Search: “papers”

An Integrated Roadside Sensing and Communication Framework for Vulnerable Road User Safety at Signalized Intersections

model-releasesarxiv-cs-cv

arXiv:2606.07016v1 Announce Type: cross Abstract: Vulnerable road users (VRUs) account for approximately half of urban traffic deaths globally, with intersections concentrating a disproportionate shar

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Research

Applying Deep Learning for cockpit segmentation in the context of mixed reality

DGX agent

arXiv:2606.06520v1 Announce Type: new Abstract: Computer vision is an area that has been growing continuously. With the advance of technologies with a first-person view, new development opportunities

researcharxiv-cs-cv

8 Jun 2026

Local Ai

Attention-Guided Autoencoder Fusion for Insulator Defect Detection Using UAV Transmission-Line Imaging

arXiv:2606.06536v1 Announce Type: cross Abstract: Automated defect detection in high-voltage transmission-line insulators remains challenging due to severe class imbalance, large scale variation, and

local-aiarxiv-cs-ai

Beyond Post-hoc Explanation: Toward Glassbox AI via Probabilistic Mediation

arXiv:2606.07113v1 Announce Type: new Abstract: Large language models are rapidly becoming infrastructural components in high-stakes institutional settings, including public administration, legal reas

Bounded-Abstention Pairwise Learning to Rank

arXiv:2505.23437v2 Announce Type: replace-cross Abstract: Ranking systems influence decision-making in high-stakes domains like health, education, and employment, where they can have substantial econo

Breaking the Ice: Analyzing Cold Start Latency in vLLM

arXiv:2606.07362v1 Announce Type: new Abstract: As scalable inference services become popular, the cold start latency of an inference engine becomes important. Today, vLLM has evolved into the de fact

ChronoForest: Closed-Loop Multi-Tree Diffusion Planning for Efficient Bridge Search and Route Composition

arXiv:2606.06618v1 Announce Type: cross Abstract: How can we plan long-horizon routes that reach designated goals, visit required waypoints, and remain short when only short-horizon offline trajectori

CoMetaPNS: Continually Meta-learning Personalized Neural Surrogates for Cardiac Electrophysiology Simulations

arXiv:2606.07488v1 Announce Type: new Abstract: Personalized virtual heart simulations face challenges in model personalization and computational cost. While neural surrogates offer state-of-the-art s

Consistent-Inversion: Reverse Consistency Guidance for Structure-Preserving Visual Editing

arXiv:2606.07145v1 Announce Type: new Abstract: Text-guided diffusion models have become effective tools for real-image visual editing, where the edited image must follow a target instruction while pr

safetyarxiv-cs-cv

DataEvolver: Automatic Data Preparation for Large Language Models through Multi-Level Self-Evolving

arXiv:2606.07001v1 Announce Type: cross Abstract: High-quality training data is essential to large language models (LLMs) and typically requires extensive and costly manual curation. Existing automati

DEFINED: A Data-Efficient Computational Framework for Fine-Grained Creativity Assessment in Debate Scenarios

arXiv:2606.07226v1 Announce Type: cross Abstract: Human creativity has emerged as a critical competency in the era of large language models. Assessing creativity in complex, open-ended environments is

DIFFRACT: Neuralized Utility Maximization for Wireless Networks by Differentiable Programming

arXiv:2606.07114v1 Announce Type: cross Abstract: Next-generation wireless networks, including satellite-to-Open RAN systems, demand agile and intelligent resource management capable of handling dynam

DirectAudioEdit: Inversion-Free Text-Guided Audio Editing via Diffusion Prediction Contrast

arXiv:2606.07356v1 Announce Type: cross Abstract: Text-guided audio editing aims to modify the language-specified acoustic content while preserving edit-irrelevant source components. Existing training

researcharxiv-cs-cl

Discovering Interpretable Algorithms by Decompiling Transformers to RASP

arXiv:2602.08857v2 Announce Type: replace-cross Abstract: Recent work has shown that the computations of Transformers can be simulated in the RASP family of programming languages. These findings have

DOPPLER: Dual-Policy Learning for Device Assignment in Asynchronous Dataflow Graphs

arXiv:2505.23131v2 Announce Type: replace Abstract: We study the problem of assigning operations in a dataflow graph to devices to minimize execution time in a work-conserving system, with emphasis on

safetyarxiv-cs-lg

Local Ai

EASE-TTT: Evidence-Aligned Selective Test-Time Training for Long-Context Question Answering

arXiv:2606.06906v1 Announce Type: cross Abstract: Long-context question answering (QA) remains challenging for smaller language models even when answer-bearing evidence is already present in the input

local-aiarxiv-cs-ai

Enhancing Conformal Prediction via Class Similarity

arXiv:2511.19359v2 Announce Type: replace Abstract: Conformal Prediction (CP) has emerged as a powerful statistical framework for high-stakes classification applications. Instead of predicting a singl

