Search: “papers”

Single-Rollout Asynchronous Optimization for Agentic Reinforcement Learning

arXiv:2607.07508v1 Announce Type: cross Abstract: Reinforcement learning (RL) is becoming increasingly important for post-training large language models (LLMs). Previous RL pipelines for LLMs were mos

safetyarxiv-cs-ai

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Smart Scissor: Coupling Spatial Redundancy Reduction and CNN Compression for Embedded Hardware

DGX agent

arXiv:2607.06915v1 Announce Type: new Abstract: Scaling down the resolution of input images can greatly reduce the computational overhead of convolutional neural networks (CNNs), which is promising fo

local-aiarxiv-cs-cv

9 Jul 2026

SmartHomeSecure: Automated Detection and Repair of Smart Home Configuration Errors Using Large Language Models

arXiv:2607.06748v1 Announce Type: cross Abstract: Smart home automation platforms increasingly rely on user-authored YAML configuration files to define device behaviors, but these files are prone to s

SoccerNet 2026 Challenges Results

arXiv:2607.07320v1 Announce Type: new Abstract: The SoccerNet 2026 Challenges constitute the sixth annual edition of the SoccerNet open benchmarking effort, dedicated to advancing computer vision rese

Stability of Flow Models for Graph Signals

arXiv:2607.07510v1 Announce Type: cross Abstract: Generating signals on graphs requires permutation-equivariant models that exhibit stability with respect to relative structural perturbations. While f

applicationsarxiv-cs-ai

STAGformer: A Spatio-temporal Agent Graph Transformer for Micro Mobility Demand Forecasting

arXiv:2607.06614v1 Announce Type: cross Abstract: Accurate station-level demand forecasting is essential for the efficient operation of bike-sharing systems, yet it remains challenging due to complex

Strategies for Span Labeling with Large Language Models

arXiv:2601.16946v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used for text analysis tasks, such as named entity recognition or error detection. Unlike encoder-base

researcharxiv-cs-cl

Superstate Quantum Mechanics

arXiv:2502.00037v4 Announce Type: replace-cross Abstract: We introduce Superstate Quantum Mechanics (SQM), a theory that considers states in Hilbert space subject to multiple quadratic constraints, wi

researcharxiv-cs-lg

T2T-VICL: Cross-Task Visual In-Context Learning via Implicit Text-Driven VLMs

arXiv:2511.16107v3 Announce Type: replace-cross Abstract: Visual in-context learning (VICL) solves visual tasks by conditioning on a few input-output demonstrations without any model training. Recent

safetyarxiv-cs-ai

TACoS: Weakly Supervised Learning of Two-Dimensional Materials from Scribble Annotations to Precise Segmentation

arXiv:2607.07169v1 Announce Type: new Abstract: The precise pixel-level localization of 2D material flakes is crucial for high-throughput screening. However, traditional fully supervised methods rely

Towards Agentic AI Governance: A Preliminary Assessment

arXiv:2607.07612v1 Announce Type: cross Abstract: Artificial intelligence is rapidly evolving from generative systems to agentic AI capable of autonomously planning and executing tasks. Widely charact

Transformer-based segmentation of prosodic boundaries in Brazilian Portuguese

arXiv:2607.07408v1 Announce Type: new Abstract: Automatic prosodic segmentation identifies boundaries between speech units from acoustic and linguistic evidence. Although recent deep learning approach

researcharxiv-cs-cl

Understanding Interpretation Difficulty in Harmful Online Communication: Insights from Cybercrime Communities

arXiv:2607.07277v1 Announce Type: new Abstract: Harmful online communication often contains slang, coded terms, abbreviations, and community-specific expressions, which make messages difficult to inte

local-aiarxiv-cs-cl

URS-Stereo: Uncertainty-Guided Residual Search for Real-Time Stereo Matching

arXiv:2607.06779v1 Announce Type: new Abstract: Real-time stereo matching is crucial for robotics, autonomous systems, and embedded vision applications, where both computational efficiency and dispari

local-aiarxiv-cs-cv

Zero-Human Demonstration End-to-end Autonomous Driving with Trajectory Scorer

arXiv:2510.24108v2 Announce Type: replace-cross Abstract: Human demonstrations are widely considered the cornerstone of end-to-end (E2E) autonomous driving despite human demonstration's scarcity for l

A Task-Driven Evaluation of UAV Detection and Tracking under Synthetic Fog

arXiv:2607.05467v1 Announce Type: new Abstract: Fog severely degrades the visibility of small unmanned aerial vehicles (UAVs) in skydominant, long-range imagery, reducing the reliability of downstream

researcharxiv-cs-cv

Agents That Teach: Towards Designing Incidental Learning Back into AI-Assisted Software Development

arXiv:2607.06101v1 Announce Type: cross Abstract: AI coding agents are rapidly reshaping how software is built, with developers increasingly delegating substantial coding tasks to autonomous agents in

