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Multi-robot Learning-based Informative Path Planning Using Spatio-Temporal Gaussian Process Kalman Filter

arXiv:2609.05515v1 Announce Type: new Abstract: Multi-robot informative path planning (IPP) for persistent target monitoring requires robots to reason about spatial uncertainty, temporal evolution, an

safetyarxiv-cs-ro

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Multi-Task Learning for Sparsely-Labeled Time Series: A Case Study on Cold-Hardiness Modeling

DGX agent

arXiv:2609.09062v1 Announce Type: new Abstract: We present a real-world case study of multi-task learning (MTL) for temporal process modeling from limited data with temporally sparse labels. Specifica

applicationsarxiv-cs-lg

9 Sept 2026

Multi-Task Learning with Covariate-Overlap Regularization

arXiv:2505.24281v2 Announce Type: replace-cross Abstract: Multi-task learning improves data efficiency by sharing information across related tasks, but indiscriminate sharing can be harmful when their

Multimodal Resource-Exhaustion Attacks on Vision-Language Models via Joint Pixel-Prompt Optimization

arXiv:2609.05889v1 Announce Type: cross Abstract: Resource-exhaustion attacks against autoregressive vision-language models (VLMs) typically assume unimodal threat models, treating the image branch as

Multiple Myeloma Lesion Segmentation on Whole-Body Diffusion-Weighted Imaging via Efficient Anatomical Anticipation and Multimodal Confirmation

arXiv:2609.06165v1 Announce Type: new Abstract: Whole-body diffusion-weighted imaging (WB-DWI) is widely used for multiple myeloma (MM) assessment, yet automated lesion segmentation remains challengin

MV-STRIDE: Enabling MLLMs to Master Multi-View Spatial Reasoning via Hierarchical Capability Modeling

arXiv:2609.07258v1 Announce Type: new Abstract: Despite the rapid progress of Multimodal Large Language Models (MLLMs) in 2D vision-language tasks, robust multi-view spatial reasoning remains a fundam

Nearly Tight Rademacher Bounds for Sparsely Activated Neural Networks

arXiv:2609.09130v1 Announce Type: new Abstract: An input may activate few hidden units even when different inputs collectively use an entire network. We study the statistical complexity of this input-

Neither Adversarial Training Nor Purification: Emergent Adversarial Robustness from Oscillatory Predictive Learning

arXiv:2609.08683v1 Announce Type: new Abstract: Adversarial robustness in computer vision is still largely achieved through adversarial training or test-time adversarial purification, both of which in

NEO-BENCH: A New Multi-Source Benchmark for Generalizable Astronomical Streak Detection

arXiv:2609.06774v1 Announce Type: cross Abstract: Near-Earth Objects (NEOs) can appear as faint streaks in long-exposure astronomical images. Detecting these streaks across diverse observatories requi

NEST: Narrative Event Structures in Time for Long Video Understanding

arXiv:2606.19706v2 Announce Type: replace Abstract: Recent progress in vision-language models has enabled processing of increasingly long video sequences, but handling extended token streams does not

NeuCME: Toward Dynamic Multimodal Continual Learning via Neural Combinatorics of Multiple Experts

arXiv:2609.07009v1 Announce Type: cross Abstract: Multimodal continual learning has recently shown great potential for developing agents with human-like intelligence by continuously learning new tasks

Neural Posterior Estimation for Tomographic Weak Lensing Mass Mapping

arXiv:2609.07833v1 Announce Type: cross Abstract: Weak gravitational lensing shear and convergence trace the distribution of baryonic and dark matter across space, making them a powerful probe of cosm

NeuralLVC: Neural Lossless Video Compression via Masked Diffusion with Temporal Conditioning

arXiv:2604.03353v2 Announce Type: replace-cross Abstract: While neural lossless image compression has advanced significantly with learned entropy models, lossless video compression remains largely une

Newton Matching for Generative Modeling: A Unified Framework for Fine-Tuning and Sampling

arXiv:2609.05727v1 Announce Type: new Abstract: We develop Newton Matching, a unified framework for fine-tuning and sampling in generative modeling. The target is piproptomu e^{au r}, where r is the r

Nice paper to improve inference efficiency. It's been a while we haven't seen good work on efficiency. Here is why it matters: A long-runnin…

Nice paper to improve inference efficiency. It's been a while we haven't seen good work on efficiency. Here is why it matters: A long-running agent's workspace outgrows its context window long before

model-releasesdair-ai--x

No-Regret Mixing of LRU and LFU with Optimal Switching Cost

arXiv:2609.07566v1 Announce Type: new Abstract: Caching systems often rely on simple eviction policies such as Least Recently Used (LRU) and Least Frequently Used (LFU), which perform well in compleme

