Search: “deployment”

Learning to Detect Shifts in Unstructured Data Streams via Monitoring-by-Betting

arXiv:2610.17399v1 Announce Type: new Abstract: Continuous monitoring of generative AI systems requires detecting distribution shifts in the unstructured data they ingest and generate. Existing monito

tutorialsarxiv-cs-lg

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Learning When to Transfer: Reinforcement Learning for Carbon-Footprint Modeling in New Manufacturing Domains

DGX agent

arXiv:2610.18730v1 Announce Type: new Abstract: Manufacturers often need to characterize a new material, process, or product before enough operating data are available to train reliable predictive mod

safetyarxiv-cs-lg

14 Oct 2026

LensErase: A Foundation Model for Erase Anything

arXiv:2610.18072v1 Announce Type: new Abstract: We introduce LensErase, a general-purpose mask-based Erase Anything foundation model designed to cover a broad spectrum of real-world erase scenarios. L

applicationsarxiv-cs-cv

Lightweight Scheduling Policies for Continuously Batched LLLM Serving Across GPU Architectures

arXiv:2610.15899v1 Announce Type: cross Abstract: Large language model serving is increasingly limited not only by model size and GPU speed, but also by scheduling during autoregressive decoding, wher

Look Before You Move: Agent-Interface-Aligned Supervision for Open-World Mobile Manipulation

arXiv:2610.15572v1 Announce Type: new Abstract: Open-world mobile manipulation requires a robot to find an object, approach it, and move it to a target receptacle from a language instruction. Training

MARTS: A Modular Agricultural Robot for Targeted Spraying of Diseased Tomato Plants in Greenhouses

arXiv:2610.18123v1 Announce Type: new Abstract: Broadcast spraying remains the dominant method of disease control in greenhouse tomato production, yet it treats healthy and diseased tissue alike, expo

local-aiarxiv-cs-ro

Mean Accuracy Is the Wrong Estimand for a Release Decision

arXiv:2610.16825v1 Announce Type: new Abstract: A release decision about a fine-tuned model is an operational commitment about the next rerun of its training recipe. Yet standard benchmark reporting g

Memory Without Curation: Learning Multi-Stream Latent Memory for Robot Policies

arXiv:2610.14406v1 Announce Type: cross Abstract: It is widely appreciated that robotic policies require long-term memory to perform complex tasks. However, directly conditioning policies on all past

MENTOR: Procedural Shielding of Tool-Using LLM Agents

arXiv:2610.17039v1 Announce Type: cross Abstract: Tool-using LLM agents are increasingly used to automate workflows governed by procedural manuals, such as company rules for booking travel or procurin

local-aiarxiv-cs-lg

METIS: Multi-Source Egocentric Training for Integrated Dexterous Vision-Language-Action Model

arXiv:2511.17366v2 Announce Type: replace-cross Abstract: Building a generalist robot that can perceive, reason, and act across diverse tasks remains an open challenge, especially for dexterous manipu

applicationsarxiv-cs-cv

Mining Cross-Modal Perception Gaps in Autonomous Driving: When Camera and LiDAR Disagree

arXiv:2610.16906v1 Announce Type: new Abstract: Multi-modal fusion for 3D object detection assumes that cameras and LiDAR are broadly complementary. In practice, how much each modality is trusted at a

safetyarxiv-cs-cv

MIRROR: Reflecting Hidden Symmetries from Offline Robot Interaction Data

arXiv:2610.17422v1 Announce Type: new Abstract: Symmetry-aware robot policy learning requires coupled observation-action transformations. For pixel observations, even simple physical symmetries can in

MOSAIC: Mode- and Support-Aware Inference-Time Control of Robot Diffusion Models

arXiv:2610.17001v1 Announce Type: new Abstract: Generative policies such as diffusion models provide expressive data-driven priors for robot behavior, yet the situations a robot faces at execution tim

MultiAlloc: Budget-Aware Precision Allocation for KV Cache Quantization

arXiv:2610.18642v1 Announce Type: new Abstract: The Key-Value (KV) cache constitutes a dominant source of memory consumption during large language model (LLM) inference, particularly in long-context a

Not All Challenges Are Equal: Evaluating Interactive Liveness Detection Against Real-Time Face Swaps

arXiv:2610.16417v1 Announce Type: new Abstract: Remote identity verification assumes that a camera stream shows a live person, yet public real-time face-swap tools can replace that person before the s

On the Monitorability of Natural Language Autoencoders: Identification vs Discrimination

arXiv:2610.18727v1 Announce Type: new Abstract: Natural Language Autoencoders (NLAs) are proposed as oversight tools for language models: an Activation Verbaliser (AV) writes an English explanation of

