Search: “evaluation”

Barycentric Anchored Weight Search for Robust Model Merging

arXiv:2610.14017v1 Announce Type: cross Abstract: We propose Barycentric Anchored Search, a post-hoc weight-space procedure for improving fine-tuned vision models under distribution shift without addi

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Benchmarking Deep Learning Models for Anomaly Detection in Real-World Cloud Telemetry

DGX agent

arXiv:2610.15818v1 Announce Type: new Abstract: Modern cloud platforms generate high-dimensional, noisy telemetry from thousands of microservices. Unlike classical anomaly detection benchmarks, cloud

model-releasesarxiv-cs-lg

14 Oct 2026

Benchmarking Multimodal Large Language Models for Zero-Shot Human-Object Interaction

arXiv:2610.18161v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated strong zero-shot reasoning across diverse domains, but their potential for Human-Object Inter

Benchmarks are becoming the core competency of any company. Our company mission is to build the world’s best models for document processing.…

model-releasesjerry-liu--x

Benchmarks are becoming the core competency of any company. Our company mission is to build the world’s best models for document processing. This also means that we have to build the world’s best benc

Beyond Single-Pathogen Forecasts: Predicting Shared Respiratory Hospital Burden from Influenza, COVID-19, and RSV

arXiv:2610.16074v1 Announce Type: cross Abstract: Co-circulating influenza, COVID-19, and respiratory syncytial virus (RSV) create a shared hospital-admission burden, because beds, staff, testing capa

Beyond the Encoder: Object-Centric Representations Emerging from Segmentation Foundation Models

arXiv:2610.18543v1 Announce Type: new Abstract: Foundation models are increasingly used as feature extractors for downstream tasks with limited data, typically through representations obtained from th

Bifocal: Training-Free Mixed Granularity Visual Token Pruning for Multimodal LLMs

arXiv:2610.18399v1 Announce Type: new Abstract: Visual token pruning for multimodal large language models (MLLMs) appears highly effective, with existing methods retaining over 95% of unpruned perform

Building Multilingual Datasets for Predicting Mental Health Severity through LLMs: Prospects and Challenges

arXiv:2409.17397v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly being integrated into various medical fields, including mental health support systems. However,

C{AE}NL: Collapse-Based Active Neural Learning with Objective-Aligned Representation Control

arXiv:2610.17509v1 Announce Type: cross Abstract: Active learning changes the representations used to acquire subsequent labels. We study this interaction through Collapse-Based Active Neural Learning

safetyarxiv-cs-cv

Can Synthetic UAV Benchmarks Be Trusted? Real-Synthetic Validation for UAV Model Selection

arXiv:2610.14647v1 Announce Type: new Abstract: Synthetic UAV imagery can expand pre-deployment test evidence when task-specific Real data are scarce, but visual plausibility or semantic label alignme

Carve VFM: Carving Specialists out of Generalists, Automatic Task-Specific Compression of Vision Foundation Models

arXiv:2610.16813v1 Announce Type: new Abstract: Vision foundation models (VFMs) provide transferable visual representations, but their inference cost limits deployment in many settings. Fine-tuning sp

CAST: Real-Time Motion Capture for Any Skeleton Topology

arXiv:2610.14856v1 Announce Type: new Abstract: This paper studies the problem of recovering motion from monocular video, even when the target skeleton topology differs from the subject observed in th

Chunk-wise Model-based Policy Optimization

arXiv:2610.14564v1 Announce Type: cross Abstract: Model-based reinforcement learning has shown superior sample efficiency by leveraging the learned latent dynamics either in the form of derivative-fre

safetyarxiv-cs-lg

Cite Pretrain: Retrieval-Free Knowledge Attribution for Large Language Models

arXiv:2506.17585v4 Announce Type: replace-cross Abstract: Large language models can answer questions correctly and still hallucinate their citations. Most citation systems address this by retrieving d

Clinical value claims in multimodal AI outpace supporting evidence

arXiv:2610.14395v1 Announce Type: new Abstract: Multimodal prediction models add a data source, such as imaging or an assay, to clinical information, and health systems must decide whether that added

Coarse-Graining Recursive Expert Computation: Continuation-Relative Interfaces and Failure Modes

arXiv:2610.14413v1 Announce Type: new Abstract: Computational coarse-graining aims to replace a sequence of updates with a cheaper module while preserving task performance. We present a continuation-r

Code-Interactive Visual Reasoning for Financial Candlestick Understanding

arXiv:2610.16587v1 Announce Type: new Abstract: Financial candlestick understanding requires locating visual elements, aligning them across trading dates and panels, and combining observations through

