Search: “pretraining”

Did the Grid Erase the Event? EndoClock for Auditing Medical World-Model Pipelines

arXiv:2608.09266v1 Announce Type: new Abstract: Medical world models commonly learn from multimodal recordings synchronized onto a fixed-rate grid. This preprocessing resamples each native stream onto

tutorialsarxiv-cs-cv

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

DINO-3DRA: Leveraging 2D Foundation Model Semantics for 3D Cerebral Aneurysm Segmentation

DGX agent

arXiv:2608.07767v1 Announce Type: new Abstract: Accurate aneurysm segmentation in 3D rotational angiography (3DRA) is hindered by extreme class imbalance, morphological similarity to vessels, and abse

researcharxiv-cs-cv

11 Aug 2026

Diversity Matters: Distributional Feature Coverage Sample Selection for Data-Efficient Backdoor Attacks

arXiv:2608.09047v1 Announce Type: cross Abstract: Backdoor attacks compromise training data so that a model retains clean accuracy but predicts an attacker-chosen target on triggered inputs. At very l

Ensemble learning of pathology foundation models for precision oncology

arXiv:2508.16085v2 Announce Type: replace Abstract: Histopathology is essential for cancer diagnosis and treatment selection, and pathology foundation models learn visual representations from whole-sl

tutorialsarxiv-cs-cv

Explaining, Verifying, and Aligning Semantic Hierarchies in Vision-Language Model Embeddings

arXiv:2603.26798v2 Announce Type: replace-cross Abstract: Vision-language model (VLM) encoders such as CLIP enable strong retrieval and zero-shot classification in a shared image-text embedding space,

safetyarxiv-cs-ai

FeedbackTrack: Visual-Cortex-Inspired Cross-Frame Feedback for Transformer Tracking

arXiv:2608.09369v1 Announce Type: cross Abstract: Visual object tracking requires effective temporal integration, yet most Transformer trackers still rely on predominantly feed-forward feature extract

FoMoH: A clinically meaningful foundation model evaluation for structured electronic health records

model-releasesarxiv-cs-ai

arXiv:2505.16941v4 Announce Type: replace-cross Abstract: Foundation models (FMs) promise to address core limitations of traditional supervised machine learning: (i) reliance on large amounts of label

Frequency-Domain Dual-Branch Fusion for Medical Visual Question Answering

arXiv:2608.08307v1 Announce Type: cross Abstract: Medical Visual Question Answering (VQA) requires aligning subtle visual evidence, including lesion texture, boundary sharpness, and diffuse density ch

From Alignment to Synthesis Contrastive Volumetric Grounding for Text-to-CT Generation

arXiv:2506.00633v3 Announce Type: replace-cross Abstract: Generating semantically controllable 3D CT volumes from radiology reports requires more than a rich text encoder, it requires vision-language

safetyarxiv-cs-ai

Full-bandwidth transformer

model-releasesarxiv-cs-ai

arXiv:2608.08888v1 Announce Type: new Abstract: Autoregressive transformers compute along two axes: horizontally across generated tokens, and vertically through model depth. Dense attention gives each

Applications

Ground-Truth Neighborhood Regularization for Reinforcement Learning Post-Training of Time Series Foundation Models

arXiv:2608.08010v1 Announce Type: cross Abstract: Time series forecasting (TSF) plays an important role in a wide range of real-world applications. Recently, time series foundation models (TSFMs), pre

applicationsarxiv-cs-ai

How Far Do Foundation Models Transfer to Infant Signals? A Cross-Dataset Transfer Audit with a Unified Need Ontology

arXiv:2608.08989v1 Announce Type: cross Abstract: Public infant cry corpora are small, label-incompatible, and almost always evaluated one corpus at a time. We ask what this practice hides and what fi

Imaginative Generative AI: Crossing the Entropy Wall into Worlds Beyond Imitation

arXiv:2608.09385v1 Announce Type: cross Abstract: Generative AI models are primarily designed to imitate the data distribution, an objective that neither corrects diversity lost by a learned generator

In-Context Density Estimation for Tabular Data

arXiv:2608.09348v1 Announce Type: new Abstract: Density estimation underlies many unsupervised tasks on tabular data such as anomaly detection, out-of-distribution detection, and data augmentation. Al

researcharxiv-cs-lg

InstructionCrafter: Generating Consistent and High-Fidelity Visual Instructions

model-releasesarxiv-cs-cv

arXiv:2608.08460v1 Announce Type: new Abstract: Given textual task instructions, generating step-by-step visual instructions as an image sequence requires the simultaneous satisfaction of multiple pro

Label-Free Parkinson's Disease Screening from Face and Voice through Mechanistic Interpretability

model-releasesarxiv-cs-lg

arXiv:2608.08976v1 Announce Type: new Abstract: Parkinson's disease (PD) is the second most common neurodegenerative disorder. Typical machine learning screening methods require PD labels, but the ava

