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Mitigating Error Amplification in Fast Adversarial Training

arXiv:2604.24332v1 Announce Type: new Abstract: Fast Adversarial Training (FAT) has proven effective in enhancing model robustness by encouraging networks to learn perturbation-invariant representatio

tutorialsarxiv-cs-lg

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Multi-Scale Contrastive Learning for Video Temporal Grounding

DGX agent

arXiv:2412.07157v3 Announce Type: replace Abstract: Temporal grounding, which localizes video moments related to a natural language query, is a core problem of vision-language learning and video under

researcharxiv-cs-cv

28 Apr 2026

Multimodal QUD: Inquisitive Questions from Scientific Figures

arXiv:2604.23733v1 Announce Type: new Abstract: Asking inquisitive questions while reading, and looking for their answers, is an important part in human discourse comprehension, curiosity, and creativ

Hardware

Now Available on Qdrant Cloud: GPU Indexing, Multi-AZ, and Audit Logging

Now Available on Qdrant Cloud: GPU Indexing, Multi-AZ, and Audit Logging We’re excited to announce some Qdrand Cloud upgrades to address AI workloads that write continuously, must meet higher uptime S

hardwareqdrant

NVIDIA Nemotron 3 Nano Omni Powers Multimodal Agent Reasoning in a Single Efficient Open Model

model-releasesnvidia-developer

NVIDIA Nemotron 3 Nano Omni is a 30B hybrid mixture-of-experts model that brings multimodal perception and reasoning into a single system, natively supporting text, image, video, and audio inputs whil

NVILA: Efficient Frontier Visual Language Models

arXiv:2412.04468v3 Announce Type: replace Abstract: Visual language models (VLMs) have made significant advances in accuracy in recent years. However, their efficiency has received much less attention

Perfecting Aircraft Maneuvers with Reinforcement Learning

arXiv:2604.24338v1 Announce Type: new Abstract: This paper evaluates an advanced jet trainer's utilization of artificial intelligence (AI)-based aircraft aerobatic maneuvers with the intention of deve

Personality Shapes Gender Bias in Persona-Conditioned LLM Narratives Across English and Hindi: An Empirical Investigation

arXiv:2604.23600v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in persona-driven applications such as education, customer service, and social platforms, where m

safetyarxiv-cs-cl

Phenom adds Plum psychometric science to its agentic AI hiring stack

Artificial intelligence-based human resources company Phenom People Inc. announced today that it has acquired Plum.io Inc., a psychometric-based talent assessments company that measures the durable sk

agentssiliconangle

PhySE: A Psychological Framework for Real-Time AR-LLM Social Engineering Attacks

arXiv:2604.23148v1 Announce Type: new Abstract: The emerging threat of AR-LLM-based Social Engineering (AR-LLM-SE) attacks (e.g. SEAR) poses a significant risk to real-world social interactions. In su

agentsarxiv-cs-ai

Propagation Structure-Semantic Transfer Learning for Robust Fake News Detection

arXiv:2604.23974v1 Announce Type: new Abstract: Fake news generally refers to false information that is spread deliberately to deceive people, which has detrimental social effects. Existing fake news

tutorialsarxiv-cs-cl

Radiomics- and Clinical Feature-Driven Prediction of Volumetric Response in Skull-Base Meningioma after CyberKnife Radiosurgery

arXiv:2604.24230v1 Announce Type: new Abstract: Skull-base meningiomas are often characterized by favorable long-term prognosis, yet their anatomical complexity and proximity to critical neurovascular

Reducing Redundancy in Retrieval-Augmented Generation through Chunk Filtering

arXiv:2604.24334v1 Announce Type: new Abstract: Standard Retrieval-Augmented Generation (RAG) chunking methods often create excessive redundancy, increasing storage costs and slowing retrieval. This s

Reheat Nachos for Dinner? Evaluating AI Support for Cross-Cultural Communication of Neologisms

arXiv:2604.23842v1 Announce Type: cross Abstract: Neologisms and emerging slang are central to daily conversation, yet challenging for non-native speakers (NNS) to interpret and use appropriately in c

tutorialsarxiv-cs-ai

Safe Navigation in Unknown and Cluttered Environments via Direction-Aware Convex Free-Region Generation

arXiv:2604.23648v1 Announce Type: new Abstract: Convex free regions provide a structured and optimization-friendly representation of collision-free space for robot navigation in unknown and cluttered

safetyarxiv-cs-ro

SAGE: Sparse Adaptive Guidance for Dependency-Aware Tabular Data Generation

arXiv:2604.24368v1 Announce Type: new Abstract: Generating high-fidelity synthetic tabular data remains a critical challenge for enhancing data availability in privacy-sensitive and low-resource domai

safetyarxiv-cs-lg

SemiSAM-O1: How far can we push the boundary of annotation-efficient medical image segmentation?

