Search: “evaluation”

Triply-Scalable Equivariant Gaussian Process Modeling

arXiv:2609.21085v1 Announce Type: cross Abstract: Gaussian processes (GPs) provide principled probabilistic predictions while encoding prior knowledge, including equivariances. Yet, their use in large

researcharxiv-cs-lg

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ULTRA: Unified Multimodal Control for Autonomous Humanoid Whole-Body Loco-Manipulation

DGX agent

arXiv:2603.03279v2 Announce Type: replace-cross Abstract: Achieving autonomous and versatile whole-body loco-manipulation remains a central barrier to making humanoids practically useful. Yet existing

safetyarxiv-cs-cv

21 Sept 2026

Uncertainty-driven training for three-dimensional calibrated lung nodule classification

arXiv:2609.20905v1 Announce Type: cross Abstract: In this work, we present an uncertainty-driven training framework for three-dimensional computed tomography (CT) lung nodule classification, where val

Understanding LLM Quantization through Activation-Guided Compensation and Orthogonal Residuals

model-releasesarxiv-cs-lg

arXiv:2609.21450v1 Announce Type: new Abstract: Post-training weight-activation quantization reduces the memory and inference costs of large language models, but aggressive W4A4 quantization remains d

Uni-PrevPredMap: Extending PrevPredMap to a Unified Framework of Prior-Informed Modeling for Online Vectorized HD Map Construction

arXiv:2504.06647v4 Announce Type: replace Abstract: Safety-critical autonomous driving motivates the effective use of prior information. For online vectorized HD map construction, temporal predictions

safetyarxiv-cs-cv

Visual Proactivity: Enhancing Human-Robot Collaboration Through Intent Communication

arXiv:2609.21729v1 Announce Type: new Abstract: As robots transition from performing repetitive tasks to collaborating with humans, understanding human intent becomes crucial to effective interaction.

safetyarxiv-cs-ro

When Online Adaptation Hurts: Parameter-Frozen Test-Time Ensembling for Continual Medical Image Segmentation

arXiv:2609.21412v1 Announce Type: new Abstract: Medical image segmenters often get worse when sites, scanner vendors, or protocols change. Continual test-time adaptation (CTTA) addresses this problem

Tutorials

When Should Robots Intervene? Balancing Engagement and Intrusiveness in Human-Robot Interaction

arXiv:2609.21734v1 Announce Type: new Abstract: Designing effective Human-Robot Interaction in task-oriented settings requires carefully balancing user engagement with socially acceptable levels of ro

tutorialsarxiv-cs-ro

When Steering Fails in Latent Reasoning: A Latent-to-Language Transition Gap

arXiv:2609.21662v1 Announce Type: cross Abstract: Activation steering has become a widely used approach for controlling language models during explicit chain-of-thought (CoT) reasoning, motivating its

XCalib Depth-Guided Geometric Optimization for Dense Thermal-Visible Video Registration

arXiv:2609.21770v1 Announce Type: new Abstract: Image registration is a vital preprocessing step in multimodal perception tasks, including image fusion, object detection, and semantic segmentation. In

safetyarxiv-cs-cv

ZYT-World: A Real-Time Controllable World Model for Closed-Loop Autonomous-Driving Simulation

arXiv:2609.21712v1 Announce Type: new Abstract: Generative world models offer controllable and repeatable closed-loop simulation for end-to-end and vision-language-action driving policies, but product

4D Radar Perception Algorithms for Autonomous Driving: A Review

arXiv:2609.19216v1 Announce Type: cross Abstract: Research on 4D millimeter-wave radar perception algorithms has flourished in recent years, extending from signal processing and object detection to se

agentsarxiv-cs-cv

A Free Lunch? Adapting PP-OCRv6 for Historical Text Recognition

arXiv:2609.20064v1 Announce Type: new Abstract: Despite impressive reported scores, large vision-language models have seen limited practical uptake in historical automatic text recognition because of

researcharxiv-cs-cv

A frontend-backend architecture for tool calls in full-duplex speech models

arXiv:2609.19334v1 Announce Type: new Abstract: Full-duplex speech-to-speech (S2S) models provide natural, low-latency conversational interaction and would benefit from the ability to use external too

agentsarxiv-cs-cl

A Hybrid Gaze-Motor Imagery BCI Framework for Effective Decision Communication

arXiv:2609.20273v1 Announce Type: cross Abstract: Non-invasive brain-computer interfaces (BCIs) and eye-tracking technologies offer promising communication pathways; however, motor imagery (MI)-based

applicationsarxiv-cs-ai

A Multi-Modal Generative Model for Tomato Disease Leaves Understanding

arXiv:2609.19555v1 Announce Type: cross Abstract: Artificial intelligence for plant disease analysis has advanced from task-specific classifiers to multi-modal models capable of jointly interpreting v