Learning Deep Modality-Shared Self-Expressiveness for Image Clustering with Textual Information

arXiv:2608.08418v1 Announce Type: new Abstract: Leveraging textual information for image clustering has emerged as a promising direction, largely owing to the powerful representations learned by Visio

safetyarxiv-cs-cv

Learning human joint torques from pixels

model-releasesarxiv-cs-cv

arXiv:2608.09083v1 Announce Type: new Abstract: Estimating human joint torques from visual observations is a key step toward bringing biomechanical analysis from controlled laboratories to real-world

Let Geometry GUIDE: Layer-wise Unrolling of Geometric Priors in Multimodal LLMs

arXiv:2604.05695v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress in 2D visual tasks but still struggle to understand physical space in rea

tutorialsarxiv-cs-cv

LUCID: Latent-Skill Unified Control via Imagined Dynamics for Long-Horizon Humanoid Loco-Manipulation

arXiv:2608.07746v1 Announce Type: new Abstract: Long-horizon humanoid loco-manipulation requires composing versatile whole-body skills and reliable high-level decision making. Existing methods often c

safetyarxiv-cs-lg

MADBench: A Benchmark for Modality-Aware Audio Deepfake Detection

model-releasesarxiv-cs-ai

arXiv:2608.09593v1 Announce Type: cross Abstract: Recent advances in speech synthesis and audio generation have made high-fidelity acoustic forgery low-cost and difficult to attribute, enabling a real

Applications

MeanSR: Restoration Trajectory Learning for One-Step Perceptual Super-Resolution

arXiv:2608.09405v1 Announce Type: new Abstract: Diffusion-based super-resolution (SR) achieves strong perceptual quality but requires costly iterative denoising. Existing one-step distillation methods

applicationsarxiv-cs-cv

Motif 3: Technical Report

arXiv:2608.09119v1 Announce Type: new Abstract: We introduce Motif 3, a decoder-only Mixture-of-Experts language model with 314 billion total parameters and 13.2 billion activated per token. Each spar

safetyarxiv-cs-ai

Neural Message Passing on Structural Interaction Graphs for Fully-Inductive Graph Neural Networks

arXiv:2608.08567v1 Announce Type: new Abstract: A central obstacle in building graph foundation models is the input heterogeneity in terms of feature space dimensionality, semantics, and structure. Su

safetyarxiv-cs-lg

OccAnyScene: Towards Unified Indoor-Outdoor 3D Occupancy Predictio

arXiv:2608.08696v1 Announce Type: new Abstract: 3D occupancy prediction is fundamental to scene understanding, yet existing 3D semantic occupancy methods are typically specialized to fixed scene types

PatchHead: Learning Spatial Patch Evidence for Generalizable AI-Generated Image Detection

arXiv:2608.09223v1 Announce Type: new Abstract: AI-generated image detectors generalize poorly when their training and test images originate from different generators or datasets. Despite the rich spa

Predictive Failure Detection in Network Hardware Using Thermal Imaging and Deep Learning with Sensor Fusion

arXiv:2608.07582v1 Announce Type: new Abstract: Unplanned network hardware malfunctions can interrupt services and result in expensive downtime in data centers. A deep learning-based predictive mainte

Preserving Item Semantics for Free: Rethinking Token Initialization in LLM-Based Generative Recommendation

model-releasesarxiv-cs-lg

arXiv:2608.07816v1 Announce Type: cross Abstract: Recent advances in generative recommendation (GR) leverage large language models (LLMs) as recommender backbones, enabling LLMs to directly generate r

RA-FinBERT: Rule-aware LoRA adaptation for low-resource financial sentiment classification

model-releasesarxiv-cs-cl

arXiv:2608.09834v1 Announce Type: new Abstract: Financial sentiment analysis converts unstructured financial news into quantitative signals that can support market analysis and decision-making. Existi

SC-Diff: Semantically Calibrated Diffusion for Visible-to-Infrared Image Translation

arXiv:2608.08555v1 Announce Type: new Abstract: Visible-to-infrared image translation provides a practical way to expand infrared training data using abundant visible images. Diffusion models are prom

safetyarxiv-cs-cv

Applications

Search over the Visual World: Persistent Visual Memory, Layered Indexes, and Source-Grounded Evidence

arXiv:2608.08075v1 Announce Type: cross Abstract: Most video-retrieval systems assume a bounded corpus and return ranked files or timestamps. Agents operating over cameras, screens, streams, and archi

applicationsarxiv-cs-cv

SegDem: Segmentation helps Demosaicing

arXiv:2608.07916v1 Announce Type: new Abstract: Image demosaicing reconstructs a full-color image from incomplete color measurements produced by a sensor covered with a color filter array (CFA). Most

Semi-Dense Matching Uncertainty Is Not Just Local Confidence

arXiv:2608.08685v1 Announce Type: new Abstract: Reliable semi-dense matching is essential for modern geometric vision systems. Designed under a coarse-to-fine paradigm, it achieves an optimal balance

