Search: “evaluation”

Audio Source Separation in Reverberant Environments using eta-divergence based Nonnegative Factorization

arXiv:2604.12480v1 Announce Type: cross Abstract: In Gaussian model-based multichannel audio source separation, the likelihood of observed mixtures of source signals is parametrized by source spectral

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Beyond Relevance: On the Relationship Between Retrieval and RAG Information Coverage

DGX agent

arXiv:2603.08819v3 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) systems combine document retrieval with a generative model to address complex information seeking tasks l

model-releasesarxiv-cs-ai

15 Apr 2026

BID-LoRA: A Parameter-Efficient Framework for Continual Learning and Unlearning

arXiv:2604.12686v1 Announce Type: cross Abstract: Recent advances in deep learning underscore the need for systems that can not only acquire new knowledge through Continual Learning (CL) but also remo

Bilevel Late Acceptance Hill Climbing for the Electric Capacitated Vehicle Routing Problem

arXiv:2604.13013v1 Announce Type: new Abstract: This paper tackles the Electric Capacitated Vehicle Routing Problem (E-CVRP) through a bilevel optimization framework that handles routing and charging

Local Ai

BIND-USBL: Bounding IMU Navigation Drift using USBL in Heterogeneous ASV-AUV Teams

arXiv:2604.11861v1 Announce Type: new Abstract: Accurate and continuous localization of Autonomous Underwater Vehicles (AUVs) in GPS-denied environments is a persistent challenge in marine robotics. I

local-aiarxiv-cs-ro

Applications

BINDER: Instantly Adaptive Mobile Manipulation with Open-Vocabulary Commands

arXiv:2511.22364v2 Announce Type: replace-cross Abstract: Open-vocabulary mobile manipulation (OVMM) requires robots to follow language instructions, navigate, and manipulate while updating their worl

applicationsarxiv-cs-ai

Agents

BLOSSOM: Block-wise Federated Learning Over Shared and Sparse Observed Modalities

arXiv:2603.27552v2 Announce Type: replace Abstract: Multimodal federated learning (FL) is essential for real-world applications such as autonomous systems and healthcare, where data is distributed acr

agentsarxiv-cs-lg

Boosting Visual Instruction Tuning with Self-Supervised Guidance

arXiv:2604.12966v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) perform well on many vision-language tasks but often struggle with vision-centric problems that require fine-gr

Brain-DiT: A Universal Multi-state fMRI Foundation Model with Metadata-Conditioned Pretraining

arXiv:2604.12683v1 Announce Type: new Abstract: Current fMRI foundation models primarily rely on a limited range of brain states and mismatched pretraining tasks, restricting their ability to learn ge

safetyarxiv-cs-cv

Challenging Vision-Language Models with Physically Deployable Multimodal Semantic Lighting Attacks

arXiv:2604.12833v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have shown remarkable performance, yet their security remains insufficiently understood. Existing adversarial studies focu

safetyarxiv-cs-cv

Applications

Characterizing Human Semantic Navigation in Concept Production as Trajectories in Embedding Space

arXiv:2602.05971v2 Announce Type: replace Abstract: Semantic representations can be framed as a structured, dynamic knowledge space through which humans navigate to retrieve and manipulate meaning. To

applicationsarxiv-cs-cl

CLAD: Efficient Log Anomaly Detection Directly on Compressed Representations

arXiv:2604.13024v1 Announce Type: new Abstract: The explosive growth of system logs makes streaming compression essential, yet existing log anomaly detection (LAD) methods incur severe pre-processing

researcharxiv-cs-lg

Clustering with Uniformity- and Neighbor-Based Random Geometric Graphs

model-releasesarxiv-cs-lg

arXiv:2501.06268v3 Announce Type: replace Abstract: We propose a graph-based clustering method based on Cluster Catch Digraphs (CCDs) that extends their applicability to moderate-dimensional data sett

CoDe-R: Refining Decompiler Output with LLMs via Rationale Guidance and Adaptive Inference

arXiv:2604.12913v1 Announce Type: cross Abstract: Binary decompilation is a critical reverse engineering task aimed at reconstructing high-level source code from stripped executables. Although Large L

Comparison of low Steps, Klein 9b x Z image turbo x Ernie Turbo x Qwen 2512 8 Steps

model-releasesr-stablediffusion

This r/StableDiffusion post presents a community-driven visual comparison of several modern, fast text-to-image diffusion models — Flux.2 Klein 9B (a smaller, faster distillation of Flux.2 Dev availab

