Search: “local-ai”

LLM-enhanced spatio-temporal learning for grid-level docked bike sharing demand prediction

arXiv:2610.03834v1 Announce Type: new Abstract: Short-term bike-sharing demand forecasting is complicated by spatial-temporal non-stationarity and the practical difficulty of incorporating unstructure

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Localization Lens for Improving Medical Vision-Language Models

DGX agent

arXiv:2610.04502v1 Announce Type: new Abstract: Medical Vision-Language Models (Med-VLMs) have demonstrated strong capabilities in clinical tasks. However, they often struggle to understand anatomical

local-aiarxiv-cs-cv

6 Oct 2026

Localize-and-Detect: Auditing Task-Level Poisoning in Instruction-Tuned Models

arXiv:2610.03960v1 Announce Type: cross Abstract: Instruction fine-tuning adapts a pretrained language model to follow instructions by training it on instruction--response pairs from a collection of t

Look Where You Say You're Looking: Self-Grounded Attention for Visual Reasoning

arXiv:2610.05023v1 Announce Type: new Abstract: We introduce Self-Saliency, a method for training Vision-Language Models (VLMs) to increase the alignment between their visual attention and the image r

MercerFlow: Flow Matching in a Kernel-Induced Latent Space for Probabilistic Forecasting

arXiv:2610.06039v1 Announce Type: new Abstract: Recent work has shown that probabilistic flow matching for time series forecasting benefits from a data-matched prior. The resulting prior introduces lo

Moment-Accurate Gaussian Mixtures for Constant-Step Stochastic Approximation

arXiv:2610.05595v1 Announce Type: cross Abstract: Local Gaussian models of constant-step learning predict output variability and expected losses, but weak convergence alone does not justify these mome

MTV: Revisiting Multi-Task Visual Representation Learning

arXiv:2601.13886v2 Announce Type: replace Abstract: Current visual representation learning remains bifurcated: vision-language models (e.g., CLIP) excel at global semantic alignment but lack spatial p

No Concept Escapes the Audit: Auditing-Aware Unlearning for Verifiable Concept Erasure in Diffusion Models

arXiv:2610.05401v1 Announce Type: new Abstract: Text-to-image diffusion models can generate prohibited content, which motivates concept erasure through machine unlearning. Most erasure methods interve

Nonlinear Density-Driven Optimal Control (D2OC) for Multi-Agent Spatial Coverage via Sequential Convex Programming

arXiv:2610.04545v1 Announce Type: cross Abstract: This paper presents a nonlinear extension of Density-Driven Optimal Control (D2OC) for multi-agent spatial coverage with prescribed density distributi

OncoNoteBERT: A Foundation Representation Model for Natural Language Processing of Real-World Outpatient Oncology Notes

arXiv:2610.03829v1 Announce Type: cross Abstract: Real-world outpatient oncology notes contain specialised terminology, tumour staging expressions, treatment names, toxicity descriptions, and institut

Optimal Control with Learned Critics under Unmodeled State Dependencies

arXiv:2610.05359v1 Announce Type: new Abstract: Model Predictive Control (MPC) provides a structured and constraint-aware mechanism for decision-making, but its reliance on optimization-friendly analy

Organize Primitives into Semantic Parts: Reinforcement Reasoning for 3D Segmentation

arXiv:2610.04602v1 Announce Type: new Abstract: Primitive-based 3D segmentation offers a compact and explicit alternative to dense surface prediction, naturally supporting structural abstraction and b

Personal VAD: Speaker-Conditioned Voice Activity Detection

arXiv:1908.04284v5 Announce Type: replace-cross Abstract: In this paper, we propose 'personal VAD', a system to detect the voice activity of a target speaker at the frame level. This system is useful

PhaseGate: Phase-Aware CPU Retrieval Scheduling for On-Device LLMs on Unified Memory

arXiv:2610.04537v1 Announce Type: new Abstract: On-device assistants run GPU-based LLM inference alongside CPU retrieval on unified-memory systems. Under a saturated local-retrieval workload, four con

Population Scaling or Data Dilution? Dynamics of Local Topology Evolution in Decentralized Learning

arXiv:2610.05476v1 Announce Type: new Abstract: Scaling decentralized learning changes not only the number of clients N, but also the dynamics of information propagation and consensus. We argue that t