Tutorials

Coding LLMs Can Be Harnessed to Learn Interpretable Models from Data

arXiv:2610.14006v1 Announce Type: new Abstract: Since compact, interpretable classifiers correspond to simple programs, it is natural to ask if LLM-based coding agents can be used to learn interpretab

tutorialsarxiv-cs-lg

Local Ai

CryoTracer: A Synthetic-to-Real System for Filament Instance Tracing in Cryo-EM

arXiv:2610.18696v1 Announce Type: new Abstract: Particle picking in cryo-electron microscopy is commonly formulated as an object-detection problem in which individual particles are represented by boun

local-aiarxiv-cs-cv

Hardware

Denoise X: Self-Supervised U-Net for Quantum Mottle Suppression in Chest Radiography

arXiv:2610.18556v1 Announce Type: new Abstract: Deep learning for medical image restoration is often constrained by the need for paired training data. Acquiring perfectly registered clean-noisy radiog

hardwarearxiv-cs-cv

DiffNash: Finding Nash Equilibrium in High-Dimensional Continuous Action Spaces with Diffusion Policies

arXiv:2610.15932v1 Announce Type: new Abstract: Computing equilibria in high-dimensional continuous games requires learning and representing rich, multi-modal strategy distributions, something convent

safetyarxiv-cs-lg

Dissociating Answerability from Extraction in LLM Question Answering over Radiology Reports

arXiv:2610.17576v1 Announce Type: cross Abstract: Answering questions from radiology reports involves two decisions: whether the report contains an answer and which span gives it. A false answer prese

Does System One Transfer? Calibrated Typed-Decision Models, Label Budgets, and Translation for Indonesian Regional Languages

arXiv:2610.14112v1 Announce Type: cross Abstract: Calibrated typed-decision ('System One') models return a label and a probability in a single forward pass at a small fraction of the cost of large lan

Applications

DRanker: A Transformer-Based Multi-Task Ranking Model for the Disney+ Homepage

arXiv:2610.15696v1 Announce Type: new Abstract: We present DRanker (Disney+ Ranker), a transformer-based multitask ranking model serving personalized recommendations on the Disney+ homepage. We descri

applicationsarxiv-cs-lg

Efficient Resource-Shiftable RL Post-training with Generative Rewards

arXiv:2610.16866v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training with generative reward models (GenRM) has become a central recipe for improving large language models (LLMs),

Explainable Visual Anomaly Detection via Concept Bottleneck Models

arXiv:2511.20088v3 Announce Type: replace Abstract: In recent years, VAD (Visual Anomaly Detection) has attracted significant attention due to its high interpretability, as it provides visual explanat

Explicitly Aligned Multi-View Breast Cancer Risk Prediction from Variable-Length Screening Histories

arXiv:2610.16329v1 Announce Type: new Abstract: Accurate breast cancer risk prediction from screening mammography is essential for improved risk stratification and personalized screening. It can benef

Exploring the Underwater World Segmentation without Extra Training

arXiv:2511.07923v3 Announce Type: replace Abstract: Accurate segmentation of marine organisms is vital for biodiversity monitoring and ecological assessment, yet existing datasets and models remain la

ForkCast: Predictive Recovery for Vision-Language-Action Policies via Counterfactual Futures

model-releasesarxiv-cs-ro

arXiv:2610.18650v1 Announce Type: new Abstract: Vision-language-action (VLA) policies perform manipulation tasks using camera images and language instructions, but object slip or visual occlusion can

FoveaTree: Information-Density Trees for Query-Guided Visual Token Pruning in Video Large Language Models

arXiv:2610.16744v1 Announce Type: new Abstract: Video large language models (Video LLMs) encode each frame into hundreds of visual tokens, making video inference expensive. Existing methods reduce thi

Agents

FRACTION: Fraud Explanation Generation via Agentic Graph Context Navigation

arXiv:2610.18023v1 Announce Type: new Abstract: Graph fraud explanation generation emerges as an important task, which requires jointly leveraging graph structure and content information to produce hu

agentsarxiv-cs-lg

Frequency Routing and Identity Conditioning for Thermal-to-Visible Face Translation

arXiv:2610.17859v1 Announce Type: new Abstract: Thermal-to-visible (T2V) face translation has important applications in nighttime biometric recognition, low-light surveillance, and human interpretatio

