Search: “evaluation”

arXiv:2610.07025v1 Announce Type: new Abstract: Multi-person 3D pose estimation with WiFi channel state information (CSI) is challenging because reflections from different people overlap without direc

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7 Oct 2026

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X-OPM: Explainable Automatic Digital On-Chip Power Modeling for Enhanced Robustness

DGX agent

arXiv:2610.08502v1 Announce Type: cross Abstract: Proactive power management systems reduce processor dynamic power through runtime power prediction and power-aware scheduling. Accurate, stable and lo

researcharxiv-cs-ai

7 Oct 2026

Agents

1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities

arXiv:2503.14858v5 Announce Type: replace Abstract: Scaling up self-supervised learning has driven breakthroughs in language and vision, yet comparable progress has remained elusive in reinforcement l

agentsarxiv-cs-lg

A Multimodal Sequence-to-Sequence Model for Cross-Subject Prediction of Brain Responses to Naturalistic Stimuli

arXiv:2507.18104v3 Announce Type: replace Abstract: Brain encoding models predict time-resolved neural activity from computational representations of ongoing experience, providing a principled framewo

A Response Theory Probe for Learned Stochastic AI Simulators, Tested on Lorenz-63

arXiv:2610.06798v1 Announce Type: cross Abstract: Machine-learning emulators of chaotic and stochastic systems are usually validated on forecast skill and long-run statistics. Neither certifies that a

A Safe Action Is Not Enough: Feasible-Future Decoding for Vision-Language-Action Policies

arXiv:2610.05166v1 Announce Type: cross Abstract: A safe action is not necessarily a viable one. Under a frozen vision-language-action (VLA) policy, an action can be likely and locally admissible yet

safetyarxiv-cs-ro

A State Based Dispatch Controller for Hospital Delivery Robots with Shared Human and Infrastructure Resources

model-releasesarxiv-cs-ro

arXiv:2610.05971v1 Announce Type: new Abstract: Robot delivery studies can overstate transport capacity when travel to pickups and human support fall outside the modeled schedule. We formulate a locat

A Three-Dimensional Reverse-Projection Method for Sparse Point Cloud Completion and Its Application to High-Speed Train Nose Reconstruction

arXiv:2610.05758v1 Announce Type: new Abstract: Holes in LiDAR scans of environments with glass windows remain an unresolved problem in three-dimensional reconstruction. This study presents a pipeline

A Unified Dynamics Framework for Reinforcement Learning and Classical Control of a Six-DOF Pipeline-Tracking ROV in NVIDIA Isaac Sim

arXiv:2610.04949v1 Announce Type: new Abstract: Reinforcement learning controllers for underwater vehicles are usually trained against one physics representation and deployed against another, so repor

safetyarxiv-cs-ro

Active-DiNTS: Active Differentiable Network Topology Search

arXiv:2610.04787v1 Announce Type: new Abstract: Neural Architecture Search (NAS) has proved to be a strong alternative to manual network design, but applying it to 3D medical image segmentation is lim

Adaptive Mean Flow for Responsive Closed-Loop Robot Control

model-releasesarxiv-cs-ro

arXiv:2610.06089v1 Announce Type: new Abstract: Diffusion- and flow-based robot policies have recently become widespread in robotic Imitation Learning (IL) due to their high performance and ability to

Tutorials

Adaptive Partitioning Schemes for Optimistic Optimization

arXiv:2610.04039v1 Announce Type: cross Abstract: Applications such as engineering design often require us to optimize a black-box function, i.e., a system whose inner processing is not analytically k

tutorialsarxiv-cs-lg

Adaptive-Shot Hybrid Quantum Anomaly Detection for Tactile Internet Security: Reliability-Aware Measurement Allocation Under Resource Constraints

arXiv:2610.05835v1 Announce Type: cross Abstract: Tactile Internet (TI) security analytics must balance reliable thresholded decisions with constrained computational and measurement resources. We stud

Advectra: Asymmetric Latent Transport for Non-Stationary Physics

arXiv:2610.05098v1 Announce Type: new Abstract: Many latent neural operators represent input and output fields in a stationary latent chart. In particular, common latent routing mechanisms use fixed o

applicationsarxiv-cs-lg

AFP-GIC: Controllable Generative Image Compression [R]

model-releasesr-machinelearning

Hi ML Community, I am excited to share our latest framework, AFP-GIC, officially published in IEEE Access (2026). We have released the deployment codebase and hosted an interactive visual playground.

