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Infra-Swarm: Robust Vision-Based Multi-Robot Swarming via Near-Infrared Spectral Vision

arXiv:2607.12489v1 Announce Type: new Abstract: Distributed swarms typically rely on either active wireless communication or passive vision, and they are frequently hindered by bandwidth constraints o

agentsarxiv-cs-ro

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Inhibited Self-Attention: Sharpening Focus in Vision Transformers

DGX agent

arXiv:2607.12881v1 Announce Type: new Abstract: Vision Transformers (ViTs) have demonstrated remarkable performance in computer vision tasks. However, their self-attention mechanism often diffuses foc

researcharxiv-cs-cv

15 Jul 2026

Instance-Enriched Semantic Maps for Visual Language Navigation

arXiv:2607.12630v1 Announce Type: cross Abstract: Visual Language Navigation (VLN) aims to enable an embodied agent to navigate complex environments by following natural language instructions. Recent

agentsarxiv-cs-cv

Institutional Equity Holdings Prediction Using Node Affinities of Dynamic Graphs

arXiv:2607.12067v1 Announce Type: new Abstract: Institutional equity holdings disclosed in SEC Form 13F filings provide a rich temporal record of portfolio decisions by large investment managers. Howe

Internet of Agentic Things: Networked AI Agents for Closed-Loop IoT Orchestration

arXiv:2607.12662v1 Announce Type: new Abstract: The paper introduces the Internet of Agentic Things (IoAT), an architectural framework that integrates agentic AI, IoT, cyber-physical systems, Physical

Interpretable and Verifiable Hardware Generation with LLM-Driven Stepwise Refinement

arXiv:2606.19387v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have achieved remarkable success in software development. However, they are susceptible to hallucinations, meanin

agentsarxiv-cs-ai

Tutorials

Invariant Learning Dynamics of Transformers in Inductive Reasoning Tasks

arXiv:2607.11875v2 Announce Type: replace-cross Abstract: We present a theoretical framework to explain the emergence of inductive reasoning abilities in Transformer language models. While previous wo

tutorialsarxiv-cs-ai

IQA-T1: Tool-based Visual Evidence Reasoning for Image Quality Assessment

arXiv:2607.12375v1 Announce Type: cross Abstract: Image Quality Assessment (IQA) in open-world environments remains challenging due to limited generalization and interpretability. Recent approaches ba

researcharxiv-cs-ai

Isolation as a First-Class Principle for LLM-Agent System Safety: Concepts, Taxonomy, Challenges and Future Directions

arXiv:2607.12406v1 Announce Type: new Abstract: The capability of LLM agents to function as the ``brain'' of a system fundamentally expands the scope of analysis beyond a standalone model. Consequentl

JADE: Expert-Grounded Dynamic Evaluation for Open-Ended Professional Tasks

arXiv:2602.06486v4 Announce Type: replace Abstract: Evaluating agentic AI on open-ended professional tasks faces a fundamental dilemma between rigor and flexibility. Static rubrics provide rigorous, r

Jetson-PI: Towards Onboard Real-Time Robot Control via Foresight-Aligned Asynchronous Inference

arXiv:2607.12659v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have achieved impressive performance on diverse embodied tasks. However, deploying VLA models on low-power onboard

Applications

Kernel PCA for Out-of-Distribution Detection: Non-Linear Kernel Selection and Approximation

arXiv:2505.15284v2 Announce Type: replace-cross Abstract: Out-of-Distribution (OoD) detection is vital for the reliability of deep neural networks, the key of which lies in effectively characterizing

applicationsarxiv-cs-cv

KnowAct-GUIClaw: Know Deeply, Act Perfectly, Personal GUI Assistant with Self-Evolving Memory and Skill

model-releasesarxiv-cs-cl

arXiv:2607.12625v1 Announce Type: new Abstract: OpenClaw has emerged as a leading agent framework for complex task automation, yet it faces insufficient cross-platform GUI interaction support and a we

Knowledge- and Gradient-Guided Reinforcement Learning for Parametrized Action Markov Decision Processes

arXiv:2607.12924v1 Announce Type: new Abstract: In this paper, we study Reinforcement Learning in Parametrized Action Markov Decision Processes (PAMDP), where each decision consists of a symbolic acti

Knowledgeless Language Models: Suppressing Parametric Recall for Evidence-Grounded Language Modeling

arXiv:2607.12831v1 Announce Type: new Abstract: Language models encode substantial factual knowledge in their parameters, which can lead to unreliable behavior when this knowledge is outdated, incompl

researcharxiv-cs-cl

Label-Decoupled Style Augmentation for Domain Generalization in Multi-Label Remote Sensing Scene Classification

model-releasesarxiv-cs-cv

arXiv:2607.12704v1 Announce Type: new Abstract: Multi-label classification assigns several co-occurring labels to each aerial scene, yet deployed models often encounter data distributions different fr