arXiv:2604.24109v1 Announce Type: new Abstract: Semi-supervised learning (SSL) has become a promising solution to alleviate the annotation burden of deep learning-based medical image segmentation mode

Shallow Neural Networks Learn Low-Degree Spherical Polynomials with Feature Learning by Learnable Channel Attention

arXiv:2512.20562v2 Announce Type: replace-cross Abstract: We study the problem of learning a low-degree spherical polynomial of degree ell_0 = Theta(1) ge 1 defined on the unit sphere in RR^d by train

tutorialsarxiv-cs-lg

Skill Retrieval Augmentation for Agentic AI

model-releasesarxiv-cs-ai

arXiv:2604.24594v1 Announce Type: cross Abstract: As large language models (LLMs) evolve into agentic problem solvers, they increasingly rely on external, reusable skills to handle tasks beyond their

SPEAR-1: Scaling Beyond Robot Demonstrations via 3D Understanding

arXiv:2511.17411v2 Announce Type: replace-cross Abstract: Robotic Foundation Models (RFMs) hold great promise as generalist, end-to-end systems for robot control. Yet their ability to generalize acros

Spectro-Temporal Modulation Representation Framework for Human-Imitated Speech Detection

arXiv:2604.23241v1 Announce Type: cross Abstract: Human-imitated speech poses a greater challenge than AI-generated speech for both human listeners and automatic detection systems. Unlike AI-generated

Stabilizing Efficient Reasoning with Step-Level Advantage Selection

model-releasesarxiv-cs-cl

arXiv:2604.24003v1 Announce Type: new Abstract: Large language models (LLMs) achieve strong reasoning performance by allocating substantial computation at inference time, often generating long and ver

Tessera: Secure, Near-Line-Rate Weight Streaming for UMA Edge Accelerators

arXiv:2604.23205v1 Announce Type: cross Abstract: Deploying proprietary Deep Neural Networks (DNNs) on commodity edge devices demands hardware-backed Digital Rights Management (DRM) capable of withsta

🆕 Today, we're releasing the public preview of Workflows, the orchestration layer for enterprise AI. 🌎 Enterprise teams have capable model…

applicationsmistral-ai--x

🆕 Today, we're releasing the public preview of Workflows, the orchestration layer for enterprise AI. 🌎 Enterprise teams have capable models. What they don't have is a way to run them reliably in produ

Towards High-Fidelity CAD Generation via LLM-Driven Program Generation and Text-Based B-Rep Primitive Grounding

arXiv:2603.11831v2 Announce Type: replace Abstract: The field of Computer-Aided Design (CAD) generation has made significant progress in recent years. Existing methods typically fall into two separate

applicationsarxiv-cs-cv

Understanding Representation Gaps Across Scales in Tropical Tree Species Classification from Drone Imagery

arXiv:2604.23019v1 Announce Type: new Abstract: Accurate classification of tropical tree species from unoccupied aerial vehicle (UAV) imagery remains challenging due to high species diversity and stro

safetyarxiv-cs-cv

Universal approximation property of Banach space-valued random feature models including random neural networks

arXiv:2312.08410v5 Announce Type: replace Abstract: We introduce a Banach space-valued extension of random feature learning, a data-driven supervised machine learning technique for large-scale kernel

tutorialsarxiv-cs-lg

Welcome to the agentic era: Public sector highlights and reflections from Next ‘26

model-releasesgoogle-cloud-ai

Welcome to the agentic era! Last week, leaders from our public sector customer and partner ecosystem took the stage at Google Cloud Next to share how they are leveraging AI and agents to scale their i

When AI reviews science: Can we trust the referee?

arXiv:2604.23593v1 Announce Type: new Abstract: The volume of scientific submissions continues to climb, outpacing the capacity of qualified human referees and stretching editorial timelines. At the s

tutorialsarxiv-cs-ai

Your Reviews Replicate You: LLM-Based Agents as Customer Digital Twins for Conjoint Analysis

arXiv:2604.22756v1 Announce Type: cross Abstract: Conjoint analysis is a cornerstone of market research for estimating consumer preferences; however, traditional methods face persistent challenges reg

applicationsarxiv-cs-ai

A Brain-Inspired Deep Separation Network for Single Channel Raman Spectra Unmixing

arXiv:2604.22324v1 Announce Type: new Abstract: Raman spectra obtained in real world applications are often a noisy combination of several spectra of various substances in a tested sample. Unmixing su

applicationsarxiv-cs-lg

A Nationwide Japanese Medical Claims Foundation Model: Balancing Model Scaling and Task-Specific Computational Efficiency

arXiv:2604.22348v1 Announce Type: new Abstract: Clinical risk prediction using longitudinal medical data supports individualized care. Self-supervised foundation models have emerged as a promising app

applicationsarxiv-cs-lg

Adapting MLLMs for Nuanced Video Retrieval

arXiv:2512.13511v2 Announce Type: replace Abstract: Our objective is to build an embedding model that captures the nuanced relationship between a search query and candidate videos. We cover three aspe

