Search: “applications”

The Costs of Pretending That There Are Data-Generating Probability Distributions in the Social World

arXiv:2407.17395v5 Announce Type: replace Abstract: Machine Learning research, including work promoting fair or equitable algorithms, often relies on the concept of a data-generating probability distr

tutorialsarxiv-cs-lg

Research

The effect of the number of parameters and the number of local feature patches on loss landscapes in distributed quantum neural networks

DGX agent

arXiv:2504.19239v2 Announce Type: replace-cross Abstract: Quantum neural networks hold promise for tackling computationally challenging tasks that are intractable for classical computers. However, the

researcharxiv-cs-lg

23 Apr 2026

The OpenHands Software Agent SDK: A Composable and Extensible Foundation for Production Agents

arXiv:2511.03690v2 Announce Type: replace-cross Abstract: Agents are now used widely in the process of software development, but building production-ready software engineering agents is a complex task

Throat and acoustic paired speech dataset for deep learning-based speech enhancement

arXiv:2502.11478v3 Announce Type: replace-cross Abstract: In high-noise environments such as factories, subways, and busy streets, capturing clear speech is challenging. Throat microphones can offer a

safetyarxiv-cs-lg

Top 10 uses for Codex at work

Codex is OpenAI's AI model designed to understand and generate code, helping developers automate programming tasks and improve productivity. This guide from OpenAI likely outlines ten practical workpl

model-releasesopenai

Toward Cooperative Driving in Mixed Traffic: An Adaptive Potential Game-Based Approach with Field Test Verification

arXiv:2604.20231v1 Announce Type: new Abstract: Connected autonomous vehicles (CAVs), which represent a significant advancement in autonomous driving technology, have the potential to greatly increase

safetyarxiv-cs-ro

Trajectory2Task: Training Robust Tool-Calling Agents with Synthesized Yet Verifiable Data for Complex User Intents

model-releasesarxiv-cs-cl

arXiv:2601.20144v3 Announce Type: replace Abstract: Tool-calling agents are increasingly deployed in real-world customer-facing workflows. Yet most studies on tool-calling agents focus on idealized se

Transparent Screening for LLM Inference and Training Impacts

arXiv:2604.19757v1 Announce Type: cross Abstract: This paper presents a transparent screening framework for estimating inference and training impacts of current large language models under limited obs

researcharxiv-cs-ai

UCCL-Zip: Lossless Compression Supercharged GPU Communication

arXiv:2604.17172v2 Announce Type: replace-cross Abstract: The rapid growth of large language models (LLMs) has made GPU communication a critical bottleneck. While prior work reduces communication volu

WebGen-R1: Incentivizing Large Language Models to Generate Functional and Aesthetic Websites with Reinforcement Learning

model-releasesarxiv-cs-cl

arXiv:2604.20398v1 Announce Type: new Abstract: While Large Language Models (LLMs) excel at function-level code generation, project-level tasks such as generating functional and visually aesthetic mul

Weighted Knowledge Distillation for Semi-Supervised Segmentation of Maxillary Sinus in Panoramic X-ray Images

arXiv:2604.20213v1 Announce Type: new Abstract: Accurate segmentation of maxillary sinus in panoramic X-ray images is essential for dental diagnosis and surgical planning; however, this task remains r

What is Codex?

Codex is OpenAI's AI model specialized in understanding and generating code across multiple programming languages. Based on OpenAI's documentation, it likely explains Codex's capabilities for code com

tutorialsopenai

White-Basilisk: A Hybrid Model for Code Vulnerability Detection

arXiv:2507.08540v5 Announce Type: replace-cross Abstract: The proliferation of software vulnerabilities presents a significant challenge to cybersecurity, necessitating more effective detection method

10 months ago, our CPO @walden_yan argued not to build multi-agent systems. Today, the landscape is different, and we've implemented a few s…

Cognition AI's Chief Product Officer Walden Yan previously advised against building multi-agent systems, but the company has since changed its position based on evolving market conditions and technica

agentscognition-ai--x

A neural operator framework for data-driven discovery of stability and receptivity in physical systems

arXiv:2604.19465v1 Announce Type: cross Abstract: Understanding how complex systems respond to perturbations, such as whether they will remain stable or what their most sensitive patterns are, is a fu

researcharxiv-cs-ai

AI-Based Detection of Temporal Changes in MR-Linac Images Acquired During Routine Prostate Radiotherapy

arXiv:2602.04983v2 Announce Type: replace-cross Abstract: Purpose: To investigate whether an AI-based method can detect subtle inter-fraction changes in MR-Linac images acquired during radiotherapy an

researcharxiv-cs-ai

An Experimental Characterization of Mechanical Layer Jamming Systems

model-releasesarxiv-cs-ro

arXiv:2511.07882v2 Announce Type: replace Abstract: Organisms in nature, such as Cephalopods and Pachyderms, exploit stiffness modulation to achieve amazing dexterity in the control of their appendage

Industry

Are LLM agents good at join order optimization?

