
• Github: https://github.com/OpenMOSS/RoboOmni
🔹 Datasets citing this paper:
• https://huggingface.co/datasets/fnlp/OmniAction
• https://huggingface.co/datasets/fnlp/OmniAction-LIBERO
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👍1
🔹 Title: Critique-RL: Training Language Models for Critiquing through Two-Stage Reinforcement Learning
🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24320
• PDF: https://arxiv.org/pdf/2510.24320
• Github: https://github.com/WooooDyy/Critique-RL
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🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24320
• PDF: https://arxiv.org/pdf/2510.24320
• Github: https://github.com/WooooDyy/Critique-RL
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🔹 Title: Latent Sketchpad: Sketching Visual Thoughts to Elicit Multimodal Reasoning in MLLMs
🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24514
• PDF: https://arxiv.org/pdf/2510.24514
• Project Page: https://latent-sketchpad.github.io/
• Github: https://github.com/hwanyu112/Latent-Sketchpad
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🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24514
• PDF: https://arxiv.org/pdf/2510.24514
• Project Page: https://latent-sketchpad.github.io/
• Github: https://github.com/hwanyu112/Latent-Sketchpad
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🔹 Title: Routing Matters in MoE: Scaling Diffusion Transformers with Explicit Routing Guidance
🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24711
• PDF: https://arxiv.org/pdf/2510.24711
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🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24711
• PDF: https://arxiv.org/pdf/2510.24711
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🔹 Title: ParallelMuse: Agentic Parallel Thinking for Deep Information Seeking
🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24698
• PDF: https://arxiv.org/pdf/2510.24698
• Github: https://github.com/Alibaba-NLP/DeepResearch
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🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24698
• PDF: https://arxiv.org/pdf/2510.24698
• Github: https://github.com/Alibaba-NLP/DeepResearch
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🔹 Title: AgentFold: Long-Horizon Web Agents with Proactive Context Management
🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24699
• PDF: https://arxiv.org/pdf/2510.24699
• Github: https://github.com/Alibaba-NLP/DeepResearch
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🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24699
• PDF: https://arxiv.org/pdf/2510.24699
• Github: https://github.com/Alibaba-NLP/DeepResearch
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🔹 Title: WebLeaper: Empowering Efficiency and Efficacy in WebAgent via Enabling Info-Rich Seeking
🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24697
• PDF: https://arxiv.org/pdf/2510.24697
• Github: https://github.com/Alibaba-NLP/DeepResearch
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🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24697
• PDF: https://arxiv.org/pdf/2510.24697
• Github: https://github.com/Alibaba-NLP/DeepResearch
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🔹 Title: AgentFrontier: Expanding the Capability Frontier of LLM Agents with ZPD-Guided Data Synthesis
🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24695
• PDF: https://arxiv.org/pdf/2510.24695
• Github: https://github.com/Alibaba-NLP/DeepResearch
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🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24695
• PDF: https://arxiv.org/pdf/2510.24695
• Github: https://github.com/Alibaba-NLP/DeepResearch
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🔹 Title: Repurposing Synthetic Data for Fine-grained Search Agent Supervision
🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24694
• PDF: https://arxiv.org/pdf/2510.24694
• Github: https://github.com/Alibaba-NLP/DeepResearch
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🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24694
• PDF: https://arxiv.org/pdf/2510.24694
• Github: https://github.com/Alibaba-NLP/DeepResearch
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🔹 Title: FunReason-MT Technical Report: Overcoming the Complexity Barrier in Multi-Turn Function Calling
🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24645
• PDF: https://arxiv.org/pdf/2510.24645
🔹 Datasets citing this paper:
• https://huggingface.co/datasets/Bingguang/FunReason-MT
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🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24645
• PDF: https://arxiv.org/pdf/2510.24645
🔹 Datasets citing this paper:
• https://huggingface.co/datasets/Bingguang/FunReason-MT
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🔹 Title: Game-TARS: Pretrained Foundation Models for Scalable Generalist Multimodal Game Agents
🔹 Publication Date: Published on Oct 27
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.23691
• PDF: https://arxiv.org/pdf/2510.23691
• Project Page: https://seed-tars.com/game-tars
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🔹 Publication Date: Published on Oct 27
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.23691
• PDF: https://arxiv.org/pdf/2510.23691
• Project Page: https://seed-tars.com/game-tars
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🔹 Title: Generalization or Memorization: Dynamic Decoding for Mode Steering
🔹 Publication Date: Published on Oct 25
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.22099
• PDF: https://arxiv.org/pdf/2510.22099
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🔹 Publication Date: Published on Oct 25
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.22099
• PDF: https://arxiv.org/pdf/2510.22099
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🔹 Title: Rethinking Visual Intelligence: Insights from Video Pretraining
🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24448
• PDF: https://arxiv.org/pdf/2510.24448
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🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24448
• PDF: https://arxiv.org/pdf/2510.24448
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🔹 Title: InteractComp: Evaluating Search Agents With Ambiguous Queries
🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24668
• PDF: https://arxiv.org/pdf/2510.24668
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🔹 Publication Date: Published on Oct 28
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.24668
• PDF: https://arxiv.org/pdf/2510.24668
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