A Multi-Objective Optimisation Framework for Corticomuscular EEG-EMG Pair Selection in Hybrid BCI

arXiv:2609.20275v1 Announce Type: cross Abstract: Hybrid brain-computer interface (BCI) systems that integrate electroencephalography (EEG) and electromyography (EMG) signals have shown significant po

A Network Science Approach to Granular Time Series Segmentation

model-releasesarxiv-cs-lg

arXiv:2505.17640v3 Announce Type: replace Abstract: Time series segmentation assigns a label to each part of a sequence. We formulate dense univariate segmentation as node classification on a graph wh

A Scalable Trust Discovery Architecture for the Internet of Agents

arXiv:2609.20095v1 Announce Type: cross Abstract: The Internet of Agents is expected to enable large numbers of autonomous agents to discover, verify, and collaborate with each other across heterogene

agentsarxiv-cs-ai

Hardware

Accelerating Sharded Data Parallelism at Scale with Federated Learning

arXiv:2609.20359v1 Announce Type: cross Abstract: The symbiotic scaling of artificial intelligence models and high-performance computing systems continually creates algorithmic challenges in their con

hardwarearxiv-cs-ai

Accuracy Is Not Enough: A Cross-Architecture Audit of Demographic Bias in Deep Knowledge Tracing

arXiv:2609.20249v1 Announce Type: new Abstract: Deep knowledge tracing (DKT) models implicitly decide which students an adaptive system believes have mastered a skill, yet almost all evidence on their

safetyarxiv-cs-lg

AdaRepair-Mem: Adaptive Experience Orchestration for Repository-Level Program Repair

arXiv:2609.20130v1 Announce Type: cross Abstract: Recent memory-augmented repository-level program repair methods reuse historical repair experiences to improve LLM-based issue resolution. However, ou

AI or Real: Detecting Partially Altered Videos Under Resource-Constrained Environments

arXiv:2609.20263v1 Announce Type: new Abstract: The proliferation of generative video models has shifted the practical detection threat from fully fabricated clips to partially manipulated footages. A

researcharxiv-cs-cv

AI Should Facilitate Democratic Deliberation at Scale

arXiv:2609.20059v1 Announce Type: cross Abstract: AI systems can strengthen democracy by supporting deliberation at scale by addressing cognitive, social, platform-design, and market-driven frictions,

safetyarxiv-cs-ai

AI Smart Glasses for Wearable Intelligence: From Egocentric Sensing to Agentic Personalization

arXiv:2609.19793v1 Announce Type: new Abstract: Recent advances in artificial intelligence (AI) are reshaping smart glasses from egocentric capture and display devices into platforms for wearable inte

agentsarxiv-cs-cv

AnyViewDex: View-Invariant Dexterous Manipulation from RGB Observations

arXiv:2609.20107v1 Announce Type: new Abstract: Visuomotor policies for multi-fingered dexterous manipulation are highly sensitive to camera viewpoint shifts. To achieve view invariance, recent method

safetyarxiv-cs-ro

AURA: Adaptive Uncertainty-Routed Analysis for Email Threat Detection

arXiv:2609.19873v1 Announce Type: new Abstract: Email spam and phishing attacks remain a critical security threat. Adversaries increasingly exploit large language models to craft contextually convinci

applicationsarxiv-cs-lg

Local Ai

Automated Goldsmith's Mark Retrieval in Silverware

arXiv:2609.20509v1 Announce Type: new Abstract: For art historians, goldsmith marks play a critical role in the identification and dating of artifacts. In practice, experts must manually compare a que

local-aiarxiv-cs-cv

Automated Gradient-Driven Parameter Sharing for Low-Resource Multilingual Speech-to-Text Translation

model-releasesarxiv-cs-cl

arXiv:2603.25836v2 Announce Type: replace Abstract: In low-resource multilingual speech-to-text translation, uniform architectural sharing across languages frequently introduces representation conflic

Tutorials

Bayesian Optimization with Rich Auxiliary Information via LLMs

arXiv:2609.19437v1 Announce Type: new Abstract: Bayesian Optimization (BO) is widely used for optimizing expensive black-box functions, yet many real-world optimization problems contain substantially

tutorialsarxiv-cs-lg

Before the Warning Comes Too Late: Incremental Phone-Scam Detection from Speech

model-releasesarxiv-cs-cl

arXiv:2609.20223v1 Announce Type: new Abstract: We study weakly supervised incremental telecom fraud detection from raw telephone audio, where training provides only conversation-level labels and pred

BuildBench: Benchmarking LLM Agents on Compiling Real-World Open-Source Software

model-releasesarxiv-cs-ai

arXiv:2509.25248v2 Announce Type: replace-cross Abstract: Automatically compiling open-source software (OSS) projects is a vital, labor-intensive, and complex task, which makes it a good challenge for

