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Notes on data science
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UrbanDS: A Graph-Guided LLM Multi-Agent System for Data-Intensive Urban Tasks
The paper presents UrbanDS, a multi-agent system that uses a graph to organize and analyze large-scale and heterogeneous urban data. The system includes a Data Profiling Agent, a Relation Agent, a Planner Agent…
PIER: Physics-Informed Environmental Retrieval for Time-Series Modeling
The researchers propose Physics-Informed Environmental Retrieval (PIER), a model-agnostic framework to improve the accuracy of environmental system modeling. The framework is designed to address challenges in limited…
Dimensionality Reduction Meets Network Science: Sensemaking on UMAP's kNN Graph
The authors of the paper 'Dimensionality Reduction Meets Network Science: Sensemaking on UMAP's kNN Graph', published in 2026, discuss a new approach to utilizing the internal k-nearest-neighbor (kNN) graph constructed…
Do LLM-Generated Skills Make Better AI Data Scientists? A Component Ablation Across Data-Science Workflows
A study by Wei-Jung Huang found no significant improvement in performance for LLM-generated skills compared to the task prompt alone when applied across four stages of a data scientist's work: data preparation, data…
Do LLM-Generated Skills Make Better AI Data Scientists? A Component Ablation Across Data-Science Workflows
A study investigates whether Language Model (LLM) generated skills can improve the performance of AI in data science tasks compared to traditional methods. The study tests this across four stages of a data science…
Data Analysis in the Wild: Benchmarking Large Language Models Against Real-World Data Complexities
The paper introduces DataGovBench, a benchmark for evaluating the performance of Large Language Models (LLMs) in practical scenarios, such as complex data analysis and insight discovery from large multi-tabular…
OpenThoughts-Agent: Data Recipes for Agentic Models
The OpenThoughts-Agent project presents a fully open data curation pipeline for training broadly capable AI agents. The researchers conducted ablation experiments and used the pipeline to create a dataset of 100K…
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