Data Science

UMKC Announces New Master of Science in Artificial Intelligence

UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...

Scientists uncover new method to generate protein datasets for training AI

6 Months Using AI for Actual Work: What's Incredible, What's Overhyped, and What's Quietly Dangerous

Six months ago I committed to using AI tools for everything I possibly could in my work. Every day, every task, every workflow. Here's th...

[2602.12380] TFT-ACB-XML: Decision-Level Integration of Customized Temporal Fusion Transformer and Attention-BiLSTM with XGBoost Meta-Learner for BTC Price Forecasting

This article presents the TFT-ACB-XML framework, a hybrid model integrating Temporal Fusion Transformer and Attention-BiLSTM with XGBoost...

[2602.12373] Policy4OOD: A Knowledge-Guided World Model for Policy Intervention Simulation against the Opioid Overdose Crisis

The paper presents Policy4OOD, a knowledge-guided world model designed to simulate policy interventions against the opioid overdose crisi...

[2602.12317] Free Lunch in Medical Image Foundation Model Pre-training via Randomized Synthesis and Disentanglement

The paper presents RaSD, a framework for pre-training medical image foundation models using synthetic data, demonstrating superior perfor...

[2602.12315] AgenticShop: Benchmarking Agentic Product Curation for Personalized Web Shopping

The paper presents AgenticShop, a benchmark for evaluating agentic systems in personalized web shopping, addressing gaps in current evalu...

[2602.12313] Visible and Hyperspectral Imaging for Quality Assessment of Milk: Property Characterisation and Identification

This study explores the use of visible and hyperspectral imaging for the rapid, non-destructive assessment of milk quality, demonstrating...

[2602.12306] Quantum walk inspired JPEG compression of images

This article presents a novel JPEG compression method inspired by quantum walks, enhancing traditional techniques through an adaptive qua...

[2602.12296] Adaptive traffic signal control optimization using a novel road partition and multi-channel state representation method

This article presents a novel adaptive traffic signal control method utilizing Deep Q-Networks and Proximal Policy Optimization to enhanc...

[2602.12284] A Lightweight LLM Framework for Disaster Humanitarian Information Classification

This paper presents a lightweight framework for classifying humanitarian information from social media, enhancing disaster response effic...

[2602.13166] Optimal Take-off under Fuzzy Clearances

This paper discusses a hybrid obstacle avoidance system for unmanned aircraft that combines optimal control with fuzzy logic to improve d...

[2602.12631] AI Agents for Inventory Control: Human-LLM-OR Complementarity

This paper explores the integration of AI agents, particularly large language models (LLMs), with traditional operations research (OR) me...

[2602.12617] GeoAgent: Learning to Geolocate Everywhere with Reinforced Geographic Characteristics

GeoAgent introduces a novel model for geolocation tasks, enhancing AI's reasoning capabilities with geographic characteristics and outper...

[2602.12544] Scaling Web Agent Training through Automatic Data Generation and Fine-grained Evaluation

This paper presents a scalable pipeline for generating high-quality training data for web agents, introducing a novel evaluation framewor...

[2602.12356] A Theoretical Framework for Adaptive Utility-Weighted Benchmarking

This paper presents a theoretical framework for adaptive utility-weighted benchmarking in AI, emphasizing the importance of stakeholder p...

[2602.12389] Evolving Beyond Snapshots: Harmonizing Structure and Sequence via Entity State Tuning for Temporal Knowledge Graph Forecasting

This paper presents Entity State Tuning (EST), a novel framework for improving temporal knowledge graph forecasting by maintaining persis...

[D] “I Was Told There Would Be No Math” Why many ML projects fail before the model

This article discusses the common pitfalls in machine learning projects, emphasizing the importance of mathematical understanding and pro...

[D] ACL ARR Jan 2026 Reviews

The article discusses three official reviews of ACL ARR Jan 2026, presenting average scores for Overall Assessment and Confidence, prompt...

[D] METR TH1.1: “working_time” is wildly different across models. Quick breakdown + questions.

The article discusses METR's Time Horizon benchmark (TH1.1), highlighting significant differences in 'working_time' across various models...

Job threats, rogue bots: five hot issues in AI

The article discusses five critical issues surrounding AI at the AI Impact Summit, including job displacement, rogue AI, energy demands, ...

As AI data centers hit power limits, Peak XV backs Indian startup C2i to fix the bottleneck | TechCrunch

C2i, an Indian startup, has raised $15 million to develop a grid-to-GPU power solution aimed at reducing energy losses in AI data centers...

[R] TimeBase: The Power of Minimalism in Efficient Long-term Time Series Forecasting

The article discusses TimeBase, a minimalist approach to long-term time series forecasting, highlighting its potential as an alternative ...