NOAH: Learning the Full Patient Journey. A Longitudinal Multimodal Time-Aware Model for Representation and Forecasting

arXiv:2609.09140v1 Announce Type: new Abstract: The digitization of healthcare has generated vast, longitudinal, and multimodal patient records over a lifetime, yet fully exploiting these data to repr

Noisy-Space Policy Gradient for Diffusion Policies in Offline Reinforcement Learning

arXiv:2609.06882v1 Announce Type: new Abstract: Diffusion policies offer a powerful and expressive parameterization for continuous control. Yet, their integration with reinforcement learning remains c

NoLoCo: No-all-reduce Low Communication Training Method for Large Models

arXiv:2506.10911v2 Announce Type: replace Abstract: Training large language models is generally done on clusters containing thousands of accelerators, communicating over a high-bandwidth interconnect.

Agents

Non-Adaptive 1-Bit Mean Estimation: Minimax Rates and the Sample-Interval Tradeoff

arXiv:2609.08564v1 Announce Type: cross Abstract: We study distributed one-dimensional mean estimation under a 1-bit communication constraint. Each agent observes one sample, drawn independently from

agentsarxiv-cs-lg

Non-Coherent Over-the-Air Federated Learning: Protocol, Convergence, and Device Scheduling

arXiv:2609.08312v1 Announce Type: cross Abstract: To mitigate the scalability bottleneck in the radio access network (RAN) in federated edge learning (FEEL), over-the-air federated learning (AirFL) ex

Nonlinear elliptic homogenization with the parametric Deep Ritz method

arXiv:2609.05778v1 Announce Type: new Abstract: Elliptic homogenization is used to determine coarse-grained properties of materials with features on small scales. When these small scale features have

Norms at a Price: Why RL-Based Alignment Can Promise Conditional Compliance at Best

arXiv:2609.07627v1 Announce Type: cross Abstract: AI agents sometimes act aligned when they infer they are being tested, and differently when not. We argue this is not an anomaly but what current trai

Not All Variables Agree: Reliability-Aware Variable-Wise Gradient Surgery for Multivariate Time-Series Forecasting

arXiv:2609.08554v1 Announce Type: new Abstract: In data-driven training, multivariate time-series forecasting is usually optimized with a scalar loss averaged over samples, variables, and horizons. Th

Applications

Not Just Oversmoothing: Detecting the Echo Chamber Effect in Graph Neural Networks

arXiv:2609.06521v1 Announce Type: new Abstract: Oversmoothing is a well-known failure mode of Graph Neural Networks (GNNs). However, most existing diagnostics rely on global aggregation measures that

applicationsarxiv-cs-lg

not the man we need at this moment

not the man we need at this moment Q: The worst case is that AI will turn against humanity. Do we have guardrails? Trump: It's going to be fine. We'll always have something to stop them. We'll have a

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NOVA: Normal-Side Modeling for Training-Free Zero-Shot Video Anomaly Detection

arXiv:2609.06360v1 Announce Type: new Abstract: Training-free zero-shot video anomaly detection (ZS-VAD) leverages vision-language models (VLMs) to localize anomaly instances from a predefined anomaly

safetyarxiv-cs-cv

Novel hybrid protein scaffold gap filling using weighted machine learning ensemble, beam search, and mass-constrained reranking

arXiv:2609.05436v1 Announce Type: cross Abstract: Protein scaffold gap filling is an important computational task in protein sequence reconstruction, where missing amino acid regions must be inferred

Novel Methods for Catheter and Guidewire Segmentation in X-ray Fluoroscopy under a Federated Learning Setting

arXiv:2609.06876v1 Announce Type: new Abstract: Endovascular procedures rely on real-time manipulation of thin instruments, catheters and guidewires, under X-ray fluoroscopy guidance, where accurate v

NSFlow: End-to-End Differentiable Neuro-Symbolic Optical Flow for Visual Odometry

arXiv:2609.06074v1 Announce Type: new Abstract: Sparse optical flow provides stable inter-frame correspondence, playing a key role in Visual Odometry (VO) and Visual-Inertial Odometry (VIO). Classical

NutriBench-Kitchen: Benchmarking Embodied AI for Nutrition Management

arXiv:2609.07135v1 Announce Type: new Abstract: An embodied kitchen assistant must do more than recognize food in isolated frames. It must track ingredient states over time and integrate visual observ

