Search: “papers”

When Freshness Is Not Enough: Distribution-Aware Age of Information for Networked LQR Control

arXiv:2606.04361v1 Announce Type: cross Abstract: Age of Information (AoI) has become a central metric for the design of wireless update systems, especially in applications where fresh measurements su

researcharxiv-cs-ro

4 Jun 2026

Safety

X4Val: Learning Neural Surrogates for Variance-Reduced Policy Evaluation

DGX agent

arXiv:2606.05159v1 Announce Type: new Abstract: Rigorous evaluation of learning-based robotic systems is an essential prerequisite for deployment. However, real-world test data is expensive to gather;

safetyarxiv-cs-ro

4 Jun 2026

A Hybrid Approach For Malware Classification Using Secondary Features Fusion

arXiv:2606.03432v1 Announce Type: cross Abstract: The number of malware (either variant or novel) is rapidly increasing, making malware detection and mitigation a complex problem. One approach to impr

Tutorials

A Systematic Evaluation of Current Architectures in Wind Power Forecasting

arXiv:2606.02849v1 Announce Type: new Abstract: Interval wind speed forecasting is essential for the efficient integration of wind energy into power systems, as it accounts for the inherent uncertaint

tutorialsarxiv-cs-lg

Acceptance-Test-Driven Evaluation Protocols for Business-Centric LLM Systems

arXiv:2606.02755v1 Announce Type: cross Abstract: Large language model (LLM) applications are increasingly expected to satisfy deterministic institutional requirements while relying on probabilistic g

Agent libOS: A Library-OS-Inspired Runtime for Long-Running, Capability-Controlled LLM Agents

arXiv:2606.03895v1 Announce Type: cross Abstract: Large language model (LLM) agents are evolving from request-response assistants into long-running software actors: they maintain state across model ca

local-aiarxiv-cs-ai

Agents

Agentic Chain-of-Thought Steering for Efficient and Controllable LLM Reasoning

arXiv:2606.03965v1 Announce Type: cross Abstract: Large language models improve final-answer accuracy through extended chain-of-thought reasoning, but often spend tokens inefficiently and offer little

agentsarxiv-cs-ai

Alignment-Aware Decoding

arXiv:2509.26169v2 Announce Type: replace Abstract: Alignment of large language models remains a central challenge in natural language processing. Preference optimization has emerged as a popular and

AmbientEye: A Dataset for Pupil Segmentation under Natural Ambient Infrared Illumination

model-releasesarxiv-cs-cv

arXiv:2606.03774v1 Announce Type: new Abstract: Eye tracking is essential for smart glasses, as it provides insight into user attention for ambient intelligence applications. However, most existing ey

An Exploration of Collision-based Enemy Morphology Generation

arXiv:2606.02832v1 Announce Type: new Abstract: Despite a great deal of prior research into Procedural Content Generation (PCG), relatively little prior work has explored generating enemies for video

AnchorMoE: Interpretable Time Series Classification via Anchor-Routed MoE

arXiv:2606.03631v1 Announce Type: cross Abstract: Multivariate time series classification (MTSC) is pivotal in high-stakes domains, such as clinical diagnosis and industrial fault detection, where saf

Are Deep Learning Based Hybrid PDE Solvers Reliable? Why Training Paradigms and Update Strategies Matter

arXiv:2602.06842v2 Announce Type: replace-cross Abstract: Deep learning-based hybrid iterative methods (DL-HIMs) integrate classical numerical solvers with neural operators, utilizing their complement

researcharxiv-cs-lg

Assessing and Mitigating Miscalibration in LLM-Based Social Science Measurement

arXiv:2605.11954v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in social science as scalable measurement tools for converting unstructured text into variables t

Assessing Pause Thresholds for empirical Translation Process Research

arXiv:2604.01410v2 Announce Type: replace Abstract: Text production (and translations) proceeds in the form of stretches of typing, interrupted by keystroke pauses. It is often assumed that fast typin

applicationsarxiv-cs-cl

Assessing Region-Level EEG Contributions to Cognitive Workload Prediction

arXiv:2606.02598v1 Announce Type: new Abstract: Accurate and generalizable estimation of cognitive workload from electroencephalography (EEG) is critical for human-centered and safety-critical systems

Auditable Climate Risk Intelligence from Fragmented ESG Data: Deterministic Orchestration and Imbalance-Aware Learning for Scope 1-3 Validation

arXiv:2606.02604v1 Announce Type: cross Abstract: ESG and climate risk data remain fragmented across heterogeneous Scope 1, Scope 2, and Scope 3 reporting environments, while conventional validation p