PreAct-Nav: Agentic Reasoning Before Action for Urban Navigation

arXiv:2610.04916v1 Announce Type: new Abstract: Urban navigation requires embodied agents to pursue long-horizon goals through local decisions based on egocentric observations. However, existing agent

Prompt and Refinement: Asymmetric Mutual Learning for Infrared Small Target Detection with Noisy Labels

arXiv:2610.05918v1 Announce Type: new Abstract: Existing data-driven infrared small target detection (ISTD) methods typically require large-scale datasets with accurate pixel-level annotations for mod

RAGrasp: Geometry-Semantic Template Retrieval and Grasp Transfer

arXiv:2610.04438v1 Announce Type: cross Abstract: We present RAGrasp, a retrieval-augmented pipeline for planar parallel-jaw grasping from a compact set of locally collected, grasp-annotated RGB-D (co

Reachability-Guided Sequential Quadratic Programming-Guarded Model Predictive Path Integral for Safe Nonlinear Predictive Control

arXiv:2610.04406v1 Announce Type: new Abstract: Safe robot control often requires combining long-horizon performance optimization with hard state and input constraints, but existing approaches tend to

RealtimeWAM: One-Step Asynchronous World Action Models

arXiv:2610.06617v1 Announce Type: new Abstract: World Action Models (WAMs) incorporate visual representations from video generation backbones to guide action prediction. Recent efficient WAMs adopt Mi

ReDiffNet: Differential RGB-Infrared Learning for Low-Light UAV Oriented Vehicle Detection

arXiv:2610.05074v1 Announce Type: new Abstract: Low-light UAV-based RGB-infrared oriented small-vehicle detection is important for nighttime traffic monitoring, emergency response, and urban inspectio

RepTC: Representation-Aware Optimization for Efficient Traffic Classification on Edge IoT Devices

arXiv:2610.04784v1 Announce Type: cross Abstract: Traffic classification (TC) is crucial to secure Internet of Things (IoT) networks, whose edge nodes often operate under privacy, bandwidth, and energ

Residual Visual Credit Optimization: Conserved Evidence Routing for Multimodal Reinforcement Learning

arXiv:2610.04918v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards scales multimodal reasoning, but an outcome reward says how much a trajectory is worth, not how that valu

Robust Ensemble Guidance for Scientific Inverse Problems

arXiv:2610.05371v1 Announce Type: new Abstract: Ensemble guidance combines pretrained diffusion priors with black-box forward models to solve inverse problems without differentiating through the physi

Robust Local Optimization Done Right

arXiv:2610.05743v1 Announce Type: new Abstract: RANSAC scoring and local optimization (LO) impose different robustness requirements, motivating the separation of hypothesis selection from refinement.

ROT: Rotating Hidden States towards Contextual Vectors for Hallucination Mitigation in LVLMs

arXiv:2610.06056v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) frequently suffer from object hallucination. Existing training-free interventions primarily manipulate attention we

RPFQ-ViT: Rotated Phase-Frame Quantization for Extremely Low-Bit Weights in Vision Transformers

arXiv:2610.04457v1 Announce Type: new Abstract: Vision Transformers (ViTs) achieve strong performance on image recognition and mobile vision applications, but their high-dimensional linear projections

Scalable Minimal-Change Learning for Controllable Image Editing

arXiv:2610.06021v1 Announce Type: new Abstract: Image editing should change only the attributes specified by an instruction while preserving everything else, yet current methods often make unintended

Shared Geometry Is Not Shared Physics: A Layerwise Test of the Platonic Representation Hypothesis in Astronomy

arXiv:2610.04130v1 Announce Type: cross Abstract: In this paper we investigate whether geometrically aligned astronomical representations are also scientifically interchangeable. We analyze every laye

Slaying the Hydra: Interaction-Aware Circuit Discovery in Language Models

arXiv:2610.04017v1 Announce Type: new Abstract: Localizing behavior to individual components of a language model is a central goal of mechanistic interpretability. However, scoring components one at a

SPACE-CLIPv2: Decoding Local Geometry from Frozen CLIP for Monocular Depth Estimation

arXiv:2610.05029v1 Announce Type: new Abstract: Vision-language foundation models such as CLIP provide strong semantic representations, but their patch tokens are not directly optimized for dense metr

STILL: Selecting Tokens for Intra-Layer Hybrid Attention to Linearize LLMs

arXiv:2602.02180v2 Announce Type: replace Abstract: Linearizing pretrained large language models (LLMs) primarily relies on intra-layer hybrid attention mechanisms to alleviate the quadratic complexit