AgenticTactileVLA: Contact-Guided Execution-Time Supervision for Generalizable Dexterous Manipulation without VLA Retraining

arXiv:2610.04391v1 Announce Type: new Abstract: Vision-language-action policies may predict a transferable manipulation strategy yet fail to realize it reliably on the encountered object: objects comp

researcharxiv-cs-ro

Aligning Multimodal Patient Evidence with Biomedical Knowledge Graphs for Clinical LLMs

arXiv:2610.06685v1 Announce Type: new Abstract: Clinical questions often depend on linking a patient's multimodal evidence to external biomedical knowledge, yet existing predictive systems rarely repr

safetyarxiv-cs-lg

Amortized Acquisition Optimization for Bayesian Optimization with Variational Mutual Information

arXiv:2601.08172v2 Announce Type: replace Abstract: Bayesian optimization (BO) of expensive black-box functions is traditionally addressed with Gaussian processes (GPs), which scale cubically with obs

applicationsarxiv-cs-lg

An LLM-in-the-loop RL Framework for Bioinformatics Feature Selection

arXiv:2610.05600v1 Announce Type: new Abstract: High-dimensional bioinformatics data, characterized by a large number of features relative to the number of samples, pose major challenges such as the `

safetyarxiv-cs-lg

Analysis of SWIR Imaging Detection Performance Under Adverse Environmental Conditions for Autonomous Driving Systems

arXiv:2610.06596v1 Announce Type: new Abstract: Short-wave infrared (SWIR) imaging has emerged as a promising modality for autonomous driving, yet its practical benefits over RGB remain poorly charact

Anatomy of LLM Sycophancy: What a Flip Rate Hides

arXiv:2610.06522v1 Announce Type: cross Abstract: A model under pushback can correct itself, capitulate, or hold, and one flip rate counts a correction and a capitulation alike. Using SycoLens, a modu

Anlu: Enabling In-Context Time Series Anomaly Detection in Foundation Models via Counterfactual Supervision

arXiv:2610.06180v1 Announce Type: new Abstract: Whether a time-series pattern is anomalous often depends on the operating regime of the monitored process. A missing event can signal a fault in one reg

Hardware

Answer Set Networks: Casting Answer Set Programming into Deep Learning

arXiv:2412.14814v2 Announce Type: replace-cross Abstract: Although Answer Set Programming (ASP) allows constraining neural-symbolic (NeSy) systems, its employment is hindered by the prohibitive costs

hardwarearxiv-cs-lg

ANT: A Multi-Granularity Network Traffic Dataset and Benchmark for Agents Behavior Auditing

arXiv:2610.06514v1 Announce Type: cross Abstract: The growing adoption of large language model (LLM) agents creates a need for network administrators and security teams to audit agent behavior within

Anticipating the Consequences of Curriculum Decisions with Large Language Models

arXiv:2610.04604v1 Announce Type: new Abstract: Automatic curriculum learning can improve the effectiveness of reinforcement learning by selecting the training experiences presented to the agent over

Aplomb 1: open-weights 5.3B decision model, 1M context, text/image/video/audio in one request, #1 among 4B models on the Decision Index

model-releasesr-localllama

We released Aplomb 1 today, a 5.3B decision model with open weights. It reads up to 1M tokens of text, JSON, images, video and audio in a single request, and on our API it makes a decision on a 1M-tok

ArticuTable: Generating Instance-Level Interactive Rigid-Articulated 3D Tabletop Scenes from a Single Image

arXiv:2610.05249v1 Announce Type: new Abstract: Embodied agents benefit from 3D environments that combine visual fidelity to real-world observations with physical interactivity. Existing single-image

applicationsarxiv-cs-cv

ASD-FEAT: A Multi-Modal Infant Video-Derived Dataset for Early ASD Risk Prediction

arXiv:2610.04051v1 Announce Type: new Abstract: Accurate early screening for Autism Spectrum Disorder (ASD) is a precursor to timely intervention, which is critical for improving cognitive and behavio

Agents

AUTOPILOT An Advanced Perception, Localization and Path Planning Techniques for Autonomous Vehicles Using YOLOv7 and MiDaS

arXiv:2610.06232v1 Announce Type: cross Abstract: Self driving vehicles have emerged as a reliable technology that has the capability to transform transportation and mobility. The development of self

agentsarxiv-cs-lg

Tutorials

Backward-Consistent Diffusion Sampling for Sparsely Observed PDE Inverse Problems

arXiv:2610.04624v1 Announce Type: new Abstract: Recovering Partial Differential Equation (PDE) coefficient fields from extremely sparse observations is a severely ill-posed inverse problem for which g

tutorialsarxiv-cs-lg

Barrier-Shaped Recurrent Reinforcement Learning for Autonomous Landing on a Heaving Ship Deck

arXiv:2610.03924v1 Announce Type: cross Abstract: This paper addresses autonomous landing of unmanned aerial vehicle (UAV) rotorcrafts on a heaving ship deck using a recurrent policy trained via asymm

safetyarxiv-cs-ro

Bayes-Sufficient Compression Is Not Enough: How Does Communication Help Multi-Agent Systems?