Beyond Single Solution: Multi-Hypothesis Collaborative Deep Unfolding Network for Image Compressive Sensing

arXiv:2606.03666v1 Announce Type: new Abstract: Recent deep unfolding networks (DUNs) have advanced Compressive Sensing (CS) by effectively integrating iterative optimization with deep learning archit

researcharxiv-cs-cv

Binary Road Surface Classification Using Machine Learning on Production Vehicle Signals During Cruising

arXiv:2606.02762v1 Announce Type: new Abstract: Knowledge of real-time road slipperiness, or even better, a refined estimate of peak grip potential, is a critical input for vehicle warning and interve

applicationsarxiv-cs-lg

Bionic Human-Motion Style Transfer for Physically Executable Whole-Body Control of Humanoid Robots

arXiv:2606.03536v1 Announce Type: new Abstract: Expressive whole-body motion is important for humanoid robots operating in human environments, where robots are expected to move stably while presenting

safetyarxiv-cs-ro

Bridging Auxiliary Constraints to Resolve Instruction Following in Large Reasoning Models

arXiv:2606.03624v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) have demonstrated impressive capabilities in many tasks, yet they struggle with reliably following multiple instructions,

Bridging Predictive Uncertainty and Safe Action: Sample-Conditioned Differentiable Planning for Autonomous Driving

arXiv:2606.03296v1 Announce Type: new Abstract: Complex, dynamic, and interactive driving environments pose significant challenges for autonomous driving, primarily due to the pervasive uncertainty of

safetyarxiv-cs-ro

Building Trust in Black-box Optimization: A Comprehensive Framework for Explainability

arXiv:2410.14573v2 Announce Type: replace-cross Abstract: Optimizing costly black-box functions within a constrained evaluation budget presents significant challenges in many real-world applications.

Calibrating Urban Traffic Simulation from Sparse Road Observations via Genetic Optimization

arXiv:2606.03823v1 Announce Type: new Abstract: Urban traffic simulation is a critical tool for infrastructure planning, including the placement of electric vehicle charging stations. However, realist

Can LLM Rerankers Predict Their Own Ranking Performance?

arXiv:2606.03535v1 Announce Type: cross Abstract: Retrieval effectiveness varies substantially across queries, making it important to estimate ranking quality before relevance judgments are available.

researcharxiv-cs-cl

Tutorials

Causal Evidence of Stack Representations in Modeling Counter Languages Using Transformers

arXiv:2606.03398v1 Announce Type: cross Abstract: Formal languages have proven to be effective conduits to understand the inner mechanisms of transformers. Past work has shown that transformers traine

tutorialsarxiv-cs-ai

Combining Statistical Features and Deep Encodings for Rehearsal-Based Class-Incremental Time Series Classification

model-releasesarxiv-cs-lg

arXiv:2606.03292v1 Announce Type: cross Abstract: Many systems used in real-world environments require adding new categories and incorporating new information without forgetting what was previously le

Cost-Aware Query Routing in RAG: Empirical Analysis of Retrieval Depth Tradeoffs

arXiv:2606.02581v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) faces a fundamental three-way tension: deeper retrieval improves factual grounding but inflates token costs and e

Coupled Local and Global World Models for Efficient First Order RL

arXiv:2602.06219v2 Announce Type: replace-cross Abstract: World models offer a promising avenue for more faithfully capturing complex dynamics, including contacts and non-rigidity, as well as complex

local-aiarxiv-cs-ai

CropCraft: A Procedural World Generator for Robotic Simulation of Agricultural Tasks

arXiv:2511.02417v2 Announce Type: replace Abstract: The adoption of agroecological practices in modern agriculture requires robotic systems capable of operating in highly diverse and complex field env

researcharxiv-cs-cv

Demystifying Pipeline Parallelism: First Theory for PipeDream

arXiv:2606.03498v1 Announce Type: new Abstract: Training modern machine learning models increasingly requires computation to be distributed across many accelerators. Data parallelism remains the defau

local-aiarxiv-cs-lg

Diagnosis of Human Object Interaction Detectors for Real World Educational Applications

model-releasesarxiv-cs-cv

arXiv:2606.02789v1 Announce Type: new Abstract: Human-object interaction (HOI) recognition is critical for automatically analyzing student behavior in complex educational environments. Although state-

