Search: “papers”

LLM-as-an-Improver: Turning Verification into Better Candidates

arXiv:2609.19515v1 Announce Type: new Abstract: Verifier-based selection improves LLM performance by generating multiple candidate solutions and using a verifier to select the most promising one. Howe

researcharxiv-cs-ai

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LLM-Guided Transformation of Non-Critical Driving Scenes into Safety-Critical Scenarios Using Augmented Reality

DGX agent

arXiv:2609.20318v1 Announce Type: cross Abstract: Testing Autonomous Driving Systems (ADS) requires realistic safety-critical scenarios, but collecting such data from real-world driving is costly and

safetyarxiv-cs-ai

18 Sept 2026

Model-based Bootstrap for Offline Policy Evaluation in Tabular Reinforcement Learning

arXiv:2609.20389v1 Announce Type: cross Abstract: Offline policy evaluation (OPE) is crucial in high-stakes reinforcement learning applications, where new policies must be assessed reliably before dep

Local Ai

Not All AI Agents Are Equal: Characterizing Resource and Performance Dynamics

arXiv:2609.19947v1 Announce Type: new Abstract: LLM-based AI agents process user requests through iterative reasoning and tool execution, often involving the invocation of remote LLM APIs with local t

local-aiarxiv-cs-ai

Odds-Ratio Thompson Sampling: A Specification and Design Guide for Contrast-Based Multi-Armed Bandits

arXiv:2609.19709v1 Announce Type: new Abstract: Batched multi-armed bandits update on a service's own schedule, and the usual implementation carries each arm's absolute reward rate from one update to

OHRID-Retail: An Open Multimodal Dataset of Human Activity in Retail Environments

arXiv:2609.19302v1 Announce Type: new Abstract: Open datasets describing human behavior in environments shared with mobile robots remain limited, particularly for retail activities that combine locomo

researcharxiv-cs-ro

Open-vocabulary 3D object detection with promptable segmentation

arXiv:2609.19358v1 Announce Type: new Abstract: Three-dimensional object detection for autonomous driving is dominated by detectors trained on large corpora of human-annotated 3D boxes. Such a detecto

agentsarxiv-cs-cv

Past, Future, All at Once: Mitigating Stability-Plasticity Dilemma via Post-hoc JANUS Rectification

arXiv:2609.19985v1 Announce Type: cross Abstract: Fine-tuning foundation models on new tasks inevitably suffer from catastrophic forgetting. While existing works attempt to mitigate this on the basis

Perception, Layout, and Validation: Calibrated Confidence for Reliable Straight-Through Processing of Financial Documents

arXiv:2609.20110v1 Announce Type: new Abstract: Straight-through processing (STP) on extracted key-value fields from financial documents without human review requires a calibrated probability together

Personalising a Cross-User Surface Electromyography Encoder Under a Small Calibration Budget

arXiv:2609.20296v1 Announce Type: new Abstract: A myoelectric interface needs calibration from the user before it will function. Earlier work has treated calibration as a quantity, but has not asked t

Position: It is Time to Virtualize Foundation Models with a Self-evolving Operating System Layer

arXiv:2609.19203v1 Announce Type: new Abstract: AI applications have shifted from single, monolithic foundation models (FM) to compound agentic systems. Yet today's stacks remain fragmented: even as p

PrefixBench-H100: Characterizing Prefix Reuse and Time-to-First-Token in H100 LLM Serving

arXiv:2609.19657v1 Announce Type: cross Abstract: Repeated prompt prefixes are increasingly common in LLM serving workloads, appearing in system prompts, templated retrieval-augmented generation pipel

Local Ai

QoS-Aware Federated Learning for Multimodal In-Cabin Interaction in Smart Vehicles

arXiv:2609.20123v1 Announce Type: new Abstract: Modern smart vehicles leverage multimodal sensors, ranging from high-bandwidth vision systems to low-rate physiological monitors, to provide personalize

local-aiarxiv-cs-lg

Applications

Randomized SVD Approximations for Spectral Co-Clustering of Word-Document Matrices

arXiv:2609.19243v1 Announce Type: cross Abstract: Spectral co-clustering is a useful tool for discovering latent structure in word-document matrices, but its reliance on singular value decomposition (

applicationsarxiv-cs-ai

Recursive Quantum Long Short-Term Memory for Stable Short-Horizon Temperature Forecasting

arXiv:2609.20594v1 Announce Type: new Abstract: Quantum long short-term memory (QLSTM) models extend recurrent sequence learning with variational quantum circuits, but their optimization behavior can

ResNLS: An Improved Model for Stock Price Forecasting

arXiv:2312.01020v3 Announce Type: replace Abstract: Stock prices forecasting has always been a challenging task. Although many research projects try to address the problem, few of them pay attention t