An End-to-End Ukrainian RAG for Local Deployment. Optimized Hybrid Search and Lightweight Generation

arXiv:2604.22095v1 Announce Type: new Abstract: This paper presents a highly efficient Retrieval-Augmented Generation (RAG) system built specifically for Ukrainian document question answering, which a

Build Strands Agents with SageMaker AI models and MLflow

In this post, we demonstrate how to build AI agents using Strands Agents SDK with models deployed on SageMaker AI endpoints. You will learn how to deploy foundation models from SageMaker JumpStart, in

agentsaws-ml-blog

Can Large Language Models Adequately Perform Symbolic Reasoning Over Time Series?

model-releasesarxiv-cs-ai

arXiv:2508.03963v4 Announce Type: replace Abstract: Uncovering hidden symbolic laws from time series data, as an aspiration dating back to Kepler's discovery of planetary motion, remains a core challe

Cloud cost optimization becomes an enterprise mandate as AI bills spiral

As AI rapidly rewrites enterprise economics, cloud cost optimization has become essential for preventing budgets from collapsing under AI workloads, enabling organizations to slash expenses and redire

applicationssiliconangle

Conditional anomaly detection using soft harmonic functions: An application to clinical alerting

arXiv:2604.21956v1 Announce Type: new Abstract: Timely detection of concerning events is an important problem in clinical practice. In this paper, we consider the problem of conditional anomaly detect

applicationsarxiv-cs-lg

Decomposed Attention Fusion in MLLMs for Training-Free Video Reasoning Segmentation

arXiv:2510.19592v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) demonstrate strong video understanding by attending to visual tokens relevant to textual queries. To direct

Evaluating LLM-Based Goal Extraction in Requirements Engineering: Prompting Strategies and Their Limitations

arXiv:2604.22207v1 Announce Type: cross Abstract: Due to the textual and repetitive nature of many Requirements Engineering (RE) artefacts, Large Language Models (LLMs) have proven useful to automate

researcharxiv-cs-ai

FMSD-TTS: Few-shot Multi-Speaker Multi-Dialect Text-to-Speech Synthesis for U-Tsang, Amdo and Kham Speech Dataset Generation

arXiv:2505.14351v4 Announce Type: replace-cross Abstract: Tibetan is a low-resource language with minimal parallel speech corpora spanning its three major dialects-U-Tsang, Amdo, and Kham-limiting pro

researcharxiv-cs-ai

Iterative Model-Learning Scheme via Gaussian Processes for Nonlinear Model Predictive Control of (Semi-)Batch Processes

arXiv:2604.22672v1 Announce Type: new Abstract: Batch processes are inherently transient and typically nonlinear, motivating nonlinear model predictive control (NMPC). However, adopting NMPC is hinder

LLM+Graph@VLDB'2025 Workshop Summary

arXiv:2604.02861v2 Announce Type: replace-cross Abstract: The integration of large language models (LLMs) with graph-structured data has become a pivotal and fast evolving research frontier, drawing s

researcharxiv-cs-ai

NeuronMLP: Efficient LLM Inference via Singular Value Decomposition Compression and Tiling on AWS Trainium

arXiv:2510.25977v4 Announce Type: replace Abstract: Emerging AI accelerators have started to gain attention and offer new opportunities for efficient inference of large language models (LLMs). Trainiu

Optimal Lower Bounds for Online Multicalibration

arXiv:2601.05245v2 Announce Type: replace Abstract: We prove tight lower bounds for online multicalibration, establishing an information-theoretic separation from marginal calibration. In the general

Rebuilding the data stack for AI

applicationsmit-tech-review

Artificial intelligence may be dominating boardroom agendas, but many enterprises are discovering that the biggest obstacle to meaningful adoption is the state of their data. While consumer-facing AI

Source-Modality Monitoring in Vision-Language Models

arXiv:2604.22038v1 Announce Type: new Abstract: We define and investigate source-modality monitoring -- the ability of multimodal models to track and communicate the input source from which pieces of

agentsarxiv-cs-cl

Hardware

Toward Robust and Efficient ML-Based GPU Caching for Modern Inference

arXiv:2509.20979v2 Announce Type: replace Abstract: In modern GPU inference, cache efficiency remains a major bottleneck, and heuristic policies such as extsc{LRU} can perform far worse than the offli

hardwarearxiv-cs-lg