Compiling Activation Steering into Weights via Null-Space Constraints for Stealthy Backdoors

arXiv:2604.12359v1 Announce Type: cross Abstract: Safety-aligned large language models (LLMs) are increasingly deployed in real-world pipelines, yet this deployment also enlarges the supply-chain atta

safetyarxiv-cs-cl

Local Ai

Complex & Weird Prompt Test: ERNIE Turbo | Flux.2 Klein 4B | Z-Image Turbo

local-air-stablediffusion

This r/StableDiffusion post presents a community benchmark testing how three compact, fast AI image generation models — ERNIE Turbo, Flux.2 Klein 4B, and Z-Image Turbo — handle complex and unconventio

ContextLens: Modeling Imperfect Privacy and Safety Context for Legal Compliance

arXiv:2604.12308v1 Announce Type: new Abstract: Individuals' concerns about data privacy and AI safety are highly contextualized and extend beyond sensitive patterns. Addressing these issues requires

safetyarxiv-cs-cl

Continuous Knowledge Metabolism: Generating Scientific Hypotheses from Evolving Literature

arXiv:2604.12243v1 Announce Type: cross Abstract: Scientific hypothesis generation requires tracking how knowledge evolves, not just what is currently known. We introduce Continuous Knowledge Metaboli

Cool stuff Google Cloud customers built, April edition: BMW big on SLMs, MLB’s Scout Insights AI, personalized resort experiences

model-releasesgoogle-cloud-ai

AI and cloud technology are reshaping every corner of every industry around the world. Without our customers, who are building the future on our platform, there would be no Google Cloud. In this regul

CropVLM: Learning to Zoom for Fine-Grained Vision-Language Perception

arXiv:2511.19820v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) often struggle with tasks that require fine-grained image understanding, such as scene-text recognition or docum

Cross-Attentive Multiview Fusion of Vision-Language Embeddings

arXiv:2604.12551v1 Announce Type: new Abstract: Vision-language models have been key to the development of open-vocabulary 2D semantic segmentation. Lifting these models from 2D images to 3D scenes, h

Cross-Cultural Simulation of Citizen Emotional Responses to Bureaucratic Red Tape Using LLM Agents

arXiv:2604.12545v1 Announce Type: new Abstract: Improving policymaking is a central concern in public administration. Prior human subject studies reveal substantial cross-cultural differences in citiz

Cross-Domain Transfer with Particle Physics Foundation Models: From Jets to Neutrino Interactions

arXiv:2604.12364v1 Announce Type: cross Abstract: Future AI-based studies in particle physics will likely start from a foundation model to accelerate training and enhance sensitivity. As a step toward

researcharxiv-cs-lg

Cross-Modal Knowledge Distillation for PET-Free Amyloid-Beta Detection from MRI

arXiv:2604.12574v1 Announce Type: new Abstract: Detecting amyloid-eta (Aeta) positivity is crucial for early diagnosis of Alzheimer's disease but typically requires PET imaging, which is costly, invas

safetyarxiv-cs-cv

Curvelet-Based Frequency-Aware Feature Enhancement for Deepfake Detection

arXiv:2604.12028v1 Announce Type: cross Abstract: The proliferation of sophisticated generative models has significantly advanced the realism of synthetic facial content, known as deepfakes, raising s

CycloneMAE: A Scalable Multi-Task Learning Model for Global Tropical Cyclone Probabilistic Forecasting

arXiv:2604.12180v1 Announce Type: cross Abstract: Tropical cyclones (TCs) rank among the most destructive natural hazards, yet their forecasting faces fundamental trade-offs: numerical weather predict

Agents

D-BDM: A Direct and Efficient Boundary-Based Occupancy Grid Mapping Framework for LiDARs

arXiv:2604.12436v1 Announce Type: new Abstract: Efficient and scalable 3D occupancy mapping is essential for autonomous robot applications in unknown environments. However, traditional occupancy grid

agentsarxiv-cs-ro

DBGL: Decay-aware Bipartite Graph Learning for Irregular Medical Time Series Classification

arXiv:2604.11842v1 Announce Type: cross Abstract: Irregular Medical Time Series play a critical role in the clinical domain to better understand the patient's condition. However, inherent irregularity

Deep Learning using Rectified Linear Units (ReLU)

arXiv:1803.08375v3 Announce Type: replace-cross Abstract: The Rectified Linear Unit (ReLU) is a foundational activation function in artficial neural networks. Recent literature frequently misattribute

DeferredSeg: A Multi-Expert Deferral Framework for Trustworthy Medical Image Segmentation

arXiv:2604.12411v1 Announce Type: new Abstract: Segmentation models based on deep neural networks demonstrate strong generalization for medical image segmentation. However, they often exhibit overconf

Detecting and refurbishing ground truth errors during training of deep learning-based echocardiography segmentation models

arXiv:2604.12832v1 Announce Type: cross Abstract: Deep learning-based medical image segmentation typically relies on ground truth (GT) labels obtained through manual annotation, but these can be prone