Explainable Runtime Dependency Tracking for AI-RAN Conflict Monitoring

model-releasesarxiv-cs-lg

arXiv:2606.06663v1 Announce Type: new Abstract: Future AI-integrated Radio Access Networks (AI-RAN) will combine open programmability with learning-enabled xApps, rApps, and control functions that act

Extending Responsibility-Sensitive Safety for the Assessment of Offloaded Autonomous Driving Services

arXiv:2606.07067v1 Announce Type: new Abstract: Safety is a fundamental requirement in the development of autonomous driving (AD) systems. While function offloading has demonstrated significant benefi

safetyarxiv-cs-ro

Agents

Feasible Action Space Reduction for Quantifying Causal Responsibility in Continuous Spatial Interactions

arXiv:2505.17739v2 Announce Type: replace-cross Abstract: Understanding the causal influence of one agent on another agent is crucial for safely deploying artificially intelligent systems such as auto

agentsarxiv-cs-ro

Agents

From Pixels to Shelf: An Integrated Robotic System for Autonomous Supermarket Stocking with a Mobile Manipulator

arXiv:2509.11740v2 Announce Type: replace Abstract: Autonomous stocking in retail environments, particularly supermarkets, presents challenges due to dynamic human interactions, constrained spaces, an

agentsarxiv-cs-ro

Generalization in Deep Neural Networks: Minimax Rates for Gradient Methods

arXiv:2606.06772v1 Announce Type: cross Abstract: Understanding the generalization performance of over-parameterized neural networks has become a central topic in deep learning theory. While recent ad

Geometric Second-Order Feature Correlation Learning for Self-Supervised Speech Emotion Recognition

arXiv:2606.06550v1 Announce Type: cross Abstract: Self-supervised learning (SSL) yields powerful, context-rich representations for speech emotion recognition (SER), yet aggregating these representatio

Agents

GOPAgen: Motion-Aware and Efficient Agentic Long-Video Understanding with Structural Memory and Hierarchical Reasoning

arXiv:2606.06532v1 Announce Type: new Abstract: Despite significant progress in agentic long video understanding, existing methods still lack detailed motion comprehension coupled with an efficient me

agentsarxiv-cs-cv

Hierarchical Forecast Reconciliation for Urban Rail Transit Demand Prediction under Operational Disruptions

arXiv:2606.07044v1 Announce Type: new Abstract: Accurate and coherent passenger demand forecasting is essential for Urban Rail Transit (URT) operations. Passenger demand has a hierarchical structure i

HORUS: A Mixed Reality Interface for Managing Teams of Mobile Robots

arXiv:2506.02622v2 Announce Type: replace Abstract: Mixed Reality (MR) interfaces have been extensively explored for controlling mobile robots, but there is limited research on their application to ma

researcharxiv-cs-ro

LiQSS: Post-Transformer Linear Quantum-Inspired State-Space Tensor Networks for Real-Time 6G

model-releasesarxiv-cs-lg

arXiv:2601.12375v3 Announce Type: replace-cross Abstract: Proactive and agentic control in Sixth-Generation (6G) Open Radio Access Networks (O-RAN) requires control-grade prediction under stringent Ne

MetaConfigurator: AI-Assisted RDF Authoring from JSON Data

arXiv:2606.07094v1 Announce Type: cross Abstract: Scientific workflows increasingly generate structured JSON data that is easy to exchange but difficult to interpret consistently across systems due to

Applications

Mind the Gap: Bridging Behavioral Silos with LLMs in Multi-Vertical Recommendations

arXiv:2606.06779v1 Announce Type: cross Abstract: In multi-vertical e-commerce platforms like DoorDash, relatively newer product verticals such as grocery and retail present a significant opportunity

applicationsarxiv-cs-ai

MotionEnhancer: Leveraging Video Diffusion for Motion-Enhanced Vision-Language Models

model-releasesarxiv-cs-ai

arXiv:2606.06853v1 Announce Type: cross Abstract: The new era has witnessed a remarkable capability to extend Vision-Language Models (VLMs) for tackling tasks of video understanding. While current VLM

Tutorials

No-Harm Physics-Informed Inverse Learning with Residual-Calibrated Uncertainty

arXiv:2606.07153v1 Announce Type: cross Abstract: Physics-informed learning is increasingly used for partial differential equation (PDE)-governed inverse problems, but its reliability remains difficul

tutorialsarxiv-cs-lg

OffQ: Taming Structured Outliers in LLM Quantization by Offsetting

arXiv:2606.07116v1 Announce Type: cross Abstract: Low-bit quantization has been widely adopted to accelerate the inference of large language models (LLMs) by significantly reducing computational cost