AlayaWorld: Long-Horizon and Playable Video World Generation

arXiv:2607.06291v1 Announce Type: new Abstract: Game worlds have traditionally been built through labor-intensive production pipelines, making them costly to develop, difficult to customization, and e

Assessing the Operational Impact of Poisoning Attacks over Augmented 3D Point Cloud Public Datasets for Connected and Autonomous Vehicles

arXiv:2607.06484v1 Announce Type: cross Abstract: Poisoning attacks against public datasets lead to major concerns, such as (i) misclassification of perceived objects when the poisoned data is used fo

agentsarxiv-cs-cv

Benchmarking KV-Cache Optimizations across Task Quality and System Performance for Long-Context Serving

arXiv:2607.05399v1 Announce Type: cross Abstract: Large language model serving is increasingly limited by KV-cache growth under long-context workloads, yet existing KV-cache compression techniques are

Benign Overfitting with Quantum Kernels

arXiv:2503.17020v2 Announce Type: replace-cross Abstract: Kernel methods compare inputs through feature maps. Quantum kernels follow the same principle: input data are encoded into quantum states, whi

researcharxiv-cs-lg

BitFair: A 12nm Bit-Serial CNN Accelerator with Learnable Early Termination and Adaptive Bit Ordering for Ultra-Low-Power XR Vision

arXiv:2607.05445v1 Announce Type: cross Abstract: Extended Reality (XR) wearables require always-on perception within tight power envelopes of a few watts and motion-to-photon latency budgets below 20

researcharxiv-cs-cv

Bridging Diffusion Pruning and Step Distillation with Teacher-Aligned Repair

arXiv:2607.06335v1 Announce Type: new Abstract: Diffusion models generate high-quality images, but their inference cost comes from two sources: large denoising networks and repeated denoising steps. E

Calf-Integrated Arms for Bimanual Quadruped Loco-Manipulation

arXiv:2607.06186v1 Announce Type: new Abstract: Most quadruped loco-manipulation designs trade manipulation capability against stance. A trunk-mounted arm sits high and usually carries a single arm; u

agentsarxiv-cs-ro

CanvasAgent: Enabling Complex Image Creation and Editing via Visual Tool Orchestration

arXiv:2607.05465v1 Announce Type: cross Abstract: Complex image creation and editing often require more than a single generation or editing model. A user request may involve synthesizing images, local

CHARLIE: An On-Premise Multi-Agent Retrieval-Augmented Generation System for Evidential Reasoning in Forensic Science

arXiv:2607.05428v1 Announce Type: cross Abstract: We present Charlie, an on-premise multi-agent Retrieval-Augmented Generation (RAG) system for structured evidential processing in digital forensic env

local-aiarxiv-cs-ai

Hardware

Clustering-Embedded Model Predictive Path Integral Control: Avoiding Averaging-Induced Failure and Enabling Efficient Cluster Selection for Dynamic Obstacles

arXiv:2607.06499v1 Announce Type: new Abstract: With the widespread availability of parallel computing hardware, sampling-based motion planning methods such as Model Predictive Path Integral (MPPI) co

hardwarearxiv-cs-ro

CMDR: Contextual Multimodal Document Retrieval

arXiv:2607.05927v1 Announce Type: cross Abstract: Multimodal document retrieval aims to retrieve relevant pages while preserving both textual and visual content from the original document. However, ex

Danus: Orchestrating Mathematical Reasoning Agents with Fact-Graph Memory

arXiv:2607.06447v1 Announce Type: new Abstract: Recent LLM-based mathematical reasoning agents have begun to tackle research-level problems and, in several cases, have contributed to the resolution of

Data-dependent Evaluations for Budgeted Submodular Maximization

arXiv:2607.05759v1 Announce Type: cross Abstract: Submodular maximization is an important building block for developing algorithms in many areas such as machine learning and data mining. Due to the NP

applicationsarxiv-cs-ai

Diffusion Language Model Parallel Decoding via Product-of-Experts Bridge

arXiv:2606.08048v1 Announce Type: cross Abstract: Diffusion language models (DLMs) offer substantial speed advantages through parallel decoding, but the lack of token dependencies limits generation qu

researcharxiv-cs-lg

Do It Right! A Methodology for Successful NLP System Development

arXiv:2607.05644v1 Announce Type: cross Abstract: Natural language processing (NLP) is a common method for supplying data to clinical research and decision making by extracting information from electr

