AI Infrastructure

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...

Siemens, NVIDIA hit chip verification milestone for AI

Dell and HIVE partner to deploy Nvidia’s next-generation AI chips

[2602.16612] Causal and Compositional Abstraction

The paper presents a formal framework for causal and compositional abstraction, emphasizing its significance in AI and scientific practic...

[2602.16603] FlowPrefill: Decoupling Preemption from Prefill Scheduling Granularity to Mitigate Head-of-Line Blocking in LLM Serving

The paper presents FlowPrefill, a novel system designed to optimize large language model (LLM) serving by decoupling preemption from sche...

[2602.16585] DataJoint 2.0: A Computational Substrate for Agentic Scientific Workflows

DataJoint 2.0 introduces a relational workflow model designed to enhance collaboration in scientific data pipelines, ensuring data integr...

[2602.16320] RefineFormer3D: Efficient 3D Medical Image Segmentation via Adaptive Multi-Scale Transformer with Cross Attention Fusion

RefineFormer3D presents a lightweight transformer architecture for 3D medical image segmentation, achieving high accuracy with significan...

[2602.16233] DistributedEstimator: Distributed Training of Quantum Neural Networks via Circuit Cutting

The paper presents a novel approach to distributed training of quantum neural networks using circuit cutting, addressing overheads and pe...

[2602.16430] Designing Production-Scale OCR for India: Multilingual and Domain-Specific Systems

This article discusses the development of production-scale Optical Character Recognition (OCR) systems tailored for India's multilingual ...

[2602.16148] Local adapt-then-combine algorithms for distributed nonsmooth optimization: Achieving provable communication acceleration

This paper introduces FlexATC, a communication-efficient framework for distributed nonsmooth optimization, achieving notable convergence ...

[2602.16132] CHAI: CacHe Attention Inference for text2video

The paper presents CHAI, a novel approach to enhance text-to-video generation by utilizing Cache Attention for efficient inference, achie...

[2602.16113] Evolutionary Context Search for Automated Skill Acquisition

The paper presents Evolutionary Context Search (ECS), a novel method for automated skill acquisition in large language models, enhancing ...

[2602.16086] LGQ: Learning Discretization Geometry for Scalable and Stable Image Tokenization

The paper presents LGQ, a novel image tokenizer that learns discretization geometry to enhance scalability and stability in visual genera...

[2602.16054] CLAA: Cross-Layer Attention Aggregation for Accelerating LLM Prefill

The paper introduces Cross-Layer Attention Aggregation (CLAA) to enhance the efficiency of long-context LLM inference by addressing token...

[2602.16174] Edge Learning via Federated Split Decision Transformers for Metaverse Resource Allocation

The paper presents Federated Split Decision Transformers (FSDT) for optimizing resource allocation in mobile edge computing for the metav...

[2602.15996] Exploring New Frontiers in Vertical Federated Learning: the Role of Saddle Point Reformulation

This paper explores saddle point reformulation in Vertical Federated Learning (VFL), presenting methods for efficient model training acro...

[2602.16136] Retrieval Collapses When AI Pollutes the Web

The paper discusses the phenomenon of 'Retrieval Collapse,' where AI-generated content dominates search results, leading to a decline in ...

[2602.16124] Rethinking ANN-based Retrieval: Multifaceted Learnable Index for Large-scale Recommendation System

The paper presents a novel approach called MultiFaceted Learnable Index (MFLI) for enhancing ANN-based retrieval in large-scale recommend...

[2602.15894] Quality-constrained Entropy Maximization Policy Optimization for LLM Diversity

This paper presents Quality-constrained Entropy Maximization Policy Optimization (QEMPO), a method to enhance diversity in large language...

[2602.15891] Learning to Drive in New Cities Without Human Demonstrations

This paper presents NOMAD, a novel approach for training autonomous vehicles to navigate new cities without relying on human driving demo...

[2602.16005] ODYN: An All-Shifted Non-Interior-Point Method for Quadratic Programming in Robotics and AI

The paper introduces ODYN, a novel non-interior-point method for quadratic programming, designed for efficiency in robotics and AI applic...

[2602.15874] P-RAG: Prompt-Enhanced Parametric RAG with LoRA and Selective CoT for Biomedical and Multi-Hop QA

The paper introduces P-RAG, a novel hybrid architecture that enhances Retrieval-Augmented Generation (RAG) for biomedical question answer...

[2602.15945] From Tool Orchestration to Code Execution: A Study of MCP Design Choices

This paper explores the design choices of Model Context Protocols (MCPs) and introduces Code Execution MCP (CE-MCP) as a solution to scal...