OneShot: Label-Efficient Detector Weighting for Time Series Anomaly Detection

arXiv:2610.16219v1 Announce Type: cross Abstract: Time series (TS) anomaly detection (AD) lacks a universal detector, with the best choice determined by the series rather than by the algorithm. Existi

researcharxiv-cs-lg

Open Foundation Models in Healthcare: Challenges, Paradoxes, and Opportunities with GenAI Driven Personalized Prescription

arXiv:2502.04356v2 Announce Type: replace-cross Abstract: In response to the success of proprietary Large Language Models (LLMs), there is a growing interest in developing open, non-proprietary LLMs a

OPTIC-ER: A Reinforcement Learning Framework for Real-Time Emergency Response and Equitable Resource Allocation in Underserved African Communities

arXiv:2508.12943v3 Announce Type: replace-cross Abstract: Public service systems in many African regions suffer from delayed emergency response and spatial inequity, causing avoidable suffering. This

tutorialsarxiv-cs-lg

Pickalo: Leveraging 6D Pose Estimation for Low-Cost Industrial Bin Picking

arXiv:2604.04690v3 Announce Type: replace Abstract: Bin picking in real industrial environments remains challenging due to severe clutter, occlusions, and the high cost of traditional 3D sensing setup

researcharxiv-cs-ro

Prediction Is All MoE Needs: Expert Load Distribution Goes from Fluctuating to Stabilizing

arXiv:2404.16914v2 Announce Type: replace Abstract: MoE facilitates the development of large models by making the computational complexity of the model no longer scale linearly with increasing paramet

local-aiarxiv-cs-lg

PRIME: Frequency-Aware Unified Pruning and Merging for MoE Compression

arXiv:2610.13982v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models have emerged as an effective paradigm for scaling large language models, yet their massive parameter footprint poses sev

Push the Limit: Learning High-Speed Sprinting and Aggressive Cornering on a Full-Scale Humanoid

arXiv:2610.14840v1 Announce Type: new Abstract: We present a learning-based framework that enables a full-scale bipedal humanoid to sprint at over 7 m/s with motion-prior-guided gait and perform aggre

researcharxiv-cs-ro

Agents

RAGE: A Tightly Coupled Radar-Aided Grip Estimator For Autonomous Race Cars

arXiv:2604.02892v2 Announce Type: replace Abstract: Real-time estimation of vehicle-tire-road friction is critical for allowing autonomous race cars to safely and effectively operate at their physical

agentsarxiv-cs-ro

Reinforcement Learning for Large-Scale Lifelong Multi-Agent Path Finding with Shared Spatial Fields

arXiv:2610.18186v1 Announce Type: new Abstract: Large-scale applications of lifelong multi-agent path finding (LMAPF) call for computationally inexpensive movement decisions under changing traffic con

Robust Detection of Directional Adversarial Attacks in Deep Neural Networks for Radiological Imaging

arXiv:2610.15628v1 Announce Type: new Abstract: Deep learning is now central to radiology, helping detect changes on X-rays, CTs, and MRIs. However, these systems are highly vulnerable to adversarial

applicationsarxiv-cs-cv

RootSLAM: Square Root Bundle Adjustment for Visual-Inertial SLAM

arXiv:2610.15157v1 Announce Type: cross Abstract: Efficient perception is a prerequisite for the small, low-power devices targeted by robotics, mixed reality, autonomous driving, and drone application

Satellite-Free Training for Drone-View Geo-Localization

arXiv:2604.01581v4 Announce Type: replace Abstract: Drone-view geo-localization (DVGL) typically assumes access to satellite imagery during task-specific development. We study a late-arriving-gallery

local-aiarxiv-cs-cv

Scenes as an Attack Surface: Uncovering Scene-Grounded Safety Failures in MLLMs

arXiv:2610.14094v1 Announce Type: new Abstract: Existing jailbreak attacks have exposed serious safety weaknesses in multimodal large language models (MLLMs). Most prior attacks rely on specially cons

safetyarxiv-cs-cv

Sea-Net: A Small and Inherently Interpretable Neural Network for Time Series Classification

arXiv:2610.17939v1 Announce Type: cross Abstract: Traditional time-series classification methods often operate as black boxes, providing a class prediction without indicating which time point or time

SHOES: Sim-to-real Hardware-adaptation via On-policy Expansion of Skills for Legged Robots

arXiv:2610.16457v1 Announce Type: new Abstract: Humans expand their locomotion capability by wearing appropriate footwear, such as hiking boots for mountains or skates for ice. Footwear changes the gr