Dynamic Evaluation of Classical and Control-Aware Optimal Trajectory Planning in Robot Manipulators

arXiv:2607.05544v1 Announce Type: new Abstract: Trajectory planning strongly influences tracking accuracy, actuator demand, and overall execution behavior in robotic manipulators. Classical planners s

researcharxiv-cs-ro

EeveeDark: A Binary Neural Framework for Low-Light Video Enhancement via Event-Guided Sensor-Level Fusion

arXiv:2607.06217v1 Announce Type: new Abstract: Enhancing videos under extreme low-light conditions remains challenging due to the difficulty of balancing restoration quality and computational efficie

Empirical Minimal-Realisation Compression of Deep Neural Networks via Controllability-Observability Tests

arXiv:2607.05457v1 Announce Type: cross Abstract: Deep neural networks often contain substantial hidden-state redundancy, but most compression methods operate directly on weights, neurons, or quantise

ExplAIner: A Declarative Query Language for Explaining Classification Models

arXiv:2607.06407v1 Announce Type: new Abstract: The XAI community has studied a wide range of queries and scores for explaining predictions of ML models. From a data management perspective, this proli

FedDAF: Federated Domain Adaptation Using Model Functional Distance

arXiv:2509.11819v2 Announce Type: replace-cross Abstract: Federated Domain Adaptation (FDA) is a federated learning (FL) approach that improves model performance at the target client by collaborating

Federated Physics-Grounded Reinforcement Learning for Distributed Stability Control in Smart Grids

model-releasesarxiv-cs-lg

arXiv:2607.05553v1 Announce Type: new Abstract: Transient stability control in smart grids requires rapid post-fault damping of generator frequency and rotor angle deviations to prevent cascading fail

Few-Medoids: An Embarrassingly Simple Coreset Selection Method for Few-Shot Knowledge Distillation

arXiv:2607.05891v1 Announce Type: cross Abstract: Coreset selection aims to identify a small and highly representative subset of a massive dataset for efficient model training. The problem remains cha

Freqformer: Image-Demoireing Transformer via Effective Frequency Decomposition

arXiv:2505.19120v2 Announce Type: replace Abstract: Image demoireing remains a challenging task due to the complex interplay between texture corruption and color distortions caused by moire patterns.

local-aiarxiv-cs-cv

From Application-Layer Simulation to Native Meta-Architecture: Structural Tension as an Endogenous Driver for Heterogeneous AI Evolution

arXiv:2607.06269v1 Announce Type: new Abstract: Current large language models (LLMs) are fundamentally stateless: their behavior is fully determined by input at inference time, and any higher-order co

safetyarxiv-cs-ai

From Graphs to Gradients: Physics-Inspired Structural Attribution for Cyber-Physical IoT Systems and Beyond

arXiv:2607.05563v1 Announce Type: new Abstract: Interpretable explanation methods in Artificial Intelligence aim to uncover the underlying causes and their effects, enabling a deeper understanding of

From Passive Observer to Active Critic: Reinforcement Learning Elicits Process Reasoning for Robotic Manipulation

arXiv:2603.15600v2 Announce Type: replace-cross Abstract: Accurate process supervision remains a critical challenge for long-horizon robotic manipulation. A primary bottleneck is that current video ML

GaussFusion: Towards Multimodal 3D Gaussian Pretraining

arXiv:2607.05906v1 Announce Type: new Abstract: 3D Gaussian Splatting provides an explicit representation that jointly models geometry and appearance, serving as a scalable foundation for 3D represent

Ground3D-LMM: Fine-Grained 3D Point Grounding and Spatial Reasoning with LMM

arXiv:2607.05493v1 Announce Type: new Abstract: Natural-language queries about 3D environments become actionable when responses are verifiable and metric. Verifiability requires explicit grounding to

Hierarchical Acoustic-Semantic Modeling: Modality Separation and Semantic Coherence for Full-Duplex SLMs

model-releasesarxiv-cs-cl

arXiv:2607.06540v1 Announce Type: new Abstract: Developing seamless, high-performance, native intelligent full-duplex Spoken Language Models (SLMs) remains a critical challenge and long-standing goal

Hilti-Trimble-Oxford Dataset: 360 Visual-Inertial Benchmark with Floor Plan Priors for SLAM and Localization

model-releasesarxiv-cs-ro

arXiv:2607.06464v1 Announce Type: new Abstract: Automated progress monitoring on construction sites is an active area of research and development. Robot and human-carried mapping systems have been dev

Tutorials

How Can Mamba Learn In Context with Outliers and Generalize Provably?

arXiv:2510.00399v2 Announce Type: replace Abstract: The Mamba model has gained significant attention for its computational advantages over Transformer-based models, while achieving comparable performa

tutorialsarxiv-cs-lg