Search: “local-ai”

Finding Kissing Numbers with Game-theoretic Reinforcement Learning

arXiv:2511.13391v4 Announce Type: replace-cross Abstract: Since Isaac Newton first studied the Kissing Number Problem in 1694, determining the maximal number of non-overlapping spheres around a centra

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FLARE: Fine-Grained Diagnostic Feedback for LLM Code Refinement

DGX agent

arXiv:2606.03852v1 Announce Type: cross Abstract: Large language models often generate code with bugs. Existing methods rely on feedback signals such as test failures and self-critiques to iteratively

local-aiarxiv-cs-ai

3 Jun 2026

Framing Migration News with LLMs: Structured CoT as a Support for Human Interpretation

arXiv:2606.03761v1 Announce Type: new Abstract: Frame analysis of migration news is a socially consequential task: media scholars and researchers who study how migration is narrated need tools that ar

local-aiarxiv-cs-cl

From 3D Perception to Safety Reasoning: A Graph-Based Framework for Real-Time Underground Mine Monitoring

arXiv:2606.03460v1 Announce Type: new Abstract: Underground coal mining requires personnel and heavy equipment to operate within shared, confined, and poorly illuminated spaces where hazards such as e

Generalizing Graph Foundation Models via Hyperbolic Retrieval-Augmented Generation

arXiv:2606.03307v1 Announce Type: cross Abstract: Graph foundation models (GFMs) emerged as a dominant paradigm in graph representation learning by leveraging large-scale pre-training for cross-domain

Graph Regularized Non-negative Reduced Biquaternion Matrix Factorization for Color Image Recognition

arXiv:2606.03654v1 Announce Type: new Abstract: Non-negative reduced biquaternion matrix factorization (NRBMF) uses the product of reduced biquaternion (RB) matrices to incorporate the non-negativity

InfoMem: Training Long-Context Memory Agents with Answer-Conditioned Information Gain

arXiv:2606.03329v1 Announce Type: new Abstract: Long-context tasks require LLMs to identify and preserve answer-relevant information from large contexts. Chunk-wise memory agents address this issue by

Learn from Your Mistakes: Tree-like Self-Play for Secure Code LLMs

arXiv:2606.03489v1 Announce Type: cross Abstract: While Large Language Models (LLMs) excel in code generation, they remain prone to replicating subtle yet critical vulnerabilities endemic to their tra

Local Guidance, Global Impact: Gaussian-Reshaped Trust Region Unlocks Behavior Transitions

arXiv:2606.03382v1 Announce Type: cross Abstract: While Proximal Policy Optimization (PPO) demonstrates strong performance in stationary settings, we show that its standard optimization paradigm strug

NetKV: Network-Aware Decode Instance Selection for Disaggregated LLM Inference

arXiv:2606.03910v1 Announce Type: cross Abstract: Disaggregated LLM inference forces the KV cache to traverse the datacenter network before decoding begins, so transfer time enters directly into the T

Neural Fields as World Models

arXiv:2602.18690v2 Announce Type: replace-cross Abstract: Humans rehearse possible futures offline, as in mental practice and perhaps dreaming, suggesting that world models may support task learning a

ParaBlock: Communication-Computation Parallel Block Coordinate Federated Learning for Large Language Models

arXiv:2511.19959v2 Announce Type: replace Abstract: Federated learning (FL) has been extensively studied as a privacy-preserving training paradigm. Recently, federated block coordinate descent scheme

Partially Observable Adversarial Patch Attacks on Vision-Language-Action Models in Robotics

arXiv:2606.03556v1 Announce Type: new Abstract: Vision-language-action (VLA) models are gaining attention in robotics, yet their robustness to adversarial attacks remains largely unexplored. Existing

local-aiarxiv-cs-ro

Patcher: Post-Hoc Patching of Backdoored Large Language Models

arXiv:2606.02995v1 Announce Type: cross Abstract: Large language models remain vulnerable to jailbreak backdoor attacks, where adversaries poison safety alignment data to embed hidden triggers that by

ReciNet: Reciprocal Space-Aware Long-Range Modeling for Crystalline Property Prediction

arXiv:2502.02748v4 Announce Type: replace Abstract: Predicting properties of crystals from their structures is a fundamental yet challenging task in materials science. Unlike molecules, crystal struct

Regret Pre-training: Bridging Prior and Posterior Views for Enhanced Knowledge Grounding

arXiv:2606.03080v1 Announce Type: cross Abstract: Causal language models factorize sequence probabilities using only preceding context, leaving future information unexploited during training despite i