Optimal Rates for Generalization of Gradient Descent Methods with Deep Neural Networks

arXiv:2606.06764v1 Announce Type: cross Abstract: Recent progress has been made in understanding the statistical generalization performance of gradient descent methods for overparameterized neural net

OPTIMUS-Prime: Minimal and Sufficient Concept Explanations for Deep Vision Models

model-releasesarxiv-cs-cv

arXiv:2606.07180v1 Announce Type: new Abstract: The growing demand for transparency in automated decision-making has propelled eXplainable Artificial Intelligence (XAI) to the forefront of machine lea

Performance Variation in Deep Reinforcement Learning

arXiv:2606.06746v1 Announce Type: new Abstract: Deep reinforcement learning (RL) algorithms often suffer from low run-to-run robustness, manifesting as significant performance variation across indepen

Position: Don't Just 'Fix it in Post': A Science of AI Must Study Training Dynamics

arXiv:2606.06533v1 Announce Type: new Abstract: What would it mean to have a scientific understanding of AI? Models are not static objects: they are snapshots of time-evolving processes shaped by data

Progress-SQL: Improving Reinforcement Learning for Text-to-SQL via Progressive Rewards

arXiv:2606.06825v1 Announce Type: cross Abstract: Reinforcement learning has recently shown promise in improving large language models for Text-to-SQL generation, yet existing methods typically optimi

QuadVerse: An Integrated Framework Aligning Visual-Physical Reality for Quadruped Simulation

arXiv:2606.07118v1 Announce Type: new Abstract: Simulation is central to robot learning, yet the sim-to-real gap remains a major bottleneck.Existing approaches often tackle visual or dynamic gaps sepa

safetyarxiv-cs-ro

Re-Centering Humans in LLM Personalization

arXiv:2606.06614v1 Announce Type: cross Abstract: Despite growing interest, most evaluations of large language models' (LLMs') personalization abilities have relied on synthetic data. It remains uncle

Re-imagining ISO 26262 in the Age of Autonomous Vehicles: Enhancing Controllability through Transferability and Predictability

arXiv:2606.07437v1 Announce Type: cross Abstract: The ISO 26262 standard defines functional safety for road vehicles through risk assessments based on Severity, Exposure, and Controllability, grounded

Robots Need More than VLA and World Models

arXiv:2606.06556v1 Announce Type: new Abstract: Generalist robot intelligence is often framed as a policy-scaling problem: collect more robot demonstrations, train larger Vision-Language-Action (VLA)

safetyarxiv-cs-ro

Robustly estimating heterogeneity in factorial data using Rashomon Partitions

arXiv:2404.02141v5 Announce Type: replace-cross Abstract: In both observational data and randomized control trials, researchers select statistical models to articulate how the outcome of interest vari

Hardware

Scalable Joint Resource Allocation for SLO-Constrained LLM Inference in Heterogeneous GPU Clouds

arXiv:2604.07472v2 Announce Type: replace Abstract: Serving large language model (LLM) inference in cloud environments requires jointly optimizing model selection, GPU provisioning, parallelism config

hardwarearxiv-cs-lg

Second-Order Path Kernel Interpolation Formulas in Machine Learning

arXiv:2606.07495v1 Announce Type: new Abstract: Understanding how training data shape neural network predictions is a central problem in modern learning theory. In 2020, Pedro Domingos proposed an int

SecretFan: Synthesizing Realistic Data without Breaking Privacy

arXiv:2602.05833v2 Announce Type: replace Abstract: There is a need for synthetic training and test datasets that replicate statistical distributions of original datasets without compromising their co

Self-evolving LLM agents with in-distribution Optimization

arXiv:2606.07367v1 Announce Type: new Abstract: Large Language Models (LLMs) have recently emerged as powerful controllers for interactive agents in complex environments, yet training them to perform

safetyarxiv-cs-lg

Spline Policy: A Structured Representation for Robot Policies

model-releasesarxiv-cs-ro

arXiv:2606.07386v1 Announce Type: new Abstract: Modern imitation-learning policies for robot manipulation often represent actions as fixed-resolution action chunks, which are simple and effective but

Stream3D-VLM: Online 3D Spatial Understanding with Incremental Geometry Priors

model-releasesarxiv-cs-cv

arXiv:2606.06891v1 Announce Type: new Abstract: Despite advances in 3D scene understanding, existing 3D Large Multimodal Models operate in offline settings, requiring complete scene observations or pr