π€π§ PandasAI: Transforming Data Analysis with Conversational Artificial Intelligence
ποΈ 28 Oct 2025
π AI News & Trends
In a world dominated by data, the ability to analyze and interpret information efficiently has become a core competitive advantage. From business intelligence dashboards to large-scale machine learning models, data-driven decision-making fuels innovation across industries. Yet, for most people, data analysis remains a technical challenge requiring coding expertise, statistical knowledge and familiarity with libraries like ...
#PandasAI #ConversationalAI #DataAnalysis #ArtificialIntelligence #DataScience #MachineLearning
ποΈ 28 Oct 2025
π AI News & Trends
In a world dominated by data, the ability to analyze and interpret information efficiently has become a core competitive advantage. From business intelligence dashboards to large-scale machine learning models, data-driven decision-making fuels innovation across industries. Yet, for most people, data analysis remains a technical challenge requiring coding expertise, statistical knowledge and familiarity with libraries like ...
#PandasAI #ConversationalAI #DataAnalysis #ArtificialIntelligence #DataScience #MachineLearning
πΉ Title: MergeMix: A Unified Augmentation Paradigm for Visual and Multi-Modal Understanding
πΉ Publication Date: Published on Oct 27
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.23479
β’ PDF: https://arxiv.org/pdf/2510.23479
β’ Github: https://github.com/Westlake-AI/openmixup
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πΉ Publication Date: Published on Oct 27
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.23479
β’ PDF: https://arxiv.org/pdf/2510.23479
β’ Github: https://github.com/Westlake-AI/openmixup
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πΉ Title: Multi-Agent Evolve: LLM Self-Improve through Co-evolution
πΉ Publication Date: Published on Oct 27
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.23595
β’ PDF: https://arxiv.org/pdf/2510.23595
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πΉ Publication Date: Published on Oct 27
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.23595
β’ PDF: https://arxiv.org/pdf/2510.23595
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πΉ Title: Sprint: Sparse-Dense Residual Fusion for Efficient Diffusion Transformers
πΉ Publication Date: Published on Oct 24
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.21986
β’ PDF: https://arxiv.org/pdf/2510.21986
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πΉ Publication Date: Published on Oct 24
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.21986
β’ PDF: https://arxiv.org/pdf/2510.21986
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π1
π€π§ Microsoft Data Formulator: Revolutionizing AI-Powered Data Visualization
ποΈ 28 Oct 2025
π AI News & Trends
In todayβs data-driven world, visualization is everything. Whether youβre a business analyst, data scientist or researcher, the ability to convert raw data into meaningful visuals can define the success of your decisions. Thatβs where Microsoftβs 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
ποΈ 28 Oct 2025
π AI News & Trends
In todayβs data-driven world, visualization is everything. Whether youβre a business analyst, data scientist or researcher, the ability to convert raw data into meaningful visuals can define the success of your decisions. Thatβs where Microsoftβs 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
π€π§ Googleβs GenAI MCP Toolbox for Databases: Transforming AI-Powered Data Management
ποΈ 28 Oct 2025
π 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
ποΈ 28 Oct 2025
π 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
π€π§ Wren AI: Transforming Business Intelligence with Generative AI
ποΈ 28 Oct 2025
π AI News & Trends
In the evolving world of data and analytics, one thing is certain β 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
ποΈ 28 Oct 2025
π AI News & Trends
In the evolving world of data and analytics, one thing is certain β 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
πΉ Title: VL-SAE: Interpreting and Enhancing Vision-Language Alignment with a Unified Concept Set
πΉ Publication Date: Published on Oct 24
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.21323
β’ PDF: https://arxiv.org/pdf/2510.21323
β’ Github: https://github.com/ssfgunner/VL-SAE
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πΉ Publication Date: Published on Oct 24
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.21323
β’ PDF: https://arxiv.org/pdf/2510.21323
β’ Github: https://github.com/ssfgunner/VL-SAE
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πΉ Title: Tongyi DeepResearch Technical Report
πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24701
β’ PDF: https://arxiv.org/pdf/2510.24701
β’ Project Page: https://tongyi-agent.github.io/blog/introducing-tongyi-deep-research/
β’ Github: https://github.com/Alibaba-NLP/DeepResearch
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πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24701
β’ PDF: https://arxiv.org/pdf/2510.24701
β’ Project Page: https://tongyi-agent.github.io/blog/introducing-tongyi-deep-research/
β’ Github: https://github.com/Alibaba-NLP/DeepResearch
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πΉ Title: ReplicationBench: Can AI Agents Replicate Astrophysics Research Papers?
πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24591
β’ PDF: https://arxiv.org/pdf/2510.24591
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24591
β’ PDF: https://arxiv.org/pdf/2510.24591
πΉ Datasets citing this paper:
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πΉ Title: OSWorld-MCP: Benchmarking MCP Tool Invocation In Computer-Use Agents
πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24563
β’ PDF: https://arxiv.org/pdf/2510.24563
β’ Project Page: https://osworld-mcp.github.io/
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24563
β’ PDF: https://arxiv.org/pdf/2510.24563
β’ Project Page: https://osworld-mcp.github.io/
πΉ Datasets citing this paper:
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πΉ Title: RoboOmni: Proactive Robot Manipulation in Omni-modal Context
πΉ Publication Date: Published on Oct 27
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.23763
β’ PDF: https://arxiv.org/pdf/2510.23763
β’ Project Page: https://OpenMOSS.github.io/RoboOmni
β’ Github: https://github.com/OpenMOSS/RoboOmni
πΉ Datasets citing this paper:
β’ https://huggingface.co/datasets/fnlp/OmniAction
β’ https://huggingface.co/datasets/fnlp/OmniAction-LIBERO
πΉ Spaces citing this paper:
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πΉ Publication Date: Published on Oct 27
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.23763
β’ PDF: https://arxiv.org/pdf/2510.23763
β’ Project Page: https://OpenMOSS.github.io/RoboOmni
β’ Github: https://github.com/OpenMOSS/RoboOmni
πΉ Datasets citing this paper:
β’ https://huggingface.co/datasets/fnlp/OmniAction
β’ https://huggingface.co/datasets/fnlp/OmniAction-LIBERO
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πΉ Title: Critique-RL: Training Language Models for Critiquing through Two-Stage Reinforcement Learning
πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24320
β’ PDF: https://arxiv.org/pdf/2510.24320
β’ Github: https://github.com/WooooDyy/Critique-RL
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24320
β’ PDF: https://arxiv.org/pdf/2510.24320
β’ Github: https://github.com/WooooDyy/Critique-RL
πΉ Datasets citing this paper:
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πΉ Title: Latent Sketchpad: Sketching Visual Thoughts to Elicit Multimodal Reasoning in MLLMs
πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24514
β’ PDF: https://arxiv.org/pdf/2510.24514
β’ Project Page: https://latent-sketchpad.github.io/
β’ Github: https://github.com/hwanyu112/Latent-Sketchpad
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24514
β’ PDF: https://arxiv.org/pdf/2510.24514
β’ Project Page: https://latent-sketchpad.github.io/
β’ Github: https://github.com/hwanyu112/Latent-Sketchpad
πΉ Datasets citing this paper:
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πΉ Title: Routing Matters in MoE: Scaling Diffusion Transformers with Explicit Routing Guidance
πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24711
β’ PDF: https://arxiv.org/pdf/2510.24711
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24711
β’ PDF: https://arxiv.org/pdf/2510.24711
πΉ Datasets citing this paper:
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πΉ Title: ParallelMuse: Agentic Parallel Thinking for Deep Information Seeking
πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24698
β’ PDF: https://arxiv.org/pdf/2510.24698
β’ Github: https://github.com/Alibaba-NLP/DeepResearch
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24698
β’ PDF: https://arxiv.org/pdf/2510.24698
β’ Github: https://github.com/Alibaba-NLP/DeepResearch
πΉ Datasets citing this paper:
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πΉ Title: AgentFold: Long-Horizon Web Agents with Proactive Context Management
πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24699
β’ PDF: https://arxiv.org/pdf/2510.24699
β’ Github: https://github.com/Alibaba-NLP/DeepResearch
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24699
β’ PDF: https://arxiv.org/pdf/2510.24699
β’ Github: https://github.com/Alibaba-NLP/DeepResearch
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πΉ Title: WebLeaper: Empowering Efficiency and Efficacy in WebAgent via Enabling Info-Rich Seeking
πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24697
β’ PDF: https://arxiv.org/pdf/2510.24697
β’ Github: https://github.com/Alibaba-NLP/DeepResearch
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πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24697
β’ PDF: https://arxiv.org/pdf/2510.24697
β’ Github: https://github.com/Alibaba-NLP/DeepResearch
πΉ Datasets citing this paper:
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πΉ Title: AgentFrontier: Expanding the Capability Frontier of LLM Agents with ZPD-Guided Data Synthesis
πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24695
β’ PDF: https://arxiv.org/pdf/2510.24695
β’ Github: https://github.com/Alibaba-NLP/DeepResearch
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24695
β’ PDF: https://arxiv.org/pdf/2510.24695
β’ Github: https://github.com/Alibaba-NLP/DeepResearch
πΉ Datasets citing this paper:
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πΉ Title: Repurposing Synthetic Data for Fine-grained Search Agent Supervision
πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24694
β’ PDF: https://arxiv.org/pdf/2510.24694
β’ Github: https://github.com/Alibaba-NLP/DeepResearch
πΉ Datasets citing this paper:
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πΉ Publication Date: Published on Oct 28
πΉ Paper Links:
β’ arXiv Page: https://arxiv.org/abs/2510.24694
β’ PDF: https://arxiv.org/pdf/2510.24694
β’ Github: https://github.com/Alibaba-NLP/DeepResearch
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