Hardware

NVIDIA Brings Real-Time AI to Broadcast, Sports and Global Streaming at IBC

At the IBC conference, running Sept. 11-14 in Amsterdam, the creative, technology and business communities are coming together to turn ideas into action and discuss innovations across the media and en

hardwarenvidia-blog

Nystrom Attention Matches Full Attention for Cross-Sectional Stock Prediction

arXiv:2609.08106v1 Announce Type: new Abstract: MASTER's inter-stock multi-head attention -- the module responsible for modeling cross-sectional stock relationships -- accounts for 42.5% of model para

Local Ai

Object-Aware Background-Controlled Editing via Weighted Velocity Guidance

arXiv:2609.06288v1 Announce Type: new Abstract: Training-free image editing steers diffusion or flow-matching generative models at inference time by modifying prompt-conditioned denoising velocities.

local-aiarxiv-cs-cv

Local Ai

Observability Analysis of Joint Steering and Extrinsic Calibration

arXiv:2609.05498v1 Announce Type: new Abstract: This technical report studies the local weak observability of a planar bicycle-model vehicle when vehicle pose, planar LiDAR extrinsic calibration, and

local-aiarxiv-cs-ro

Observability conditions for neural state-space models with eigenvalues and their roots of unity

arXiv:2504.15758v3 Announce Type: replace Abstract: We operate through the lens of ordinary differential equations and control theory to study the concept of observability in the context of neural sta

Observation Design for Certified Control Authority: Projection--Estimability Separation and Active-Face Equivalence

arXiv:2609.05962v1 Announce Type: new Abstract: A sound runtime admission gate executes only actions it can certify, and certifies only what its observations support. This paper asks how observations

researcharxiv-cs-ro

Observe Before You Alert: Adaptive Driver Alerting with Vision-Language Models

arXiv:2609.08130v1 Announce Type: new Abstract: Driver alerting from dashcam video requires sequential decision-making under partial observability: a system must decide not only whether a scene is ris

Observing Health Outcomes Using Remote Sensing Imagery and Geo-Context Guided Visual Transformer

arXiv:2602.00110v2 Announce Type: replace Abstract: Visual transformers have driven major progress in remote sensing image analysis, particularly in object detection and segmentation. Recent vision-la

safetyarxiv-cs-cv

OcclusionCBF: Backup Control Barrier Functions for Safe Navigation Among Hidden Dynamic Obstacles

arXiv:2609.06342v1 Announce Type: new Abstract: Robots navigating under occlusion may enter states from which no admissible input can avoid a dynamic obstacle once it becomes visible. We present Occlu

safetyarxiv-cs-ro

Hardware

OCTN: Neural OCT Representations for Robot-Guided Precision Intervention

arXiv:2609.06810v1 Announce Type: new Abstract: Optical coherence tomography (OCT) offers compact, contactless, micron-scale imaging suitable for intraoperative guidance, but native OCT volumes are di

hardwarearxiv-cs-ro

OdysSim: Building Foundation Models for Human Behavior Simulation

arXiv:2606.14199v2 Announce Type: replace-cross Abstract: Large language models are increasingly deployed as human simulators for interactive evaluation and social simulation. Yet helpfulness-driven p

Agents

Omni Interaction Agent Technical Report

arXiv:2609.08977v1 Announce Type: cross Abstract: In this work, we present Gander, an end-to-end model that unifies omni perception, realtime interaction, and agentic capabilities within a single fram

agentsarxiv-cs-lg

Applications

OmniNav: Robust Long-Horizon Target Navigation in Dynamic Environments

arXiv:2609.08159v1 Announce Type: new Abstract: Long-horizon target navigation requires a robot to sustain task execution across evolving observations, decisions, and physical interactions. This requi

applicationsarxiv-cs-ro

On BatchNorm Forward Modes in Value-Based Reinforcement Learning

arXiv:2609.06421v1 Announce Type: new Abstract: Batch normalization (BN) substantially improves sample efficiency in continuous-control actor-critic methods such as CrossQ, yet recent studies report p

On Generalisation Error Bounds for Transformers

arXiv:2410.11500v2 Announce Type: replace-cross Abstract: In this paper, we establish a collection of covering number bounds for linear function classes under various norm constraints on the inputs an

On the Effectiveness of the z-Transform Method in Quadratic Optimization

arXiv:2507.03404v3 Announce Type: replace Abstract: The z-transform of a sequence is a classical tool used within signal processing, control theory, computer science, and electrical engineering. It al

On the flip slide there is a >10% chance that AI could save all humans by curing disease and aging in the next decade

On the flip slide there is a >10% chance that AI could save all humans by curing disease and aging in the next decade Jacob is correct here—we really do earnestly believe AI could kill all humans! I p

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