Search: “evaluation”

Domain-adaptive Zero-Shot Image Enhancement via Locality-Constrained Diffusion Guidance

arXiv:2609.35289v1 Announce Type: new Abstract: Denoising Diffusion Probabilistic Models have shown remarkable performance in unconditional image generation. In order to generate images with desired s

local-aiarxiv-cs-cv

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Research

Don't stop me now: How Validation Criteria Affect Checkpoint Selection and Early Stopping

DGX agent

arXiv:2602.22107v2 Announce Type: replace Abstract: Checkpoint selection is a standard component of neural network training, yet the validation criterion used to select a checkpoint is often chosen he

researcharxiv-cs-lg

29 Sept 2026

DORA: Dynamic Online Reinforcement Agent for Token Pruning in Vision Transformers

arXiv:2609.34325v1 Announce Type: new Abstract: Vision Transformers (ViTs) incur quadratic self-attention cost in the number of tokens. Most token-reduction methods adapt token identities within a pre

Agents

Dr. MAS: Stable Reinforcement Learning for Multi-Agent LLM Systems

arXiv:2602.08847v2 Announce Type: replace Abstract: Multi-agent LLM systems enable advanced reasoning and tool use via role specialization, yet reliable reinforcement learning (RL) post-training for s

agentsarxiv-cs-lg

DR-net-Mamba: Selective State-Space Modeling for Long-Range ECG Time-Series Denoising

arXiv:2609.35634v1 Announce Type: new Abstract: Electrocardiogram (ECG) recordings are corrupted by non-stationary noise sources that degrade diagnostic reliability, particularly in ambulatory and lon

local-aiarxiv-cs-lg

DRIFT: Data Selection for LLM Instruction Tuning via On-Policy Attribution

arXiv:2606.18307v2 Announce Type: replace Abstract: Data selection for instruction tuning is usually studied for efficiency, reaching strong performance with a fraction of the training data. We ask wh

Dynamic Manipulation with World-Action Models via Counterfactual Planning

arXiv:2609.33172v1 Announce Type: cross Abstract: World-Action models (WAMs) trained on static demonstrations often fail to manipulate moving targets even when they possess the required manipulation s

DynaTokens: Teaching Dynamics to Camera-Controlled Video Models at Test Time

arXiv:2609.35704v1 Announce Type: new Abstract: Video generation must account for two sources of motion, one induced by the observer's camera path and the other caused by scene dynamics. An ideal came

local-aiarxiv-cs-cv

E-WAVE: Event-based Continuous Optical Flow via Warping-Aligned Visual Encoding

arXiv:2609.34346v1 Announce Type: new Abstract: Temporally dense optical flow is essential for dynamic perception in immersive VR/AR systems, where rapid head, hand, and object motion must be continuo

applicationsarxiv-cs-cv

ECHO: Event-Augmented Context with Hindsight and Outlook for Wrist-Only Manipulation

arXiv:2609.34893v1 Announce Type: new Abstract: Learning-based manipulation policies relying on RGB cameras often suffer from degraded observations under extreme exposure. Event cameras mitigate this

Edge-Level Automorphism in GNNs: A Quantitative Framework and Effective Designs For Link Prediction

arXiv:2609.34729v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) are effective for learning node and link embeddings through permutation-equivariant aggregation. However, standard GNNs col

EdgeVLN: Runtime-Aware Deployment Ready Quantized Vision Language Navigation Model

arXiv:2609.35570v1 Announce Type: cross Abstract: Vision-language navigation (VLN) models perform well but target compute-rich platforms, limiting deployment on memory- and power-constrained robotic e

Editable Map-Conditioned Trajectory Generation for Human Mobility Simulation

arXiv:2609.32360v1 Announce Type: new Abstract: Geospatial simulation of infrastructure interventions requires mobility generators that respond directly to edited maps, yet many data-driven generators

EEG-Fusion: Failure-Informed Source-Free Expert Routing for Robust Motor Imagery EEG Decoding

arXiv:2609.33962v1 Announce Type: cross Abstract: Subject-independent motor-imagery (MI) EEG decoding can exhibit subject-level failures even when average performance appears acceptable: under subject

Efficient Bezier Velocity Optimization for Free-Floating Space Manipulators

arXiv:2609.31880v1 Announce Type: new Abstract: We present FAVOR (Free-floating Arm Velocity Optimization with Recursive Sensitivities), a planner for collision-free reaching, tracking, and prescribed

researcharxiv-cs-ro

Efficient Message Passing for Partial Differential Equation Priors

arXiv:2609.32956v1 Announce Type: new Abstract: Prior information for real-world physical quantities is most elegantly expressed via partial differential equations (PDEs). In this paper, we propose a