ResCLIP: Residual Attention for Training-free Dense Vision-language Inference

arXiv:2411.15851v2 Announce Type: replace Abstract: While vision-language models like CLIP have shown remarkable success in open-vocabulary tasks, their application is currently confined to image-leve

Resource-Constrained Adaptive Inference for Sequential Pricing

arXiv:2606.03736v1 Announce Type: cross Abstract: Resource-constrained pricing controllers can make fixed-price inference impossible: the controller's resource state may remove the target price neighb

SAMatcher: Co-Visibility Modeling with Segment Anything for Robust Feature Matching

arXiv:2606.03406v1 Announce Type: new Abstract: Reliable correspondence estimation is a fundamental problem in image processing, underpinning applications such as Structure from Motion, visual localiz

Scalable Derivative Gaussian Processes via Exact Gradient Reduction

arXiv:2606.02909v1 Announce Type: cross Abstract: Gradient observations can substantially improve Gaussian process (GP) surrogates, particularly in high-dimensional settings where function evaluations

SEAOTTER: Sensor Embedded Autoencoding with One-Time Transcode for Efficient Reconstruction

arXiv:2606.03940v1 Announce Type: cross Abstract: In robotics systems, vast amounts of visual data are easily captured at high resolution using low-cost, low-power hardware. Yet, limited bandwidth and

SegTune: Structured and Fine-Grained Control for Song Generation

arXiv:2606.02638v1 Announce Type: cross Abstract: Recent advances in neural song generation have enabled high-quality synthesis from lyrics and global textual prompts. However, most systems fail to mo

SJD-PAC: Accelerating Speculative Jacobi Decoding via Proactive Drafting and Adaptive Continuation

arXiv:2603.18599v2 Announce Type: replace Abstract: Speculative Jacobi Decoding (SJD) offers a draft-model-free approach to accelerate autoregressive text-to-image synthesis. However, the high-entropy

Tailoring Strictly Proper Scoring Rules for Downstream Tasks: An Application to Causal Inference

arXiv:2606.03332v1 Announce Type: new Abstract: Probabilistic models are typically trained using task-agnostic objectives like log-loss, which can lead to significant errors in downstream estimation.

The Road Ahead in Autonomous Driving: The KITScenes Multimodal Dataset

arXiv:2606.02956v1 Announce Type: new Abstract: Existing autonomous driving datasets have enabled major progress, but fall short in sensor fidelity, map completeness, or geographic diversity. We prese

Tiny Collaborative Inference for Occlusion-Robust Object Detection

arXiv:2606.02894v1 Announce Type: new Abstract: Small edge devices such as IoT surveillance nodes and search-and-rescue (SAR) platforms are increasingly expected to run computer vision locally. On ult

Toward a Modular Architecture for Embedded AI Agent Systems at the Edge

arXiv:2606.02862v1 Announce Type: new Abstract: The rise of Large Language Models (LLMs) has enabled agentic AI capable of complex reasoning and tool use; however, deploying such autonomy in pervasive

Visual Instruction Tuning Aligns Modalities through Abstraction

arXiv:2606.03871v1 Announce Type: cross Abstract: Visual instruction tuning effectively adapts a pre-trained Large Language Model (LLM) to process image information alongside text. Yet, it remains unc

local-aiarxiv-cs-cl

VulnAgent-R2: Evidence-Calibrated Multi-Agent Auditing for Repository-Level Vulnerability Detection

arXiv:2603.13384v2 Announce Type: replace-cross Abstract: Software vulnerabilities often depend on cross-file data flow, build options, framework conventions, and runtime guards, so isolated function

WebRISE: Requirement-Induced State Evaluation for MLLM-Generated Web Artifacts

arXiv:2606.03220v1 Announce Type: cross Abstract: Existing benchmarks for MLLM-generated web artifacts assess interaction through local evidence and miss the requirement-induced states and transitions

When RLHF Fails: A Mechanistic Taxonomy of Reward Hacking, Collapse, and Evaluator Gaming

arXiv:2606.03238v1 Announce Type: cross Abstract: Reinforcement learning from human feedback (RLHF) makes large-scale post-training possible by replacing an underspecified human objective with learned

A Lightweight Deep Learning-based Model for Ranking Influential Nodes in Complex Networks

arXiv:2507.19702v1 Announce Type: cross Abstract: Identifying influential nodes in complex networks is a critical task with a wide range of applications across different domains. However, existing app

AEyeDE: An Attention-Based Attribution Framework for AI-Generated Text Detection

arXiv:2606.00016v1 Announce Type: cross Abstract: Detecting AI-generated text is becoming increasingly challenging as modern language models approach human-level fluency and can evade detectors that r