Agents

SHRUMS: Sensor Hallucination for Real-time Underwater Motion Planning with a Compact 3D Sonar

arXiv:2510.18996v2 Announce Type: replace Abstract: Autonomous navigation in 3D is a fundamental problem for autonomy. Despite major advancements in terrestrial and aerial settings due to improved ran

agentsarxiv-cs-ro

Simple Linear Corrections for Compression in Late Interaction

arXiv:2610.14196v1 Announce Type: cross Abstract: Late-interaction (multi-vector) models represent documents using a set of token-level vectors, providing a middle ground between cross-encoders and de

Simplifying and Improving On-Policy Distillation for Few-Step Diffusion

arXiv:2610.18472v1 Announce Type: new Abstract: Few-step distillation reduces the sampling cost of diffusion and flow models, but existing approaches often require auxiliary score models or specialize

local-aiarxiv-cs-cv

SkipWorld: Latent Skip Planning with Distilled World Models for Efficient Visual Navigation

arXiv:2610.18135v1 Announce Type: new Abstract: World-model-based visual navigation enables action planning by predicting future states under candidate trajectories. However, long-horizon rollout rema

tutorialsarxiv-cs-ro

StreamingWAM: Streaming World Action Modeling via Chunk-Wise Staircase Flow Matching

arXiv:2610.15585v1 Announce Type: new Abstract: World Action Models (WAMs), often built upon pretrained video-generation world models, have emerged as a promising framework for general-purpose and ope

applicationsarxiv-cs-ro

TableVision: Recovering Verified Structure from Historical Tables

arXiv:2610.17448v1 Announce Type: new Abstract: Gaps, skips, and mistakes are the normal state of a historical register: rows go missing, tables cross page breaks, columns slip under wrong names, and

TETRIS-4DGS: Efficient Post-Training Compression of 4D Gaussian Splatting

arXiv:2610.14663v1 Announce Type: new Abstract: 4D Gaussian Splatting (4DGS) has emerged as a powerful dynamic scene representation, supporting real-time high quality rendering but suffers from prohib

Agents

Think Before You Speak: Enabling Training-Free Latent Communication Between Language Models

arXiv:2610.16165v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated remarkable capabilities in solving complex tasks in coding, mathematical logic, and iterative reasoning

agentsarxiv-cs-lg

Tikhonov-Stabilized Bezier Representation Forecasting for Training-free Diffusion Acceleration

arXiv:2610.16448v1 Announce Type: new Abstract: Diffusion models, particularly Diffusion Transformers, achieve strong image and video generation quality but remain expensive at inference time due to r

safetyarxiv-cs-cv

Today I'm excited to share that New Material is joining @MistralAI to design sovereign frontier AI. We're establishing a new team, 'Solution…

model-releasesarthur-mensch--x

Today I'm excited to share that New Material is joining @MistralAI to design sovereign frontier AI. We're establishing a new team, 'Solutions Design' within Mistral: working across product, engineerin

Triage-PiEvo: Evidence Admission for Principle-Evolving Scientific Agents

arXiv:2610.14683v1 Announce Type: new Abstract: Large language model (LLM)-based AI Scientists advance scientific discovery, yet they suffer from inefficiencies due to noisy observations. Existing pri

Truncation Samplers Are Nested: Comparing Decoding Rules Is a Measurement Problem

arXiv:2610.15570v1 Announce Type: cross Abstract: Settling one comparison between two truncation samplers has cost six thousand A100-hours, and nothing says in advance how far apart two samplers can b

Trust-Calibrated VLA Policy Post-Training with Evolving Imagination

arXiv:2610.16517v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are often pretrained via imitation learning, making reinforcement learning (RL) post-training important when deplo

UEPS: Robust and Efficient MRI Reconstruction

arXiv:2603.18572v2 Announce Type: replace-cross Abstract: Deep unrolled models (DUM) have become the state-of-the-art for accelerated MRI reconstruction, yet their robustness under domain shift remain

Understanding and Mitigating Training Instability in Large-Scale Recommender Systems: A Cascade Perspective

arXiv:2610.14394v1 Announce Type: cross Abstract: Training large-scale recommender systems on dynamic industrial platforms, such as Short-Form Video (SFV) services with billions of daily interactions,

researcharxiv-cs-lg

UniLAP: A Unified Latent Action Policy for Cross-Embodiment Manipulation

arXiv:2610.16969v1 Announce Type: cross Abstract: Latent Action Models (LAMs) can capture manipulation priors from action-free videos, but discrete latents usually impose a granularity bottleneck, lim

UniW(A)M: A Unified Mixture-of-Experts Framework for World and World-Action Models

arXiv:2610.18697v1 Announce Type: cross Abstract: World models (WMs) and world-action models (WAMs) focus on future world prediction and executable action generation, respectively. Although these mode

tutorialsarxiv-cs-cv