BurnRiSc: Toward Non-Invasive Burnout Screening in Open Source from Public Repository Signals

arXiv:2609.19422v1 Announce Type: cross Abstract: Burnout is a chronic occupational syndrome, and open source is close to a worst case for it: maintainers absorb unbounded demand with no manager to re

researcharxiv-cs-cl

Local Ai

Can Data Attribution Filter Out Subliminal Learning? Not Reliably

arXiv:2609.20027v1 Announce Type: new Abstract: Subliminal learning allows language models to transmit behavioral traits through training data with no obvious semantic relationship to those traits, un

local-aiarxiv-cs-ai

ClashBench: Conflicts Leading Agents to Seize and Harm

model-releasesarxiv-cs-ai

arXiv:2609.19892v1 Announce Type: cross Abstract: As agent systems become more widely used, multiple agent sessions increasingly run alongside pre-existing user tasks in the same environment, sharing

CleanVideo: Adaptive Concept Erasure for Text-to-Video Diffusion Models

arXiv:2609.20267v1 Announce Type: cross Abstract: Concept erasure aims to selectively eliminate undesired visual semantics from pre-trained generative models without compromising their general utility

Code-as-Auditor: Executable Compliance Reasoning via Regulation-to-Code

arXiv:2609.19199v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly adopted for compliance and legal reasoning tasks, yet their outputs often lack explicit grounding in leg

applicationsarxiv-cs-ai

Coding Agents with an Obstacle-Aware Harness for Safe Robot Manipulation

arXiv:2609.20822v1 Announce Type: cross Abstract: Coding agents have emerged as a promising paradigm for robot manipulation: a language model writes the robot controller as a program, and agents built

safetyarxiv-cs-ai

Communication and Verification in LLM Agents towards Collaboration under Information Asymmetry

arXiv:2510.25595v2 Announce Type: replace-cross Abstract: While Large Language Model (LLM) agents are often approached from the angle of action planning/generation to accomplish a goal (e.g., given by

Compact Vision Models for Iris Presentation Attack Detection under Presentation Attack Instrument Shift and Environmental Degradation

arXiv:2609.20386v1 Announce Type: new Abstract: Iris presentation attack detection (PAD) is security-critical when a subsystem that appears reliable during development encounters presentation attack i

Compass-v3: Scaling Domain-Specific LLMs for Multilingual E-Commerce in Southeast Asia

model-releasesarxiv-cs-cl

arXiv:2509.09121v2 Announce Type: replace Abstract: Large language models (LLMs) excel in general-domain applications, yet their performance often degrades in specialized tasks requiring domain-specif

Compositional Reasoning in Language Models under Reinforcement Learning Post-Training

arXiv:2609.19465v1 Announce Type: new Abstract: Compositional reasoning is critical for real-world problem solving: since training data is necessarily limited, models must generalize by composing lear

applicationsarxiv-cs-ai

Constraint-Safe Graph-Context Scoring for Stable Point-Feature Labels Under Text-Width and Accessibility-Inspired Profiles

arXiv:2609.19848v1 Announce Type: new Abstract: Point-feature label placement on interactive maps must reconcile geometric validity, display yield, local placement utility, and stability across camera

CORAL-AUV: CFD Oriented Reinforcement Learning for Autonomous Underwater Vehicles

arXiv:2607.09557v2 Announce Type: replace Abstract: Fine grain control and positioning of autonomous underwater vehicles (AUVs) is critical for sampling, maintenance, and survey applications. Traditio

safetyarxiv-cs-ro

CoreSense: Traceable Failure Recall and Conflict-Aware Belief Gating for Auditable Robot Decisions

arXiv:2609.19512v1 Announce Type: cross Abstract: Robots can recall prior failures without knowing whether recalled evidence remains valid, conflicts with current observations, or is sufficient to gui

safetyarxiv-cs-ai

Cross-Architecture Foundation-Model Distillation for Edge Flood Segmentation

arXiv:2609.20441v1 Announce Type: new Abstract: Geospatial foundation models can provide strong flood-segmentation performance, but their size limits deployment on memory-constrained edge hardware. We

Cross-Sectional Asset Retrieval via Future-Aligned Soft Contrastive Learning

arXiv:2602.10711v2 Announce Type: replace-cross Abstract: Asset retrieval (finding similar assets in a financial universe) is central to quantitative investment decision-making. Existing approaches de

CrystalMO-TuRBO: Multi-Objective Trust-Region Bayesian Optimization for High-precision Joint Crystal Structure Refinement

model-releasesarxiv-cs-lg

arXiv:2609.20592v1 Announce Type: new Abstract: Crystal structure refinement is a fundamental inverse problem in materials characterization, where structural parameters are optimized to reproduce expe