AFUN: Towards an Affordance Foundation Model for Functionality Understanding

arXiv:2606.02551v1 Announce Type: cross Abstract: Affordance understanding bridges visual perception and physical action, serving as an explainable interface for robot manipulation in open and unstruc

Aligning Cellular Sheaves with Classifier Attention for Interpretable Weakly-Supervised Pathology Localization

arXiv:2606.00092v1 Announce Type: cross Abstract: Weakly-supervised classification of whole-slide images with attention-based multiple instance learning (ABMIL) on top of foundation features now reach

{alpha}Depth: Learning Single-Pass Soft Boundary Decomposition for Stereo Conversion

arXiv:2606.00386v1 Announce Type: new Abstract: Accurately modeling soft boundaries, e.g., hair and defocus blur, is a fundamental challenge in stereo conversion due to the ambiguous blending of foreg

AlphaToken: Decoupling Adaptation and Stability for Path-Aware Response Token Valuation in LLM Post-Training

arXiv:2606.01635v1 Announce Type: cross Abstract: Token selection is pivotal for effective LLM post-training. However, existing methods mostly rely on local heuristics and rarely formulate token selec

Amortized Predictability-aware Training Framework for Time Series Forecasting and Classification

arXiv:2602.16224v2 Announce Type: replace Abstract: Time series data are prone to noise in various domains, and training samples may contain low-predictability patterns that deviate from the normal da

Annotation-Informed Block-Sparse Bayesian Modeling for cis-Expression Prediction

arXiv:2606.00483v1 Announce Type: cross Abstract: Genotype-based cis-expression prediction depends on accurately modeling local regulatory architecture. We present block-sparse Bayesian sparse linear

ArrythML: An Autoencoder-Based TinyML Approach for On-Device Arrhythmia Detection on Resource-Constrained Embedded Systems

arXiv:2606.02256v1 Announce Type: new Abstract: Our work presents a method for ECG segmentation and arrhythmia detection using Tiny Machine Learning (TinyML) models for real-time, on-device inference

AutoIQ: An Ensemble Framework for Automatic Assessment of Geometric Distortion in Prostate Diffusion-Weighted Imaging

arXiv:2606.00393v1 Announce Type: cross Abstract: Geometric distortion in prostate diffusion-weighted imaging (DWI) can impair lesion localization and reduce the reliability of MRI-based clinical asse

Beyond Pure Sampling: Hybrid Optimization Mechanisms for Non-Convex Model Predictive Control

arXiv:2606.00737v1 Announce Type: new Abstract: This paper investigates the optimization mechanisms of non-convex Model Predictive Control (MPC) using the Maximum Entropy Differential Dynamic Programm

local-aiarxiv-cs-ro

Beyond Task-Agnostic: Task-Aware Grouping for Communication-Efficient Multi-Task MoE Inference

arXiv:2606.01007v1 Announce Type: cross Abstract: Sparsely activated Mixture-of-Experts (MoE) models scale capacity via conditional computation, but distributed inference suffers from cross-GPU expert

Capability Self-Assessment: Teaching LLMs to Know Their Limits

arXiv:2606.00251v1 Announce Type: new Abstract: The ability to recognize one's own limitations and decide whether to solve a problem or delegate is fundamental for reliable intelligent systems. Yet we

Certificates without Electrons? Theory and Evidence on Impacts from AI-Driven Power Demand

arXiv:2606.00811v1 Announce Type: cross Abstract: Data centers now account for 4.4% of United States electricity demand, yet the grid-level effectiveness of the renewable energy certificates (RECs) an

Closed-Form Pose Estimation of Endoluminal Medical Devices via Gradiometer-Based Electromagnetic Localization System

arXiv:2606.01946v1 Announce Type: new Abstract: Embedded magnetic tracking holds highly attractive prospects for remote navigation of endoluminal medical devices. However, existing six-degree-of-freed

local-aiarxiv-cs-ro

Coarse-to-Fine Compositional Diffusion for Long-Horizon Planning

arXiv:2606.00837v1 Announce Type: cross Abstract: Diffusion models provide strong priors for generating structured data, but many tasks require outputs beyond the scale on which these models are typic

Compliance-Scored Best-of-N Guardrail Orchestration for Multimodal Document Generation in Payments Dispute Defense

arXiv:2606.01513v1 Announce Type: cross Abstract: High-stakes enterprise document generation, including financial dispute narratives, compliance notices, and audit summaries, demands schema correctnes