LakeQuest: A Three-Domain Benchmark for Grounded Question Answering across Data Lakes

arXiv:2607.12310v1 Announce Type: cross Abstract: While modern question answering (QA) systems excel on clean, schema-aligned corpora, real-world knowledge is rarely so neatly packaged. Answering ques

Tutorials

Language Identification with Succinct Machine-Independent Traces

arXiv:2607.12443v1 Announce Type: new Abstract: Motivated by the power of large language models, there has been renewed interest in the Gold-Angluin model of language identification in the limit, with

tutorialsarxiv-cs-cl

Applications

LapSurgie: Humanoid Robots Performing Surgery via Teleoperated Handheld Laparoscopy

arXiv:2510.03529v3 Announce Type: replace Abstract: Robotic laparoscopic surgery has gained increasing attention in recent years for its potential to deliver more efficient and precise minimally invas

applicationsarxiv-cs-ro

LARAD: Layout-Aware Road Anomaly Detection via Spatial-Logic Reasoning

arXiv:2607.12858v1 Announce Type: new Abstract: Accurate open-world obstacle detection is critical for autonomous driving. Current anomaly segmentation methods suffer from a fundamental blind spot: th

agentsarxiv-cs-cv

LatentFlow: A General Framework for Conditioning Stochastic Processes

arXiv:2607.12922v1 Announce Type: cross Abstract: Stochastic-process models are, as a rule, far easier to simulate than to condition. Non-linear observations, non-Gaussian likelihoods, black-box infor

Learning an Interpretable Risk Scoring System for Maximizing Decision Net Benefit

arXiv:2604.04241v2 Announce Type: replace Abstract: Risk scoring systems are widely used in high-stakes domains to assist decision-making. However, existing approaches often focus on optimizing predic

Learning and Testing Convex Functions

arXiv:2511.11498v2 Announce Type: replace-cross Abstract: We consider the problems of learning and testing real-valued convex functions over Gaussian space. Despite the extensive study of function con

Learning-based Probabilistic Load Forecasting with Post-hoc and In-model Uncertainty

arXiv:2607.12730v1 Announce Type: cross Abstract: Smart-building load forecasters are often trained offline on dense, multivariate, high-frequency data, but deployment may provide only hourly, feature

researcharxiv-cs-ai

Learning-enabled Acceleration of Scenario-based Model Predictive Control

arXiv:2607.12775v1 Announce Type: cross Abstract: Scenario-based model predictive control (SBMPC) is a variant of model predictive control (MPC) that explicitly accounts for uncertainty by optimizing

Applications

Learning Forced Multibody Dynamics on Lie Groups

arXiv:2607.12627v1 Announce Type: new Abstract: We propose an architecture for learning the dynamics of mechanical systems based on discrete forced Euler-Lagrange equations on Lie groups using only po

applicationsarxiv-cs-lg

Learning from Complementary Ultrasound Representations for Liver Disease Classification

arXiv:2607.12062v1 Announce Type: new Abstract: Differentiating non-alcoholic steatohepatitis (NASH) from non-alcoholic fatty liver disease (NAFLD) using ultrasound remains challenging due to subtle t

researcharxiv-cs-cv

Learning in Curved Weight Space:Exponential-Linear Weight Reparameterization for Improved Optimization

arXiv:2607.09967v2 Announce Type: replace-cross Abstract: Many neural networks operations have a multiplicative nature rather than additive: halving or doubling a norm are analogous relatively but req

Learning Latent Energy-Based Models via Interacting Particle Langevin Dynamics

arXiv:2510.12311v2 Announce Type: replace-cross Abstract: We develop interacting particle algorithms for learning latent variable models with energy-based priors. To do so, we leverage recent developm

Learning Mechanistic Reasoning for Chemical Reactions with Large Language Models

model-releasesarxiv-cs-cl

arXiv:2607.12771v1 Announce Type: cross Abstract: Reaction mechanisms consist of the step-by-step sequences of elementary reactions that explain chemical transformations. Learning the mechanism logic

Learning the Graphical Nature of Symmetries

arXiv:2607.12026v1 Announce Type: cross Abstract: Finite groups are rigid algebraic objects, whose Cayley graphs expose a rich network geometry through which group-theoretic structure can be measured,

Tutorials

Learning to Discretize: Diffusion-Based Adaptive Mesh with Spectral Guidance

arXiv:2607.11974v1 Announce Type: cross Abstract: Most neural partial differential equation (PDE) surrogates learn how fields evolve after a grid has already been chosen. However, before any operator

tutorialsarxiv-cs-ai

Learning When to Trust in Contextual Social Bandits

arXiv:2603.13356v2 Announce Type: replace Abstract: Robust reinforcement learning typically assumes that feedback sources are either globally trustworthy or corrupted within a fixed global budget. We