This Databricks article examines whether Large Language Model agents can effectively optimize SQL join order, a critical query optimization problem in database systems. The analysis likely evaluates L

industrydatabricks

Article and Comment Frames Shape the Quality of Online Comments

arXiv:2603.27889v2 Announce Type: replace Abstract: Framing theory posits that how information is presented shapes audience responses, but computational work has largely ignored audience reactions. Wh

researcharxiv-cs-cl

Industry

As EV batteries improve, ChargePoint debuts 600 kW fast charger

ChargePoint has unveiled the ChargePoint Express Grid, powered by Eaton, a vehicle-to-everything capable solution that delivers up to 600 kW of power for passenger EVs and megawatt charging for heavy-

industryars-technica

Centralized Copy-Paste: Enhanced Data Augmentation Strategy for Wildland Fire Semantic Segmentation

arXiv:2507.06321v2 Announce Type: replace Abstract: Collecting and annotating images for the purpose of training segmentation models is often cost prohibitive. In the domain of wildland fire science,

CityRAG: Stepping Into a City via Spatially-Grounded Video Generation

arXiv:2604.19741v1 Announce Type: new Abstract: We address the problem of generating a 3D-consistent, navigable environment that is spatially grounded: a simulation of a real location. Existing video

agentsarxiv-cs-cv

Local Ai

COMODO: Cross-Modal Video-to-IMU Distillation for Efficient Egocentric Human Activity Recognition

arXiv:2503.07259v2 Announce Type: replace-cross Abstract: The goal of creating intelligent, human-centered wearable systems for continuous activity understanding faces a fundamental trade-off: Egocent

local-aiarxiv-cs-ai

Industry

CrowdStrike brings real-time Cloud Detection and Response to Google Cloud

CrowdStrike Holdings Inc. today expanded its Cloud Detection and Response service to Google Cloud Platform, adding runtime protection for Google workloads as attackers lean on artificial intelligence

industrysiliconangle

DADA: Dual Averaging with Distance Adaptation

arXiv:2501.10258v2 Announce Type: replace-cross Abstract: We present a novel universal gradient method for solving convex optimization problems. Our algorithm, Dual Averaging with Distance Adaptation

Disentangling Damage from Operational Variability: A Label-Free Self-Supervised Representation Learning Framework for Output-Only Structural Damage Identification

arXiv:2604.19658v1 Announce Type: new Abstract: Damage identification is a core task in structural health monitoring. In practice, however, its reliability is often compromised by confounding non-dama

tutorialsarxiv-cs-lg

Dynamic Model Routing and Cascading for Efficient LLM Inference: A Survey

arXiv:2603.04445v2 Announce Type: replace-cross Abstract: The rapid growth of large language models (LLMs) with diverse capabilities, costs, and domains has created a critical need for intelligent mod

researcharxiv-cs-cl

Efficient Autoregressive Inference for Transformer Probabilistic Models

arXiv:2510.09477v2 Announce Type: replace-cross Abstract: Set-based transformer models for amortized probabilistic inference and meta-learning, such as neural processes, prior-fitted networks, and tab

Energy-Weighted Flow Matching: Unlocking Continuous Normalizing Flows for Efficient and Scalable Boltzmann Sampling

model-releasesarxiv-cs-lg

arXiv:2509.03726v2 Announce Type: replace-cross Abstract: Sampling from unnormalized target distributions, e.g. Boltzmann distributions mu_{ext{target}}(x) propto exp(-E(x)/T), is fundamental to many

Enforcing Reciprocity in Operator Learning for Seismic Wave Propagation

arXiv:2602.11631v2 Announce Type: replace-cross Abstract: Accurate and efficient wavefield modeling underpins seismic structure and source studies. Traditional methods comply with physical laws but ar

EPS: Efficient Patch Sampling for Video Overfitting in Deep Super-Resolution Model Training

arXiv:2411.16312v2 Announce Type: replace Abstract: Leveraging the overfitting property of deep neural networks (DNNs) is trending in video delivery systems to enhance video quality within bandwidth l

Evaluation of Winning Solutions of 2025 Low Power Computer Vision Challenge

arXiv:2604.19054v1 Announce Type: new Abstract: The IEEE Low-Power Computer Vision Challenge (LPCVC) aims to promote the development of efficient vision models for edge devices, balancing accuracy wit