Do Explanations Increase the Risk of Decision Logic Leakage? Explanation-Guided Stealing of Graph Models

arXiv:2506.03087v2 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) have become essential tools for analyzing graph-structured data in domains such as drug discovery and financial a

safetyarxiv-cs-ai

DriftSched: Adaptive QoS-Aware Scheduling under Runtime Token Drift for Multi-Tenant GPU Inference

arXiv:2606.02982v1 Announce Type: cross Abstract: The rapid growth of large language model (LLM) inference services has increased the demand for efficient multi-tenant GPU scheduling. While modern inf

Dynamic Objective Selection with Safeguards and LLM Oversight for Financial Decision-Making

arXiv:2606.03704v1 Announce Type: new Abstract: Financial decision-making tasks such as stock recommendation and portfolio allocation typically estimate future return and risk and then select trades o

Dynamic Short Convolutions Improve Transformers

arXiv:2606.03825v1 Announce Type: cross Abstract: Transformers have become the dominant architecture for large language models, largely due to the scalability and flexibility of attention, feed-forwar

safetyarxiv-cs-cl

E2LLM: Towards Efficient LLM Serving in Heterogeneous Edge/Fog Environments

arXiv:2606.03770v1 Announce Type: cross Abstract: Large Language Models (LLMs) have become integral to modern applications, yet their deployment remains challenging. Beyond executing the models themse

Edge-Aware and Content-Adaptive Infrared Gas Leak Detection for Industrial Safety Monitoring

arXiv:2512.23234v3 Announce Type: replace-cross Abstract: Infrared gas leak detection is important for industrial safety and environmental monitoring, but automatic detection remains challenging becau

local-aiarxiv-cs-ai

Efficient Hyperparameter Optimization for LLM Reinforcement Learning

arXiv:2606.03073v1 Announce Type: cross Abstract: Reinforcement learning (RL) for large language models (LLMs) is highly sensitive to hyperparameter configurations, making hyperparameter optimization

Enhanced Renewable Energy Forecasting using Context-Aware Conformal Prediction

arXiv:2510.15780v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) is increasingly used to support renewable energy forecasting and grid operations. As renewable penetration grows,

local-aiarxiv-cs-lg

Enhancing Operational Safety via Agentic Dialogue Hazard Identification Analysis

arXiv:2606.03812v1 Announce Type: new Abstract: Operational safety in high-stakes domains such as industrial process control, autonomous, and safety-critical systems, demand reliable hazard identifica

safetyarxiv-cs-ai

Evaluating and Calibrating LLM Confidence on Questions with Multiple Correct Answers

model-releasesarxiv-cs-cl

arXiv:2602.07842v2 Announce Type: replace Abstract: Confidence calibration is essential for making large language models (LLMs) reliable, yet existing training-free methods have been primarily studied

Extreme Motion Generation via Hybrid Null-Space Control for Straight-Line Path Following

arXiv:2606.03390v1 Announce Type: new Abstract: This work studies ``extreme motion generation'', which aims to maximize the Cartesian path length along a pre-defined trajectory within the manipulator'

safetyarxiv-cs-ro

Fast Organic Crystal Structure Prediction with Unit Cell Flow Matching

arXiv:2606.03199v1 Announce Type: new Abstract: Organic crystal structure prediction (CSP) is a requirement for computational modelling of organic solids, but traditionally costs several CPU-years per

Tutorials

FCUS-rPPG: A Fast-Converging Unsupervised Framework for Remote Photoplethysmography via Gradient Oscillation Suppression

arXiv:2606.03050v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) enables non-contact extraction of blood volume pulse (BVP) signals using consumer-grade cameras. Recent unsupervised

tutorialsarxiv-cs-cv

FlashMLA-ETAP: Efficient Transpose Attention Pipeline for Accelerating MLA Inference on NVIDIA H20 GPUs

arXiv:2506.01969v3 Announce Type: replace-cross Abstract: Efficient inference of Multi-Head Latent Attention (MLA) is challenged by deploying the DeepSeek-R1 671B model on a single Multi-GPU server. T

FLIPS: Instance-Fingerprinting for LLMs via Pseudo-random Sequences

arXiv:2606.03330v1 Announce Type: cross Abstract: Literature reveals that a Large Language Model's (LLM) behavior is not only conditioned by its original weights but also its instance-level parameters

Agents

FORGE: Multi-Agent Graduated Exploitation and Detection Engineering

arXiv:2606.03453v1 Announce Type: cross Abstract: Vulnerability disclosure volumes now far exceed organizational assessment capacity, yet three adjacent research communities (proof-of-concept generati

agentsarxiv-cs-ai

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

local-aiarxiv-cs-cv