Local Ai

LEGO-SLAM: Language-Embedded Gaussian Optimization SLAM

arXiv:2511.16144v2 Announce Type: replace Abstract: Recent advances in 3D Gaussian Splatting (3DGS) have enabled Simultaneous Localization and Mapping (SLAM) systems to build photorealistic maps. Howe

local-aiarxiv-cs-cv

Lesion Segmentation in Moderate to Severe Traumatic Brain Injury: An nnU-Net Based Approach with Adaptive Normalization in the AIMS-TBI 2025 Challenge

arXiv:2607.12684v1 Announce Type: new Abstract: The segmentation of lesions in Moderate to Severe Traumatic Brain Injury (msTBI) from T1-weighted MRI presents a significant clinical challenge due to t

researcharxiv-cs-cv

Less Experts, Faster Decoding: Cost-Aware Speculative Decoding for Mixture-of-Experts

arXiv:2607.12696v1 Announce Type: cross Abstract: Sparse Mixture-of-Experts (MoE) models have become an important approach for scaling Large Language Models (LLMs), but their inference efficiency depe

Let RGB Be the Language of Vision

arXiv:2607.12450v1 Announce Type: new Abstract: This work introduces a unified formulation for vision models, where diverse forms of visual information beyond natural images, such as masks, depth maps

researcharxiv-cs-cv

Local Ai

Leveraging Prior Knowledge of Diffusion Model for Person Search

arXiv:2510.01841v2 Announce Type: replace Abstract: Person search aims to jointly perform person detection and re-identification by localizing and identifying a query person within a gallery of uncrop

local-aiarxiv-cs-cv

Local Ai

LIDAR-AD: A Decoder-Free Latent-Interaction Dreamer with Action-Residual Chains for Autonomous Driving

arXiv:2607.11964v1 Announce Type: new Abstract: Autonomous driving requires long-horizon closedloop decision making in dynamic traffic environments. Latent world models offer an effective framework fo

local-aiarxiv-cs-lg

Lightweight Multi-Scale Anomaly Detection for Resource-Constrained Edge Devices

arXiv:2607.12599v1 Announce Type: new Abstract: Time-series anomaly detection is increasingly important in IoT systems, sensor networks, and edge monitoring applications, where models must operate und

Line-Anchored Feedback Cuts Token Costs and Improves Correctness in AI Code Editing

arXiv:2607.12713v1 Announce Type: cross Abstract: Generated tokens are a direct driver of the cost, latency, and energy of generative AI (GAI) code editing. We show the format of feedback is a lever o

Linear Regression under Missing or Corrupted Coordinates

arXiv:2509.19242v2 Announce Type: replace-cross Abstract: We study multivariate linear regression under Gaussian covariates in two settings, where data may be erased or corrupted by an adversary under

LiteTopK: Exploiting the Curse of Dimensionality for a Fused Indexer-TopK Kernel in Long-Context Sparse Attention

arXiv:2607.11976v1 Announce Type: new Abstract: Indexer-TopK, the operation to compute the scores and select the top-k candidates, is widely used by sparse attention kernels in large language models a

LLM Judges Can Be Too Generous When There Is No Reference Answer

arXiv:2607.12885v1 Announce Type: new Abstract: LLM judges are increasingly being used to evaluate open-ended model responses, often in no-reference settings where a ground-truth answer is unavailable

researcharxiv-cs-cl

LLMs Can See the Smoke but not the Fire: Evaluating Abductive Reasoning with Elenchos

arXiv:2607.12733v1 Announce Type: new Abstract: Large language models (LLMs) excel at pattern recognition and text generation, but their capacity for abductive inference - inferring latent hypotheses

researcharxiv-cs-ai

Look, Focus, Act: Efficient and Robust Robot Learning via Human Gaze and Foveated Vision Transformers

arXiv:2507.15833v3 Announce Type: replace-cross Abstract: Human vision is a highly active process driven by gaze, which directs attention to task-relevant regions through foveation, dramatically reduc

Lost in the Maze: Overcoming Context Limitations in Long-Horizon Agentic Search

model-releasesarxiv-cs-cl

arXiv:2510.18939v2 Announce Type: replace Abstract: Long-horizon agentic search requires iteratively exploring the web over long trajectories and synthesizing information across many sources, enabling

Lost in Visual Translation: A VLM-Assisted Perceptual-Semantic Coherence Framework for EEG-to-Image Reconstruction

arXiv:2607.12364v1 Announce Type: cross Abstract: EEG-to-image evaluation should distinguish visual fidelity from recoverable meaning. Yet EEG-derived reconstructions are blurry, distorted, and low-de