FairTree: Subgroup Fairness Auditing of Machine Learning Models with Bias-Variance Decomposition

arXiv:2604.19357v1 Announce Type: new Abstract: The evaluation of machine learning models typically relies mainly on performance metrics based on loss functions, which risk to overlook changes in perf

safetyarxiv-cs-lg

FedSEA: Achieving Benefit of Parallelization in Federated Online Learning

arXiv:2604.19336v1 Announce Type: new Abstract: Online federated learning (OFL) has emerged as a popular framework for decentralized decision-making over continuous data streams without compromising c

Fine-tuning DeepSeek-OCR-2 for Molecular Structure Recognition

arXiv:2604.03476v2 Announce Type: replace-cross Abstract: Optical Chemical Structure Recognition (OCSR) is critical for converting 2D molecular diagrams from printed literature into machine-readable f

Framelet-Based Blind Image Restoration with Minimax Concave Regularization

arXiv:2604.19314v1 Announce Type: new Abstract: Recovering corrupted images is one of the most challenging problems in image processing. Among various restoration tasks, blind image deblurring has bee

safetyarxiv-cs-cv

From Natural Language to Executable Narsese: A Neuro-Symbolic Benchmark and Pipeline for Reasoning with NARS

arXiv:2604.18873v1 Announce Type: new Abstract: Large language models (LLMs) are highly capable at language generation, but they remain unreliable when reasoning requires explicit symbolic structure,

GeoLaux: A Benchmark for Evaluating MLLMs' Geometry Performance on Long-Step Problems Requiring Auxiliary Lines

arXiv:2508.06226v2 Announce Type: replace Abstract: Geometry problem solving (GPS) poses significant challenges for Multimodal Large Language Models (MLLMs) in diagram comprehension, knowledge applica

Get more from speculative decoding in MoE models https://cohere.link/Et2rbsB

Speculative decoding is a technique that accelerates language model inference by using a smaller draft model to generate candidate tokens, which are then verified by a larger model, reducing latency w

model-releasescohere--x

Global Optimization of Gaussian Process Acquisition Functions Using a Piecewise-Linear Kernel Approximation

arXiv:2410.16893v3 Announce Type: replace-cross Abstract: Bayesian optimization relies on iteratively constructing and optimizing an acquisition function. The latter turns out to be a challenging, non

Local Ai

HardNet++: Nonlinear Constraint Enforcement in Neural Networks

arXiv:2604.19669v1 Announce Type: new Abstract: Enforcing constraint satisfaction in neural network outputs is critical for safety, reliability, and physical fidelity in many control and decision-maki

local-aiarxiv-cs-lg

Introducing Anyscale Agent Skills: Build faster, debug smarter, and optimize AI workloads running on Ray

Anyscale Agent Skills is a framework built on Ray that enables developers to build AI agents more efficiently with improved debugging capabilities and workload optimization. The tool likely provides a

agentsanyscale-ray

Introducing Gemini Enterprise Agent Platform, powering the next wave of agents

model-releasesgoogle-cloud-ai

In the early days of generative AI, building safe and reliable business tools took massive engineering effort and a high tolerance for trial and error. We helped solve that with Vertex AI, our trusted

Introducing the Google Cloud Knowledge Catalog

model-releasesgoogle-cloud-ai

Traditional data catalogs were built as manual inventories for technical users, focusing on table structures rather than the deep context that AI agents need. When agents lack business semantics and d

>LangChain gives you testing tools. It never tells you what to test, in what order, or when you're done. This is changing soon Launching May…

LangChain is introducing new testing tools and capabilities that will help developers with test guidance, organization, and completion criteria—moving beyond just providing testing infrastructure to a

agentsharrison-chase--x

Latent Linear Quadratic Regulator for Robotic Control Tasks

arXiv:2407.11107v3 Announce Type: replace-cross Abstract: Model predictive control (MPC) has played a more crucial role in various robotic control tasks, but its high computational requirements are co

tutorialsarxiv-cs-lg

Making ChatGPT better for clinicians

OpenAI describes improvements and adaptations made to ChatGPT to better serve clinical and healthcare professionals. The work likely addresses how the model can be made more reliable, accurate, and us

model-releasesopenai

MiTA Attention: Efficient Fast-Weight Scaling via a Mixture of Top-k Activations

arXiv:2602.01219v4 Announce Type: replace-cross Abstract: The attention operator in Transformers can be viewed as a two-layer fast-weight MLP, whose weights are dynamically instantiated from input tok