Agents

SemPIC: Learning Semantic Position-Independent KV Caches

arXiv:2607.28069v2 Announce Type: replace Abstract: Long-context retrieval and agentic workloads repeatedly reuse the same documents under changing instructions, histories, and document orders. Prefix

agentsarxiv-cs-ai

SLIM-0.5B: Learning Action-Grounded Predictive Latents for Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.09771v1 Announce Type: new Abstract: Vision-language-action policies rely on large multimodal backbones to jointly perform perception, language conditioning, and action generation at every

The Evolution of Mixture-of-Experts Architectures in Large Language Models: Routing, Topology, Load Balancing, and Expert Parallelism

model-releasesarxiv-cs-cl

arXiv:2608.08650v1 Announce Type: new Abstract: Mixture-of-Experts models increase parameter capacity while keeping the computation activated by each token bounded, but their architectural evolution c

Transfer Learning-Enabled Distortion Compensation for Amplitude-Phase-Time Block Modulation-Based Nonlinear Single-Carrier Wireless Communications

arXiv:2608.08554v1 Announce Type: cross Abstract: Power amplifier (PA) nonlinearity and memory effects significantly limit the spectral compliance, reliability, and energy efficiency of communication

researcharxiv-cs-lg

TriView-YOLO: Early Multi-View Fusion for Ground Penetrating Radar Cavity Detection in Soft, High-Water-Content Soils

arXiv:2608.09522v1 Announce Type: new Abstract: Automated detection of subsurface cavities from Ground Penetrating Radar (GPR) is most difficult in soft, high-water-content ground, where conductive, w

Local Ai

Vision-Language Grounding as Bidirectional Concept Correspondence

arXiv:2608.07886v1 Announce Type: cross Abstract: Vision-language grounding connects language to visual content, yet most existing formulations reduce grounding to a unidirectional localization proble

local-aiarxiv-cs-ai

When Latents Forget Pixels: Restoring Fidelity in Diffusion Transformer Super-Resolution

arXiv:2608.09133v1 Announce Type: cross Abstract: Image super-resolution (SR) with large generative models has recently achieved remarkable perceptual quality, yet maintaining fidelity to the LR obser

tutorialsarxiv-cs-ai

ZetaGPT: A Reference Implementation of Positional--Encoding--Free State--Space--Attention Language Models

arXiv:2608.09432v1 Announce Type: cross Abstract: Transformer-based language models rely on self-attention, whose computation is permutation-equivariant and therefore lacks an intrinsic mechanism for

CrossTracer: Cross-Embodiment Navigation via VLA Model Reasoning and Trace Residuals Adapting

model-releasesarxiv-cs-ro

arXiv:2608.06688v1 Announce Type: new Abstract: Vision-language-action (VLA) models provide strong semantic priors for robot navigation, but they often ignore embodiment-specific mobility constraints.

Degradation-Aware Prompt Learning with Cross-Modal Compensation for Adverse Weather Removal

arXiv:2608.06939v1 Announce Type: new Abstract: Adverse weather causes diverse and complex image degradations, severely compromising the reliability of computer vision systems. Existing all-in-one res

safetyarxiv-cs-cv

Local Ai

Dual-Node NVIDIA DGX Spark over Tailscale: A Remote-Access Testbed for Distributed LLM Training and Cyber-Threat-Intelligence Fine-Tuning

arXiv:2608.07226v1 Announce Type: cross Abstract: Compact AI systems make local language-model experimentation increasingly accessible, yet practical evidence for multi-node training on desktop-class

local-aiarxiv-cs-lg

Agents

Dueling World Models: Advantage-Style Action Channels for Common-Mode Distractor Rejection

arXiv:2608.06706v1 Announce Type: cross Abstract: Latent world models plan by predicting future states from an action, but when a scene contains motion the agent does not control, they quietly go acti

agentsarxiv-cs-ai

DynaCrys: Crystal Generation with Dynamic Space-Group Diffusion

arXiv:2608.07401v1 Announce Type: cross Abstract: The search for new crystalline materials spans an enormous compositional and structural space. Generating candidates in this space requires jointly mo

researcharxiv-cs-lg

Fast and Accurate: An Adaptive VLA Inference Framework through Environment-aware Model Selection

model-releasesarxiv-cs-lg

arXiv:2608.06434v1 Announce Type: cross Abstract: Embodied intelligence demands both long-horizon reasoning and real-time closed-loop responsiveness. Recent dual-system Vision-Language-Action (VLA) ar

Local Ai

HazeSpikeMamba: Coupling Spiking-Inspired and State-Space Features for Self-Supervised Real-World Dehazing

arXiv:2608.06886v1 Announce Type: new Abstract: Dehazing networks are commonly trained on synthetic hazy-clear pairs, but their performance often drops on real photographs. Synthetic haze generated us

local-aiarxiv-cs-cv