Detecting Complex Money Laundering Patterns with Incremental and Distributed Graph Modeling

model-releasesarxiv-cs-lg

arXiv:2604.01315v2 Announce Type: replace Abstract: Money launderers take advantage of limitations in existing detection approaches by hiding their financial footprints in a deceitful manner. They man

Detecting Precise Hand Touch Moments in Egocentric Video

arXiv:2604.12343v1 Announce Type: new Abstract: We address the challenging task of detecting the precise moment when hands make contact with objects in egocentric videos. This frame-level detection is

Agents

DINO-Explorer: Active Underwater Discovery via Ego-Motion Compensated Semantic Predictive Coding

arXiv:2604.12933v1 Announce Type: cross Abstract: Marine ecosystem degradation necessitates continuous, scientifically selective underwater monitoring. However, most autonomous underwater vehicles (AU

agentsarxiv-cs-cv

Distorted or Fabricated? A Survey on Hallucination in Video LLMs

arXiv:2604.12944v1 Announce Type: cross Abstract: Despite significant progress in video-language modeling, hallucinations remain a persistent challenge in Video Large Language Models (Vid-LLMs), refer

Document OCR benchmarks are still an open problem Existing document OCR benchmarks are either too narrowly focused on a specific type (e.g. …

model-releasesjerry-liu--x

Document OCR benchmarks are still an open problem Existing document OCR benchmarks are either too narrowly focused on a specific type (e.g. FinTabNet, ChartQA), or on documents that aren’t reflective

Does RLVR Extend Reasoning Boundaries? Investigating Capability Expansion in Vision-Language Models

arXiv:2511.00710v4 Announce Type: replace Abstract: Recent studies posit that Reinforcement Learning with Verifiable Rewards (RLVR) primarily amplifies behaviors inherent to the pre-training distribut

DoseRAD2026 Challenge dataset: AI accelerated photon and proton dose calculation for radiotherapy

arXiv:2604.12778v1 Announce Type: cross Abstract: Purpose: Accurate dose calculation is essential in radiotherapy for precise tumor irradiation while sparing healthy tissue. With the growing adoption

DyBBT: Dynamic Balance via Bandit-inspired Targeting for Dialog Policy with Cognitive Dual-Systems

arXiv:2509.19695v3 Announce Type: replace-cross Abstract: Task oriented dialog systems often rely on static exploration strategies that do not adapt to dynamic dialog contexts, leading to inefficient

Dynamic Modeling and Robust Gait Optimization of a Compliant Worm Robot

arXiv:2604.12031v1 Announce Type: new Abstract: Worm-inspired robots provide an effective locomotion strategy for constrained environments by combining cyclic body deformation with alternating anchori

researcharxiv-cs-ro

Elastic Net Regularization and Gabor Dictionary for Classification of Heart Sound Signals using Deep Learning

arXiv:2604.12483v1 Announce Type: cross Abstract: In this article, we propose the optimization of the resolution of time-frequency atoms and the regularization of fitting models to obtain better repre

Enabling Ultra-Fast Cardiovascular Imaging Across Heterogeneous Clinical Environments with A Generalist Foundation Model and Multimodal Database

arXiv:2512.21652v2 Announce Type: replace-cross Abstract: Multimodal cardiovascular magnetic resonance (CMR) imaging provides comprehensive and non-invasive insights into cardiovascular disease (CVD)

Enhancing Agentic Textual Graph Retrieval with Synthetic Stepwise Supervision

arXiv:2510.03323v2 Announce Type: replace Abstract: Integrating textual graphs into Large Language Models (LLMs) is promising for complex graph-based QA. However, a key bottleneck is retrieving inform

safetyarxiv-cs-cl

Every Picture Tells a Dangerous Story: Memory-Augmented Multi-Agent Jailbreak Attacks on VLMs

arXiv:2604.12616v1 Announce Type: new Abstract: The rapid evolution of Vision-Language Models (VLMs) has catalyzed unprecedented capabilities in artificial intelligence; however, this continuous modal

Evolving the Complete Muscle: Efficient Morphology-Control Co-design for Musculoskeletal Locomotion

arXiv:2604.12855v1 Announce Type: new Abstract: Musculoskeletal robots offer intrinsic compliance and flexibility, providing a promising paradigm for versatile locomotion. However, existing research t

researcharxiv-cs-ro

FABLE: Fine-grained Fact Anchoring for Unstructured Model Editing

model-releasesarxiv-cs-cl

arXiv:2604.12559v1 Announce Type: new Abstract: Unstructured model editing aims to update models with real-world text, yet existing methods often memorize text holistically without reliable fine-grain

FaCT: Faithful Concept Traces for Explaining Neural Network Decisions

arXiv:2510.25512v2 Announce Type: replace-cross Abstract: Deep networks have shown remarkable performance across a wide range of tasks, yet getting a global concept-level understanding of how they fun