Robust Workflow Generation via Adversarial Learning for Audio Deepfake Detection

arXiv:2609.20063v1 Announce Type: cross Abstract: The rapid advancement of speech synthesis and voice conversion technologies has made audio deepfakes increasingly realistic, posing serious security r

RTK-Vision PPO for Autonomous Micro UAV Recovery on an Airborne Carrier

arXiv:2609.20629v1 Announce Type: new Abstract: Autonomous recovery of a micro unmanned aerial vehicle (UAV) onto a moving airborne carrier enables reusable deploy-mission-recover operation, but coupl

safetyarxiv-cs-ro

Score Centering Stabilizes Off-policy Reinforcement Learning

arXiv:2609.20807v1 Announce Type: new Abstract: Reinforcement learning (RL) of large language models is notoriously sensitive to small differences between training and inference engines, often referre

Self-excited actuation enables adaptive and resilient flapping-wing flight

arXiv:2609.19480v1 Announce Type: new Abstract: The muscles that power insect flight fall into one of two categories: 1) synchronous muscles that contract under direct control from the nervous system,

researcharxiv-cs-ro

Applications

Semantic Layer Induction from Raw Telemetry via Hierarchical LLM and RAG Abstraction

arXiv:2609.19615v1 Announce Type: cross Abstract: Modern applications generate massive volumes of raw telemetry data, but translating those noisy, heterogeneous event streams into actionable business

applicationsarxiv-cs-ai

SenseFuse: Label-Free Fusion of Image and Shape Encoders for Open-Vocabulary 3D Instance Segmentation

arXiv:2609.20475v1 Announce Type: new Abstract: Open-vocabulary scene understanding is fundamental for robotics, laying the groundwork for spatial reasoning and object manipulation. While closed-vocab

researcharxiv-cs-cv

SETTer: Sparse-Encoder Transformer for Long-term Multivariate Time Series Forecasting

arXiv:2609.20086v1 Announce Type: new Abstract: Long-term multivariate time series plays a significant role in many application areas such as power systems, trading, etc. However, their accurate predi

SoftTri: Smooth Triangular Membership Functions for Adaptive Fuzzy Inference Systems

arXiv:2609.20194v1 Announce Type: cross Abstract: Triangular membership functions (MFs) are widely used in fuzzy systems because of their interpretability, low parameterization complexity, and strong

Solving Minimum Span Antibandwidth and Cyclic Antibandwidth Labeling Problems

arXiv:2609.20091v1 Announce Type: new Abstract: The Antibandwidth and Cyclic Antibandwidth problems are NP-hard graph labeling problems that aim to maximize the minimum (cyclic) distance between label

Stable Policy Learning

arXiv:2609.19418v1 Announce Type: cross Abstract: In evidence-based policymaking, typically one experimental sample is observed, then a learned policy recommendation is implemented at scale. Policies

Applications

Steering the Compass: Aligning Dynamic Psychological Counseling Conversations with Cognitive Behavioral Therapy Strategies

arXiv:2609.20565v1 Announce Type: new Abstract: Recent advancements in large language models have revolutionized the field of psychological counseling, especially in the context of Cognitive Behaviora

applicationsarxiv-cs-cl

Sufficient Decision Proxies for Decision-Focused Learning

arXiv:2505.03953v3 Announce Type: replace Abstract: When solving optimization problems under uncertainty with contextual data, utilizing machine learning to predict the uncertain parameters' values is

Support Thresholds, Not Algorithms, Limit Rare-Association Recovery in Co-Purchase Networks

arXiv:2609.20171v1 Announce Type: new Abstract: The support threshold of the Apriori algorithm involves a trade-off in conducting market basket analysis: the associations that occur frequently are not

Hardware

Task-Oriented Active Learning of Residual Dynamics for Model Predictive Path Integral Control

arXiv:2609.19378v1 Announce Type: new Abstract: Online residual learning can reduce model mismatch in predictive control, but passive data collection may fail to adequately cover states that become im

hardwarearxiv-cs-ro

Task-Oriented Semantic Feature Transmission for Multi-Task Satellite Remote Sensing over Low-SNR Channels

arXiv:2609.20150v1 Announce Type: new Abstract: Conventional satellite remote sensing transmission follows a reconstruct-then-infer paradigm that optimizes pixel-level fidelity, creating an objective

researcharxiv-cs-cv

Tele-Traversability: Rethinking Traversability for Teleoperated Ground Robots in Terrain Navigation

arXiv:2609.19577v1 Announce Type: new Abstract: Teleoperation, a human-in-the-loop control scheme, allows a human operator to remotely command and guide a mobile robot to navigate in off-road environm

safetyarxiv-cs-ro

The Bias of Nonlinear Two-Time-scale Stochastic Approximation under Constant Step-Sizes

arXiv:2609.20409v1 Announce Type: new Abstract: Two-timescale stochastic approximation (TTSA) is a fundamental tool for analyzing coupled iterative algorithms in reinforcement learning, optimization,