Hardware

Efficient World Action Model Inference with Adaptive Intermediate States

arXiv:2609.34608v1 Announce Type: new Abstract: World Action Models (WAMs) enable future-aware control by jointly modeling actions and environment dynamics. However, iterative diffusion or flow infere

hardwarearxiv-cs-ro

EffiPair: Improving the Efficiency of LLM-generated Code with Differential Execution Feedback

arXiv:2604.05137v2 Announce Type: replace-cross Abstract: Large language models (LLMs) can generate functionally correct programs that differ substantially in execution efficiency. Existing inference-

EgoTSR++: Egocentric Spatiotemporal Reasoning for Task Progress Understanding

arXiv:2609.31751v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have advanced rapidly in static visual understanding, yet remain unreliable when judging how an egocentric task is progres

Electric Potential Patterns Forecasting in the Southern Hemisphere with Deep Learning Techniques

arXiv:2609.31804v1 Announce Type: cross Abstract: Space weather disturbances driven by the solar wind can degrade satellite navigation, disrupt radio communications, and threaten power infrastructure,

applicationsarxiv-cs-cv

Endo-TSR: Temporal Spectral Modeling of Appearance and Motion for Endoscopic Reconstruction

arXiv:2609.32399v1 Announce Type: new Abstract: Endoscopic scene reconstruction requires modeling tissue motion and temporal appearance while recovering fine surface detail. Deformable Gaussian models

Energy Vision--Language--Action: A Controlled Multimodal Benchmark for Intent-Conditioned Residential Energy Management

arXiv:2609.31648v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are studied mainly in robotics, where visual observations and language instructions are mapped to physical actions.

Enhancing Foundation Models for Imbalanced SAR Ship Classification via Targeted Oversampling

arXiv:2609.31657v1 Announce Type: new Abstract: Remote-sensing foundation models offer strong representations for SAR imagery, but their behavior under severe long-tail class imbalance is still not we

Enhancing Visual Reasoning in Chest X-Ray Report Generation Using Reinforcement Learning

arXiv:2609.31911v1 Announce Type: new Abstract: Medical report generation has made significant progress with the rise of modern vision-language models and the growing availability of large-scale medic

Environment-Conditioned Tail Reweighting for Invariant Learning under Mixed Shifts

arXiv:2601.22944v3 Announce Type: replace Abstract: Out-of-distribution generalization becomes challenging when spurious correlations vary across environments while difficult or underrepresented sampl

applicationsarxiv-cs-lg

Epistemic Learning from Imprecise Annotation

arXiv:2609.34285v1 Announce Type: new Abstract: Imprecise annotations may support several plausible labelling distributions, yet learning methods often resolve this ambiguity into a single predictive

Evasion Attacks on Cost-Utility-Based Adversarial Training for Online AutoML in IoT Networks

arXiv:2609.31981v1 Announce Type: cross Abstract: As Internet of Things (IoT) networks increasingly depend on machine learning for anomaly, malware, intrusion detection, and network monitoring, such s

EvE: An Alternate Optimizer to Adam

arXiv:2609.35614v1 Announce Type: new Abstract: Adam and its variants dominate neural network training, but a single run only reveals whether a configuration works well after most of its budget is spe

EviSplat: Preserving Multi-View Evidence in 3D Gaussian Splatting for Open-Vocabulary Segmentation

arXiv:2609.34853v1 Announce Type: new Abstract: Open-vocabulary 3D scene understanding enables object localization and segmentation from free-form text queries without a fixed category vocabulary. Man

ExpertoRhythm: Morphology-Aware Learning for Waveform Reconstruction and Cuffless Blood Pressure Estimation from Single-Channel PPG

arXiv:2609.34146v1 Announce Type: new Abstract: Continuous cuffless blood pressure (BP) monitoring from photoplethysmography (PPG) has strong potential for wearable health and telemonitoring, but accu