Taylor Representations for Model-Free RL in Networked MDPs

arXiv:2610.05456v1 Announce Type: cross Abstract: In Networked Markov Decision Processes, transition dynamics are often unknown and the state--action space grows rapidly with the number of agents. In

TempoBridge: Source-Conditioned Flow Matching with Optimal Transport Couplings for Single-Cell Population Transitions

arXiv:2610.04945v1 Announce Type: new Abstract: Destructive single-cell measurements provide unpaired population snapshots rather than observations of the same cells across conditions. Local cell stat

The Poisoned Conversation: Privacy-Leaking Watermarks in Unified Multimodal Models

arXiv:2610.05453v1 Announce Type: cross Abstract: Multimodal models are increasingly shifting toward unified architectures that understand and generate text, images, and other modalities within a shar

TimeNet: An Extensible Unified Data Infrastructure for Next-Generation Temporal Foundation Models

arXiv:2610.04407v1 Announce Type: cross Abstract: Temporal Foundation Models (TFMs) aim to generalize across domains, datasets, and tasks. Yet, their development remains constrained by fragmented, tas

TrustmeWatcher: An Application for Workplace Micro-Sensing and Explainable Well-Being Feedback

arXiv:2610.06657v1 Announce Type: new Abstract: Workplace sensing studies combine long-running behaviour traces with self-reports, yet the tools that collect those data often sit apart from the interf

Vela: Scaling Vision-Language-Action Models with Adaptive Action Curve Parametrization

arXiv:2610.05230v1 Announce Type: new Abstract: Most vision-language-action models represent future motion as fixed-rate action chunks, tying temporal resolution and prediction horizon to a fixed outp

Verifier-Guided Synthetic Augmentation for 3D Human Shape Generation

arXiv:2610.04006v1 Announce Type: new Abstract: Limited training data diversity constrains generative modeling of 3D human bodies: conservative models remain close to observed examples, whereas explor

A Locally Penalized Cross-Estimate Federated Method with Guarantees for Constrained Personalized Learning

arXiv:2603.19617v2 Announce Type: replace Abstract: Federated learning (FL) is a communication-efficient framework for solving distributed optimization problems. Standard FL methods aggregate local up

A Path Integral Surrogate for Multi-Step Gradient Inversion in Federated Learning

arXiv:2610.03597v1 Announce Type: new Abstract: Federated learning lets many clients train a shared model together without ever sending their private data to a central server. Each client shares only

Activation Sparsity with Weight Approximation for Faster LLM Decoding on Offloaded Weights

arXiv:2610.02598v1 Announce Type: new Abstract: Deploying LLMs on consumer-grade GPUs with insufficient memory to hold their weights can result in prohibitively slow inference, because decoding repeat

AdaStep: Adaptive Step Credit Weighting for Agentic Reinforcement Learning

arXiv:2610.03223v1 Announce Type: cross Abstract: Long-horizon LLM agents are typically trained with sparse outcome rewards, making trajectory-level objectives too coarse to distinguish the contributi

local-aiarxiv-cs-cl

AI-driven Thermal-aware Data Center Capacity Planning

arXiv:2610.02442v1 Announce Type: new Abstract: The emerging of large language models (LLMs) has posed significant challenges to the thermal management of data center. Intense GPU computation for LLMs

Beyond Entropy: Self-Diagnostic Multi-Role Token Optimization for Video Reasoning

arXiv:2610.03400v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards has substantially advanced multimodal reasoning, yet it remains fundamentally limited by ambiguous token-

Bridging Frontier Reasoning and Robot Execution: From Autonomous Demonstration Generation to Dense Language Supervision

arXiv:2610.03615v1 Announce Type: new Abstract: Recent advances in frontier models enable robot manipulation from only a few demonstrations, but high inference latency limits their use for real-time r

Cordial Learning: Distributed Training with Correlated Data

arXiv:2610.03330v1 Announce Type: cross Abstract: We consider a distributed learning task with agents that have correlated data. Specifically, the label of an agent depends on the input of other agent

local-aiarxiv-cs-ai

CORNAV: Construction-Aware Reasoning for Robot Navigation on Active Worksites

arXiv:2610.03622v1 Announce Type: new Abstract: The construction industry faces persistent labor shortages, low productivity that costs the global economy over $1.6 trillion annually, and one of the h