Tutorials

Traffic Engineering in Large-scale Networks with Generalizable Graph Neural Networks

arXiv:2503.24203v3 Announce Type: replace-cross Abstract: Traffic Engineering (TE) in large-scale networks like cloud Wide Area Networks (WANs) and Low Earth Orbit (LEO) satellite constellations is a

tutorialsarxiv-cs-lg

Transformer fault diagnosis using an efficient simulation-driven variational quantum classifier with domain-aware feature encoding

arXiv:2609.20214v1 Announce Type: cross Abstract: Early transformer fault diagnosis is challenged by nonlinear dissolved-gas interactions, overlapping fault signatures, and limited labeled data, while

VAST: V2X/Dynamic Map-Aware Autonomous Driving Systems Validation Toolchain

arXiv:2609.19681v1 Announce Type: new Abstract: Cooperative autonomous driving in the IoT-to-Edge-to-Cloud continuum requires system-level validation across vehicles, infrastructure sensors, edge-side

agentsarxiv-cs-ro

What Do We Expect from LLMs? Mapping the Design of LLM Benchmarks

arXiv:2609.19182v1 Announce Type: new Abstract: Benchmarks are central to how progress in large language models (LLMs) is assessed and communicated. Yet model rankings alone reveal little about how ev

agentsarxiv-cs-ai

Workspace Models: Lightweight Robotic Memory via Saliency-Driven Supervision

arXiv:2609.20820v1 Announce Type: cross Abstract: Complex robotic manipulation tasks frequently require a long-term memory of past events and actions. As conditioning on full histories renders policie

Xeno-Interpretability: Investigating the Alien Minds of LLMs

arXiv:2609.20408v1 Announce Type: cross Abstract: Large language models are usually interpreted through concepts that humans already possess: truthfulness, refusal, deception, personality, harmfulness

A Geometric Theory of Decision Boundaries in Structured Markov Decision Processes

arXiv:2609.18610v1 Announce Type: new Abstract: Classical dynamic programming represents optimal sequential decisions through value functions and policies. While this functional representation is natu

A Heisenberg Lift Descriptor for Order Sensitive Online Handwriting Recognition

model-releasesarxiv-cs-cv

arXiv:2609.17565v1 Announce Type: new Abstract: Online handwriting recognition systems typically represent pen trajectories through fixed-length Euclidean shape descriptors that capture the spatial ou

A Scalable Framework for Automated NER Annotation Correction in Low-Resource Languages

arXiv:2609.18739v1 Announce Type: cross Abstract: Poor quality or noisy annotations in Named Entity Recognition (NER), as in any other NLP task, make it challenging to achieve state-of-the-art perform

researcharxiv-cs-ai

A Systematic Evaluation of the COTQ Provincial Land Cover Product: Structural Consistency, Spectral Separability, and Relative Positioning Against ESA, ESRI, and Google Products

arXiv:2609.17731v1 Announce Type: new Abstract: High-resolution land use and land cover (LULC) products derived from Sentinel-2 imagery are widely used for environmental monitoring and land management

researcharxiv-cs-ai

A Unified Hierarchical Framework for Fine-grained Cross-view Geo-localization over Large-scale Scenarios

model-releasesarxiv-cs-cv

arXiv:2505.07622v2 Announce Type: replace Abstract: Cross-view geo-localization is a promising solution for large-scale localization problems, requiring the sequential execution of retrieval and metri

A Zeroth-Order Paradigm for LLM Preference Alignment

arXiv:2609.19144v1 Announce Type: cross Abstract: Direct preference alignment methods are widely used to align large language models (LLMs) with human preferences because of their computational and me

Hardware

Accelerating Stateful Network Applications with Performance Prediction on SoC SmartNICs

arXiv:2410.22229v2 Announce Type: replace-cross Abstract: Offloading stateful network functions to multi-threaded SoC SmartNICs promises significant performance and cost benefits. However, realizing t

hardwarearxiv-cs-cl

Accuracy- and Real-Time-Aware 4D Radar Preprocessing for Autonomous Driving Perception Systems

arXiv:2609.18542v1 Announce Type: new Abstract: 4D radar has emerged as a promising next-generation sensor for improving the robustness of autonomous driving perception systems because of its stable s

agentsarxiv-cs-cv

Align, Integrate, and Fire: Efficient Token-Level Alignment for Zero-Shot SpeechLLMs

model-releasesarxiv-cs-cl

arXiv:2609.18516v1 Announce Type: new Abstract: While Large Language Models excel in natural language processing, efficiently extending their capabilities to spoken input remains a significant challen