F4R: Failure-Driven Recognition, Reconstruction, Refinement, and Redeployment for Continual Robot Self-Improvement

arXiv:2609.35575v1 Announce Type: new Abstract: The real-world performance of current vision-language-action models is fundamentally constrained by the limited coverage of expert demonstrations and th

safetyarxiv-cs-ro

Hardware

Facial classification Using Hybrid Quantum Machine Learning

arXiv:2609.31915v1 Announce Type: new Abstract: Hybrid quantum methods have received limited study for resource-constrained facial biometrics. We present a hybrid quantum-classical facial recognition

hardwarearxiv-cs-cv

Fading Expert Guidance: Bridging Model-Based and Learning-Based Control for Abortable Autonomous Overtaking

arXiv:2308.09456v2 Announce Type: replace Abstract: Overtaking on two-lane roads is a safety-critical decision-making problem for autonomous vehicles, since oncoming traffic may force the ego vehicle

safetyarxiv-cs-ro

FailPatch: Failure Residual Patching for Vision-Language-Action Models

arXiv:2609.34175v1 Announce Type: new Abstract: Vision-Language-Action (VLA) policies are typically adapted using successful demonstrations, which provide direct action supervision but rarely cover fa

safetyarxiv-cs-ro

Feature Space Guidance for Breast Cancer Classification in DCE-MRI

arXiv:2609.32555v1 Announce Type: new Abstract: Dynamic contrast enhanced breast MRI (DCE-MRI) is a powerful clinical tool for breast cancer detection, providing high resolution anatomical detail toge

Federated 3D Gaussian Splatting for Large-Scale Scene Reconstruction at Wireless Edge

arXiv:2609.32177v1 Announce Type: new Abstract: Three-dimensional (3D) Gaussian splatting (3D-GS) has emerged as a promising technique for large-scale scene reconstruction due to its high rendering ef

local-aiarxiv-cs-cv

Federated Subspace Guided Vision-Language-Action Policy Distillation for Non-IID Multi-Robot Manipulation

arXiv:2609.32239v1 Announce Type: cross Abstract: Federated learning offers a natural way for multiple robots to jointly improve manipulation policies without requiring centralized access to training

FIDAL: Diversity-Aware Federated Active Learning Under Real-World Distribution Shifts

arXiv:2609.31637v1 Announce Type: cross Abstract: Federated learning enables collaborative model training across institutions without centralizing data, yet high annotation costs, domain shifts, and c

First Learn, Then Memorize: The Spectral Bias of Diffusion Models

arXiv:2609.35377v1 Announce Type: new Abstract: Diffusion models trained on a finite dataset first learn to generate novel, high-quality samples and only much later collapse onto their training set. W

FloodDiffusion 2: Efficient and Path Controllable Streaming Motion Generation

arXiv:2609.33167v1 Announce Type: new Abstract: We present FloodDiffusion 2 (FD2), an efficient and controllable framework that builds upon FloodDiffusion (FD1), a state-of-the-art streaming motion ge

applicationsarxiv-cs-cv

Flow-Matching-Based Protein Structure Tokenizer Made Efficient and Easy

arXiv:2609.33129v1 Announce Type: new Abstract: As the bridge between protein modality and discrete modeling, protein structure tokenization still largely relies on heavily engineered training objecti

FlowTool: Controlling Tool Parameter in Image Retouching via Flow Matching

arXiv:2609.35673v1 Announce Type: new Abstract: Tool-based image editing (image retouching) is commonly formulated with autoregressive multimodal large language models (MLLMs) that sequentially genera

Focus on Likely Classes for Test-Time Prediction

arXiv:2505.03819v4 Announce Type: replace Abstract: We ask: Can focusing on likely classes of a single, in-domain sample improve accuracy? Prior work argued 'no', we answer 'yes' on average. Standard

FoLD: Force-Informed Learning for Dexterous Articulated Object Manipulation

model-releasesarxiv-cs-ro

arXiv:2609.33551v1 Announce Type: new Abstract: Transferring human demonstrations to dexterous robots remains challenging because differences in hand morphology and contact dynamics often cause retarg

Forecast-Necessary Causal Discovery for Nonlinear Political Panel Data: Feedback, Functional Form, and the Dynamics of Democratization

arXiv:2609.34115v1 Announce Type: cross Abstract: A non-significant coefficient in a dynamic panel model need not imply the absence of a relationship. It may instead reflect heterogeneous effects aver

FoundDSR: A Generalizable Foundation Model with Guided 2D Gaussian Splatting for Depth Super-Resolution

arXiv:2609.32323v1 Announce Type: new Abstract: We introduce FoundDSR, a generalizable foundation model for robust depth reconstruction across unseen data distributions using RGB-D pairs. FoundDSR beg

From Attention Sensitivity to Layer Role: Revisiting Mixed-Precision Quantization of Transformers

arXiv:2609.34866v1 Announce Type: new Abstract: Most post-training quantization pipelines fit each weight matrix to its pretrained counterpart, one matrix at a time. Whether that proxy tracks what an

From Data to Program: Fast & Direct Generative Program Inference from Empirical Data

arXiv:2609.35348v1 Announce Type: new Abstract: Estimating probability densities from a finite set of samples typically requires dataset-specific model fitting. We introduce PRODiGI, a pretrained data