arXiv:2610.03769v1 Announce Type: new Abstract: Multi-agent LLM systems pair a sender with broad context and an executor with a limited local view. We study when a short message improves the executor'

[Benchmark] Running Local LLMs on Orange Pi 5 Plus (RK3588, 16GB): Ollama Tok/s, NPU Offloading, Core Pinning & Thermals

model-releasesr-localllama

Disclosure: This unit was provided free of charge by Orange Pi for testing. No editorial review, no preconditions, no script. All data, bottlenecks, and thermal behavior are reported directly from har

Beyond Token Accuracy: Prioritizing What Matters for Visual Reconstruction

arXiv:2610.03822v1 Announce Type: new Abstract: Tokens have become a unified interface for multimodal foundation models, making visual-token communication a natural paradigm for efficient image delive

safetyarxiv-cs-cv

Beyond Transport Cost: Routing Differences between Flow Matching and Optimal Transport

arXiv:2610.05921v1 Announce Type: cross Abstract: In generative models, Optimal Transport (OT) is used to improve Flow Matching (FM) by reducing noise-data coupling cost. However, different noise-to-o

BossouChimpanzee: Long-term Chimpanzee Video Dataset

arXiv:2610.05293v1 Announce Type: new Abstract: We describe the BossouChimpanzee video dataset, a unique long-term visual record of wild chimpanzees at an outdoor laboratory for field experiments in B

BRANCH-MoE: Balance-Aware Tree Routing for Large Embedding Models

arXiv:2610.06725v1 Announce Type: new Abstract: Mixture-of-experts (MoE) layers increase model capacity without a proportional increase in per-example computation. However, conventional flat routers c

Bridging the EHR Divide: Asymmetric Contrastive Learning for Cross-National Medical Representation Transfer

arXiv:2610.04946v1 Announce Type: new Abstract: Cross-system transfer of longitudinal Electronic Health Record (EHR) representations is challenging because clinical coding, patient populations, and he

applicationsarxiv-cs-lg

Calibrated Weak Supervision for Post-Harvest Burned-Cropland Mapping Under Label Scarcity

arXiv:2610.05040v1 Announce Type: new Abstract: Mapping post-harvest burned cropland is difficult when fires are small and fragmented and reliable labels are scarce. We developed a calibrated weak-sup

Causally Fair Generation with Large Language Models

arXiv:2610.04444v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate, complete, and transform information in settings where their outputs can shape conseque

safetyarxiv-cs-lg

CentriQ: Calibration-Free Quantization of Diffusion Transformers via Exact Mean Centering

arXiv:2610.06260v1 Announce Type: new Abstract: Diffusion transformers (DiTs) achieve state-of-the-art image generation, but their sampling cost limits deployment. Quantizing both weights and activati

Hardware

Characterizing Parallelism Strategies in LLM Inference: Fundamental Compute-Communication Trade-offs

arXiv:2610.05305v1 Announce Type: cross Abstract: Large Language Model (LLM) inference has become the dominant workload in modern AI systems, requiring serving infrastructures to maximize throughput w

hardwarearxiv-cs-lg

CIPHER-MoE: Balancing Efficiency and Routing Fidelity in Trillion-Scale MoE Training

arXiv:2610.05744v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) has been widely adopted in recent large language model (LLM) architectures. However, scaling up MoE in LLM training introduces

ClasSAE: Class-Aligned Sparse Autoencoders via Differentiable Feature-Class Affinity

arXiv:2610.04020v1 Announce Type: new Abstract: Sparse Autoencoders (SAEs) began as an unsupervised tool for decomposing neural representations into sparse, interpretable features, and are increasingl

safetyarxiv-cs-cv

CLIFT: Conformal Self-Verification for Web Agent Training and Test-Time Scaling

arXiv:2610.06829v1 Announce Type: cross Abstract: Open-source web agents are now strong enough to execute realistic browser tasks, but training them with reinforcement learning still depends on weak s

Closing the Context Gap: Activation Alignment for Tabular In-Context Learning

arXiv:2610.06679v1 Announce Type: new Abstract: Tabular foundation models perform in-context learning (ICL) by conditioning predictions on labeled training examples provided as context. Unlike traditi

Co-Optimizing Graph Sparsification and Approximate Computing for Energy-Efficient FPGA-Based GCN Inference

arXiv:2610.06138v1 Announce Type: new Abstract: Graph Convolutional Networks (GCNs) have emerged as a powerful framework for learning from graph-structured data, yet their deployment on resource-const

CoHyFuse: Condition-wise Hypergraph Fusion with Global Connectome in Task-fMRI

arXiv:2610.05913v1 Announce Type: new Abstract: Task-fMRI connectomes reveal state-dependent neural reconfigurations, yet conventional methods marginalize these signals by aggregating distinct conditi