applications

HiSAC: Hierarchical Sparse Activation Compression for Ultra-long Sequence Modeling in Recommenders

arXiv:2602.21009v2 Announce Type: replace-cross Abstract: Modern recommender systems leverage ultra-long user behavior sequences to capture dynamic preferences, but end-to-end modeling is infeasible i

applicationsarxiv-cs-cl

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Applications

How AWS Finance teams reclaimed hundreds of hours with Amazon Quick

DGX agent

AWS Finance used Amazon Quick chat agents and Flows to automate two major time-consuming workflows: financial target setting and weekly business reviews. The automation reduced target-setting time fro

applicationsaws-ml-blog

7 Jul 2026

HUGS: Guiding Unified Dexterous Grasp Synthesis Across Modes and Scales via Learned Human Priors

arXiv:2607.04554v1 Announce Type: new Abstract: Dexterous grasping across diverse object scales requires contact modes ranging from two-finger pinches to bimanual grasps. Existing dexterous grasp synt

Hybrid Deep Learning for Traceability and Classification of Industrial Slate Tiles

arXiv:2607.04811v1 Announce Type: new Abstract: Applying deep learning to instance-aware reidentification of slate tiles and extraction site classification can improve production efficiency and qualit

I have been playing these world models/games since the first diffusion DOOM, and multiplayer at 20 FPS is pretty neat. 'A dream of rocket le…

applicationsethan-mollick--x

I have been playing these world models/games since the first diffusion DOOM, and multiplayer at 20 FPS is pretty neat. 'A dream of rocket league,' indeed. Introducing MIRA. A playable, multiplayer wor

IBIS: A Hybrid Inception-BiLSTM and SVM Ensemble for Robust Doppler-based Human Activity Recognition

arXiv:2510.24936v3 Announce Type: replace Abstract: Wi-Fi sensing is a leading technology for Human Activity Recognition (HAR), offering a non-intrusive and cost-effective solution for healthcare and

IBM debuts compact z17 mainframes and LinuxONE servers for on-premises enterprise AI

IBM Corp. today announced a massive expansion of its on-premises enterprise infrastructure lineup, with new single-frame and rack-mount versions of its iconic z17 mainframes and more compact LinuxONE

applicationssiliconangle

Identifiability of Relational Queries in Multi-View Pretraining

arXiv:2607.04735v1 Announce Type: cross Abstract: When data sources are integrated through a shared interface, a downstream query may or may not be determined by what the interface exposes: two global

!Imperio, smolVLA: The Implications of Data Poisoning on Open Source Robotics

arXiv:2607.04146v1 Announce Type: cross Abstract: This work establishes that trigger-word data poisoning of vision language action models is practical, while at the same time the open-source robotics

ImputeECG: Deep Learning Reconstruction of Complete 12-Lead Electrocardiograms from Incomplete Recordings for Cardiac Assessment

arXiv:2607.05009v1 Announce Type: cross Abstract: Complete digital 12-lead electrocardiograms (ECGs) are essential for AI-enabled cardiovascular assessment, yet many clinical ECG records, particularly

Invisible Strings: Deriving Puppetry Principles and their Hidden Connections to Robot Behavior Design

arXiv:2607.03289v1 Announce Type: new Abstract: When designing robots' nonverbal behaviors, many researchers have turned to arts-based insights, such as Disney's Animation Principles. Yet, while these

Joint distribution of upstream runoff governs downstream river-discharge prediction uncertainty in distributed ML models

arXiv:2607.03217v1 Announce Type: new Abstract: Uncertainty quantification of hydrological predictions is necessary to inform operational decisions. Recent generative machine-learning methods have adv

karl. -- A Research Vehicle for Automated and Connected Driving

arXiv:2602.08842v3 Announce Type: replace-cross Abstract: As highly automated driving is transitioning from single-vehicle closed-access testing to commercial deployments of public ride-hailing in sel

Knowledge-Centric Information Systems

arXiv:2607.02609v1 Announce Type: cross Abstract: For decades, data engineering has developed mature architectural principles for integrating, governing, validating, cataloging, and serving organizati

Knowledge-Informed Local Causal Discovery of Optimal Adjustment Sets

arXiv:2607.04447v1 Announce Type: new Abstract: Local causal discovery is a scalable alternative to global structure learning. However, it can struggle to identify valid adjustment sets in data-scarce

Labeled-Data-Free Meta-Learning: Efficient Task Generation Using Pre-trained Models and Unlabeled Data

arXiv:2607.02850v1 Announce Type: new Abstract: Meta-learning without labeled data is crucial for real-world applications, where obtaining labeled datasets can be expensive or restricted due to privac