Agents

From Acoustic Sensing to Physical Actions: A Comprehensive Survey of Security Risks in Edge-Deployed Audio LLM-Based Agents

arXiv:2610.15390v1 Announce Type: cross Abstract: Audio Large Language Models (Audio LLMs) are embedded in agents for smart homes, vehicles, wearables, and embodied systems, where acoustic inputs can

agentsarxiv-cs-cv

Tutorials

From Pixels to Executable Physics: Behavior-Grounded World Models for Embodied Action Consequence Prediction

arXiv:2610.17630v1 Announce Type: cross Abstract: In outdoor environments, varying terrain and contact conditions can cause identical action commands to produce different motion outcomes for quadruped

tutorialsarxiv-cs-cv

From Rainfall to Road-Network Functionality: Transferable Graph Forecasting for Flood-Disrupted Transportation Networks

arXiv:2610.14622v1 Announce Type: new Abstract: Extreme rainfall can rapidly degrade road-network functionality (RNF), disrupting emergency mobility, accessibility, evacuation, logistics, and infrastr

From Simulated Fluids to Living Tissue: Zero-Shot Foundation Model Transfer to Perturbed Embryos

arXiv:2610.16236v1 Announce Type: new Abstract: Morphogenesis is driven by the interplay of genetic regulation and tissue mechanics. In vivo video data is limited, particularly under genetic mutations

Game-Theoretic Reinforcement Learning based Topology-Agnostic Defense for Virtual Power Plants

arXiv:2610.15183v1 Announce Type: new Abstract: The rapid proliferation of distributed energy resources (DERs) aggregated by virtual power plants (VPPs) elevates cybersecurity risk by expanding the at

safetyarxiv-cs-lg

GeoBridge: Evolving Transferable Decoder Topologies for Geometric Vision

arXiv:2610.15280v1 Announce Type: new Abstract: Depth estimation and Gaussian reconstruction share a need for multi-scale feature processing, yet use different prediction interfaces and training objec

GREAT: A Graph Edge Attention Network for the Electric Vehicle Routing Problem with Asymmetric Costs

arXiv:2408.16717v4 Announce Type: replace Abstract: Due to the ongoing electrification of transportation systems, energy-based routing problems such as the Electric Vehicle Routing Problem (EVRP) are

Agents

Have You Seen It Clearly? Uncertainty-Guided Belief Refinement for Zero-Shot Object Navigation

arXiv:2610.15375v1 Announce Type: new Abstract: Zero-Shot Object Navigation (ZSON) requires an agent to locate target objects in unfamiliar environments without additional training for the test catego

agentsarxiv-cs-ro

HierarchiRetina: A Diabetic Retinopathy Screening and Grading Cascade with Heterogeneous Mixture-of-Experts Lesion Segmentation

arXiv:2610.17933v1 Announce Type: new Abstract: Clinical screening for diabetic retinopathy proceeds in stages, yet most automated systems grade fundus images with a single black-box network. Three ga

How to Build a Benchmark That Actually Measures Taste

arXiv:2610.14707v1 Announce Type: cross Abstract: Expert-aligned 'taste' benchmarks should reward craft judgment, not the ability to game the test. We introduce TasteBench, a pairwise good-vs-bad benc

HumanPhys: A Human-Centric Physical-World Perception Benchmark for Real-World Visual Reasoning

arXiv:2610.14679v1 Announce Type: new Abstract: We introduce HumanPhys, a human-centric benchmark for real-world physical perception, and a training corpus emitted by the same pipeline. Each question

Hybrid Context Forests and Bilateral Viterbi Matching for 3D Rib Centerline Tracing in CT

arXiv:2610.16047v1 Announce Type: cross Abstract: Automatic extraction and anatomical numbering (R01-R12, L01-L12) of all 24 rib centerlines in thoracic CT is essential for unfolded rib visualization,

Tutorials

In-Context Learning Can Help Vision-Language Models Overcome Training Priors

arXiv:2610.12942v2 Announce Type: replace Abstract: Vision-language models (VLMs) learn strong statistical regularities during training, which can make them fail to properly respond to visual evidence

tutorialsarxiv-cs-cv

InCLAD: A Continual Learning Benchmark for Industrial Visual Anomaly Detection

arXiv:2610.15032v1 Announce Type: new Abstract: Industrial anomaly detection benchmarks have advanced rapidly, yet they remain largely static and therefore underrepresent deployment settings in which

Interpretable Graph Partitioning for Spatial Prediction

arXiv:2610.16063v1 Announce Type: new Abstract: Spatial prediction estimates unobserved values from spatially distributed observations. Although flexible predictive models are increasingly available,

Interpretable Multimodal EEG-ECG Framework for Neonatal Seizure Prediction and Patient-Adaptive Transfer Learning

arXiv:2511.14110v2 Announce Type: replace-cross Abstract: Neonatal seizures carry substantial risks of acute brain injury and long-term neurodevelopmental impairment, motivating the need for timely id