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[2604.02349] OPRIDE: Offline Preference-based Reinforcement Learning via In-Dataset Exploration
Data Science

[2604.02349] OPRIDE: Offline Preference-based Reinforcement Learning via In-Dataset Exploration

Abstract page for arXiv paper 2604.02349: OPRIDE: Offline Preference-based Reinforcement Learning via In-Dataset Exploration

arXiv - AI · 3 min ·
[2604.02348] Contextual Intelligence The Next Leap for Reinforcement Learning
Machine Learning

[2604.02348] Contextual Intelligence The Next Leap for Reinforcement Learning

Abstract page for arXiv paper 2604.02348: Contextual Intelligence The Next Leap for Reinforcement Learning

arXiv - Machine Learning · 4 min ·
[2604.02347] FTimeXer: Frequency-aware Time-series Transformer with Exogenous variables for Robust Carbon Footprint Forecasting
Machine Learning

[2604.02347] FTimeXer: Frequency-aware Time-series Transformer with Exogenous variables for Robust Carbon Footprint Forecasting

Abstract page for arXiv paper 2604.02347: FTimeXer: Frequency-aware Time-series Transformer with Exogenous variables for Robust Carbon Fo...

arXiv - Machine Learning · 4 min ·
[2604.02346] DrugPlayGround: Benchmarking Large Language Models and Embeddings for Drug Discovery
Llms

[2604.02346] DrugPlayGround: Benchmarking Large Language Models and Embeddings for Drug Discovery

Abstract page for arXiv paper 2604.02346: DrugPlayGround: Benchmarking Large Language Models and Embeddings for Drug Discovery

arXiv - AI · 3 min ·
[2604.02345] UI-Oceanus: Scaling GUI Agents with Synthetic Environmental Dynamics

[2604.02345] UI-Oceanus: Scaling GUI Agents with Synthetic Environmental Dynamics

Abstract page for arXiv paper 2604.02345: UI-Oceanus: Scaling GUI Agents with Synthetic Environmental Dynamics

arXiv - AI · 4 min ·
[2604.02344] Characterizing WebGPU Dispatch Overhead for LLM Inference Across Four GPU Vendors, Three Backends, and Three Browsers
Llms

[2604.02344] Characterizing WebGPU Dispatch Overhead for LLM Inference Across Four GPU Vendors, Three Backends, and Three Browsers

Abstract page for arXiv paper 2604.02344: Characterizing WebGPU Dispatch Overhead for LLM Inference Across Four GPU Vendors, Three Backen...

arXiv - Machine Learning · 4 min ·
[2604.02343] Haiku to Opus in Just 10 bits: LLMs Unlock Massive Compression Gains
Llms

[2604.02343] Haiku to Opus in Just 10 bits: LLMs Unlock Massive Compression Gains

Abstract page for arXiv paper 2604.02343: Haiku to Opus in Just 10 bits: LLMs Unlock Massive Compression Gains

arXiv - AI · 4 min ·
[2604.02342] Homophily-aware Supervised Contrastive Counterfactual Augmented Fair Graph Neural Network
Machine Learning

[2604.02342] Homophily-aware Supervised Contrastive Counterfactual Augmented Fair Graph Neural Network

Abstract page for arXiv paper 2604.02342: Homophily-aware Supervised Contrastive Counterfactual Augmented Fair Graph Neural Network

arXiv - Machine Learning · 3 min ·
[2604.02341] LLM Reasoning with Process Rewards for Outcome-Guided Steps
Llms

[2604.02341] LLM Reasoning with Process Rewards for Outcome-Guided Steps

Abstract page for arXiv paper 2604.02341: LLM Reasoning with Process Rewards for Outcome-Guided Steps

arXiv - AI · 4 min ·
[2604.02340] Not All Denoising Steps Are Equal: Model Scheduling for Faster Masked Diffusion Language Models
Llms

[2604.02340] Not All Denoising Steps Are Equal: Model Scheduling for Faster Masked Diffusion Language Models

Abstract page for arXiv paper 2604.02340: Not All Denoising Steps Are Equal: Model Scheduling for Faster Masked Diffusion Language Models

arXiv - Machine Learning · 3 min ·
[2604.02339] SIEVE: Sample-Efficient Parametric Learning from Natural Language
Llms

[2604.02339] SIEVE: Sample-Efficient Parametric Learning from Natural Language

Abstract page for arXiv paper 2604.02339: SIEVE: Sample-Efficient Parametric Learning from Natural Language

arXiv - Machine Learning · 3 min ·
[2604.02338] LiME: Lightweight Mixture of Experts for Efficient Multimodal Multi-task Learning
Machine Learning

[2604.02338] LiME: Lightweight Mixture of Experts for Efficient Multimodal Multi-task Learning

Abstract page for arXiv paper 2604.02338: LiME: Lightweight Mixture of Experts for Efficient Multimodal Multi-task Learning

arXiv - Machine Learning · 4 min ·
[2604.02337] Generating Counterfactual Patient Timelines from Real-World Data
Machine Learning

[2604.02337] Generating Counterfactual Patient Timelines from Real-World Data

Abstract page for arXiv paper 2604.02337: Generating Counterfactual Patient Timelines from Real-World Data

arXiv - Machine Learning · 4 min ·
[2604.02335] Convolutional Surrogate for 3D Discrete Fracture-Matrix Tensor Upscaling
Machine Learning

[2604.02335] Convolutional Surrogate for 3D Discrete Fracture-Matrix Tensor Upscaling

Abstract page for arXiv paper 2604.02335: Convolutional Surrogate for 3D Discrete Fracture-Matrix Tensor Upscaling

arXiv - Machine Learning · 4 min ·

Should you fear AI?

I think yes. Absolutely. But fear isn't always a bad thing. Think of it like crossing a busy road. Fear is what makes you stop, look, and...

Reddit - Artificial Intelligence · 1 min ·
Experts push AI, human capital integration in national budgeting

Experts push AI, human capital integration in national budgeting

AI News - General · 7 min ·

Meet ‘AutoAgent’: The Open-Source Library That Lets an AI Engineer and Optimize Its Own Agent Harness Overnight

AI News - General · 1 min ·
How AI will redefine workforce skilling & early-career mobility

How AI will redefine workforce skilling & early-career mobility

Artificial Intelligence (AI) is rapidly transforming the way people learn, work, and build careers.For students and young professionals, ...

AI News - General · 4 min ·
Los Angeles Emerges as Major AI Hub With 10 Standout Companies Leading Innovation in 2026

Los Angeles Emerges as Major AI Hub With 10 Standout Companies Leading Innovation in 2026

LOS ANGELES — Once known primarily for Hollywood glamour and entertainment, Los Angeles has solidified its position as a thriving center ...

AI News - General · 10 min ·
AI in newsroom

AI in newsroom

AI News - General · 11 min ·