Last Layer Hamiltonian Monte Carlo

arXiv:2507.08905v2 Announce Type: replace-cross Abstract: We explore the use of Hamiltonian Monte Carlo (HMC) sampling as a probabilistic last layer approach for deep neural networks (DNNs). While HMC

Layout-independent actuation allocator for fin-actuated marine robots

arXiv:2607.03204v1 Announce Type: new Abstract: In this study, we propose a layout-independent control allocator capable of zero-shot deployment across diverse actuator configurations. The proposed me

Learning Flexible Generalization in Video Quality Assessment by Bringing Device and Viewing Condition Distributions

arXiv:2607.04643v1 Announce Type: new Abstract: Video quality assessment (VQA) plays a critical role in optimizing video delivery systems. While numerous objective metrics have been proposed to approx

Learning to Discover Iterative Spectral Algorithms

arXiv:2602.09530v2 Announce Type: replace-cross Abstract: We introduce AutoSpec, a neural network framework for discovering iterative spectral algorithms for large-scale numerical linear algebra and n

LLM-Enhanced Hierarchical Heterogeneous Graph Representation Learning for Malicious Python Package Detection

arXiv:2607.03350v1 Announce Type: cross Abstract: Malicious Python packages have become a major threat to software supply chain ecosystems due to the widespread adoption of open-source repositories su

LOTUSim: Multi-Domain Simulator for Marine Robotics

arXiv:2607.03072v1 Announce Type: cross Abstract: Simulation is essential for maritime robotics, supporting operator training, mission rehearsal, and human-vehicle interaction in environments where re

Machine Learning for Depression Screening and Intervention: an Original Circadian Rhythm Score-based Methodology

arXiv:2607.04648v1 Announce Type: cross Abstract: Depression screening from large-scale behavioral data is challenged by fragmented circadian indicators, limited interpretability, and the lack of inte

MACRO: Training-free Multi-plane Attention for Closeup Render Optimization

arXiv:2607.03875v1 Announce Type: new Abstract: Close-up rendering, zooming into a scene well beyond any training camera, is important for virtual production and interactive 3D content, yet remains an

MDL Meets Latent Confounders: LNML-based Causal Discovery

arXiv:2607.04133v1 Announce Type: new Abstract: Causal discovery with nonlinear mechanisms and latent confounders remains challenging. Existing methods often rely on either linear assumptions or causa

Measuring the Robustness of Audio Deepfake Detection under Real-World Corruption

arXiv:2503.17577v2 Announce Type: replace-cross Abstract: Deepfakes have emerged as a widespread and rapidly escalating concern in generative AI, spanning images, audio, and videos. Among these, audio

MetaCaDI: A Meta-Learning Framework for Causal Discovery from Multiple Environments with Unknown Interventions

arXiv:2510.22298v2 Announce Type: replace-cross Abstract: Uncovering the causal mechanisms of complex real-world systems remains a significant challenge, as these systems often entail high data collec

MetricAnything: Scaling Metric Depth Pretraining with Noisy Heterogeneous Sources

arXiv:2601.22054v2 Announce Type: replace-cross Abstract: Scaling has powered recent advances in vision foundation models, yet extending this paradigm to metric depth estimation remains challenging du

MIRAGE: Defending Long-Form RAG Against Misinformation Pollution

arXiv:2607.05069v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) improves factuality by grounding LLMs in external evidence, but real-world retrieval is often polluted: semanticall

applicationsarxiv-cs-cl

MOSAIC: Skill-Centric Manipulation Planning with Physics Simulation

arXiv:2504.16738v3 Announce Type: replace-cross Abstract: Planning long-horizon manipulation motions using a set of predefined skills is a central challenge in robotics; solving it efficiently could e

Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales

arXiv:2607.04972v1 Announce Type: cross Abstract: Deploying robot teams in the real world requires simultaneous adaptation to unseen environments, unknown partners, and varying team sizes, yet existin

Norm Ai nabs 120M at 1.2B valuation to bring AI agents to the law

Nomos Ai Inc., a company building a platform to embed legal operations into artificial intelligence agents, today announced it has raised 120 million in new funding, bringing the company’s valuation t

applicationssiliconangle

Norm, which runs an AI law firm that provides AI-powered legal services to clients alongside human lawyers, raised 120M led by Khosla at a 1.2B valuation (Guinevere Grant/Bloomberg)

