Search: “evaluation”

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

researcharxiv-cs-cv

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

DGX agent

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,

model-releasesarxiv-cs-lg

14 Oct 2026

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

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

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

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

researcharxiv-cs-cv

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

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

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

researcharxiv-cs-cv

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,

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

JtT: Rethinking Point Trajectory Diffusion for Diverse and Rigid Motion from an Image

arXiv:2610.16591v1 Announce Type: new Abstract: We study forecasting rigid-body motion from a single image: generating diverse and physically plausible future trajectories for arbitrary points in a sc

tutorialsarxiv-cs-cv

KedgeFlow: A Programmable Control Plane for Enterprise AI Agents

arXiv:2610.14810v1 Announce Type: cross Abstract: Enterprise AI agents can execute altered versions of approved actions, concurrently reuse the same permission, or retry operations whose responses wer

Let the Mind Conceive, Let the Hand Achieve: Following Multimodal Instructions for Long-Horizon Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2610.18352v1 Announce Type: new Abstract: A robot following a multi-step instruction needs to act on the right objects in the right order, even as the scene changes. It must also maintain awaren

Longitudinal Learner Participation Profiling in Online Learning: Heterogeneous Consensus Clustering under Unequal Observation Windows

arXiv:2610.17494v1 Announce Type: new Abstract: Learning management system traces are clustered to identify participation profiles, but unequal observation windows may cause profiles to reflect durati

tutorialsarxiv-cs-lg

Mean Accuracy Is the Wrong Estimand for a Release Decision

arXiv:2610.16825v1 Announce Type: new Abstract: A release decision about a fine-tuned model is an operational commitment about the next rerun of its training recipe. Yet standard benchmark reporting g

Local Ai

MIST: Multi-Scale Spatial Context for Gene Expression Prediction from Histology

arXiv:2610.18769v1 Announce Type: new Abstract: Predicting spatial gene expression from standard H&E images could extend molecular analysis to tissues without spatial transcriptomic measurements. A st

local-aiarxiv-cs-cv