Guinevere Grant / Bloomberg: Norm, which runs an AI law firm that provides AI-powered legal services to clients alongside human lawyers, raised 120M led by Khosla at a 1.2B valuation — Norm Ai has rai

applicationstechmeme

Occluding the Solution Space: Planner-Agnostic Adversarial Attacks on Tolerance-Aware Manipulation

arXiv:2607.03758v1 Announce Type: new Abstract: Adversarial attacks on motion planning are crucial for evaluating and quantifying the intrinsic robustness of robotic manipulation. However, existing ap

One Framework for All: Cross-Modal Membership Inference for Generative Models

arXiv:2607.04339v1 Announce Type: cross Abstract: Large generative models across text-to-text, text-to-image, and image-to-text modalities have been shown to pose significant privacy risks. One fundam

OpenAI, Anthropic, and other top AI labs are offering startups token credits and special promotions, as the AI labs seek lasting streams of enterprise revenue (Wall Street Journal)

Wall Street Journal: OpenAI, Anthropic, and other top AI labs are offering startups token credits and special promotions, as the AI labs seek lasting streams of enterprise revenue — Pitched battle for

applicationstechmeme

OpFlow: Learning Opportunity-Conditioned Choice Potentials for Robust OD Flow Prediction

arXiv:2607.03200v1 Announce Type: new Abstract: Origin-destination (OD) flow prediction is central to urban analytics, yet deep models trained on raw counts remain vulnerable to distribution shift. Th

P^3: Toward Versatile Embodied Agents

arXiv:2508.07033v2 Announce Type: replace Abstract: Embodied agents have shown promising generalization capabilities across diverse physical environments, making them essential for a wide range of rea

PedestrianDiffusion: Multimodal Generative Denoising and Dense State Estimation for Inertial Navigation

arXiv:2607.03349v1 Announce Type: cross Abstract: The accuracy of consumer-grade inertial navigation is bottlenecked by the stochastic noise of Micro-Electro-Mechanical Systems (MEMS). Traditional det

PLGSA-Transformer: Periocular Landmark-Guided Attention with Occlusion-Adaptive Cosine Thresholding for Cross-Modal Masked and Unmasked Face Recognition

arXiv:2607.03581v1 Announce Type: cross Abstract: The widespread adoption of facial masks, accelerated by COVID-19 and mandated in security-sensitive settings, has exposed limitations of conventional

Present but Not Remembered: Auditing How Frozen VLAs Encode, Deploy, and Steer Visual History

arXiv:2607.03372v1 Announce Type: new Abstract: A frozen vision-language-action model (VLA) receives recent observations at every decision step, yet prior work has focused on adding memory rather than

QuantFlow: A Federated Mamba-Based Post-Transformer Foundation Model for Time-Series Forecasting

arXiv:2607.02632v1 Announce Type: cross Abstract: Time-series forecasting supports decisions in finance, en-ergy, transportation, public health, and industrial monitoring. Recent foundation models imp

REAL-OW: Rehearsal-free Open World Object Detection with Low-Rank Adaptation and Dual-Stage Objectness Modeling

arXiv:2607.03004v1 Announce Type: new Abstract: Open-World Object Detection (OWOD) requires detectors to identify previously unseen objects as unknown and incrementally incorporate them into the set o

Relevance-Based Embeddings: Lightweight Candidate Retrieval via Heavy-Ranker Calls

arXiv:2607.03515v1 Announce Type: cross Abstract: In many machine learning applications, the most relevant items for a query should be efficiently retrieved. The relevance function is usually an expen

Resource-constrained Project Scheduling with Time-of-Use Energy Tariffs and Machine States: A Logic-based Benders Decomposition Approach

arXiv:2601.06542v2 Announce Type: replace-cross Abstract: In this paper, we investigate the Resource-Constrained Project Scheduling Problem (RCPSP) with Time-of-Use (TOU) energy tariffs and machine st

SAVER: Mitigating Hallucinations in Large Vision-Language Models via Style-Aware Visual Early Revision

arXiv:2508.03177v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) recently achieve significant breakthroughs in understanding complex visual-textual contexts. However, hallucina

SE-UNet: Singular Equivariant Imaging for Real-World Constrained Generation

arXiv:2607.02628v1 Announce Type: new Abstract: While diffusion models have revolutionized image synthesis, their application to real-world inverse problems is often hampered by the need for massive d

Semi-parametric Functional Classification via Path Signatures Logistic Regression with Adaptive Order Selection

arXiv:2507.06637v2 Announce Type: replace-cross Abstract: We propose Path Signatures Logistic Regression (PSLR), a semi-parametric framework for classifying vector-valued functional data with scalar c