Search: “pretraining”

A Foundation Model for Zero-Shot Logical Rule Induction

arXiv:2605.04916v1 Announce Type: cross Abstract: Inductive Logic Programming (ILP) learns interpretable logical rules from data. Existing methods are transductive: their learned parameters are bound

applicationsarxiv-cs-lg

A Scalable Multi-Task Model for Virtual Sensors

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DGX agent

arXiv:2601.20634v2 Announce Type: replace Abstract: Virtual sensors replace expensive physical sensors in critical applications through machine learning by predicting target signals from available mea

model-releasesarxiv-cs-lg

7 May 2026

Adaptive Policy Selection and Fine-Tuning under Interaction Budgets for Offline-to-Online Reinforcement Learning

arXiv:2605.05123v1 Announce Type: new Abstract: In offline-to-online reinforcement learning (O2O-RL), policies are first safely trained offline using previously collected datasets and then further fin

safetyarxiv-cs-lg

Breaking the Quality-Privacy Tradeoff in Tabular Data Generation via In-Context Learning

arXiv:2605.04911v1 Announce Type: new Abstract: Tabular data synthesis aims to generate high-quality data while preserving privacy. However, we find that existing tabular generative models exhibit a c

applicationsarxiv-cs-lg

Chaotic Contrastive Learning for Robust Texture Classification

arXiv:2605.05012v1 Announce Type: new Abstract: Texture classification is a pivotal task in computer vision, presenting unique challenges due to high inter-class similarity and the sensitivity of stru

Deep Reprogramming Distillation for Medical Foundation Models

arXiv:2605.04447v1 Announce Type: new Abstract: Medical foundation models pre-trained on large-scale datasets have shown powerful versatile performance. However, when adapting medical foundation model

Deepfake Audio Detection Using Self-supervised Fusion Representations

arXiv:2605.03420v1 Announce Type: cross Abstract: This paper describes a submission to the Environment-Aware Speech and Sound Deepfake Detection Challenge (ESDD2) 2026, which addresses component-level

researcharxiv-cs-ai

Empirical Study of Pop and Jazz Mix Ratios for Genre-Adaptive Chord Generation

arXiv:2605.04998v1 Announce Type: cross Abstract: Chord progression generation is practically important but understudied. Most large-scale symbolic music systems target melody, multi-track arrangement

FairEnc: A Fair Vision-Language Model with Fair Vision and Text Encoders for Glaucoma Detection

arXiv:2605.04882v1 Announce Type: new Abstract: Automated glaucoma detection is critical for preventing irreversible vision loss and reducing the burden on healthcare systems. However, ensuring fairne

safetyarxiv-cs-cv

Feature Identification via the Empirical NTK

arXiv:2510.00468v4 Announce Type: replace Abstract: We provide evidence that eigenanalysis of the empirical neural tangent kernel (eNTK) can surface feature directions in trained neural networks. Acro

Few-Shot Learning Pipeline for Monkeypox Skin Disease Classification Using CNN Feature Extractors

arXiv:2605.05034v1 Announce Type: new Abstract: Despite the strong performance of Convolutional Neural Networks (CNNs) in disease classification, their effectiveness often depends on access to large a

From Diffusion to Rectified Flow: Rethinking Text-Based Segmentation

arXiv:2605.04590v1 Announce Type: new Abstract: Text-based image segmentation aims to delineate object boundaries within an image from text prompts, offering higher flexibility and broader application

Height-Guided Projection Reparameterization for Camera-LiDAR Occupancy

arXiv:2605.05072v1 Announce Type: new Abstract: 3D occupancy prediction aims to infer dense, voxel-wise scene semantics from sensor observations, where the 2D-to-3D view transformation serves as a cru

applicationsarxiv-cs-cv

Local Ai

HEXST: Hexagonal Shifted-Window Transformer for Spatial Transcriptomics Gene Expression Prediction

arXiv:2605.04682v1 Announce Type: cross Abstract: Spatial transcriptomics offers spatially resolved gene expression profiling within tissue sections, but its cost and limited throughput hinder large-s

local-aiarxiv-cs-cv

HistoMet: A Pan-Cancer Deep Learning Framework for Prognostic Prediction of Metastatic Progression and Site Tropism from Primary Tumor Histopathology

arXiv:2602.07608v2 Announce Type: replace Abstract: Metastatic Progression remains the leading cause of cancer-related mortality, yet predicting whether a primary tumor will metastasize and where it w

InSpatio-WorldFM: An Open-Source Real-Time Generative Frame Model

arXiv:2603.11911v3 Announce Type: replace Abstract: We present InSpatio-WorldFM, an open-source real-time frame model for spatial intelligence. Unlike video-based world models that rely on sequential

LEGO: LoRA-Enabled Generator-Oriented Framework for Synthetic Image Detection

arXiv:2605.04445v1 Announce Type: new Abstract: The rapid advancement of generative technologies has made synthetic images nearly indistinguishable from real ones, thereby creating an urgent need for

LUCAS-MEGA: A Large-Scale Multimodal Dataset for Representation Learning in Soil-Environment Systems

arXiv:2605.04323v1 Announce Type: new Abstract: Understanding soil is fundamental to agriculture, carbon cycling, and environmental sustainability, yet progress is limited by fragmented and heterogene

MIRAGE: Retrieval and Generation of Multimodal Images and Texts for Medical Education

arXiv:2605.04772v1 Announce Type: new Abstract: Access to diverse, well-annotated medical images with interactive learning tools is fundamental for training practitioners in medicine and related field

applicationsarxiv-cs-cv

Open-Source Image Editing Models Are Zero-Shot Vision Learners

model-releasesarxiv-cs-cl

arXiv:2605.04566v1 Announce Type: cross Abstract: Recent studies have shown that large generative models can solve vision tasks they were not explicitly trained for. However, existing evidence relies

OracleProto: A Reproducible Framework for Benchmarking LLM Native Forecasting via Knowledge Cutoff and Temporal Masking

arXiv:2605.03762v1 Announce Type: new Abstract: Large language models are moving from static text generators toward real-world decision-support systems, where forecasting is a composite capability tha

safetyarxiv-cs-ai

Prompt-Anchored Vision-Text Distillation for Lifelong Person Re-identification

arXiv:2605.05027v1 Announce Type: new Abstract: Lifelong person re-identification (LReID) aims to train a generalizable model with sequentially collected data. However, such models often suffer from s

SAMIC: A Lightweight Semantic-Aware Mamba for Efficient Perceptual Image Compression

arXiv:2605.04560v1 Announce Type: new Abstract: Perceptual image compression focuses on preserving high visual quality under low-bitrate constraints. Most existing approaches to perceptual compression

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion

arXiv:2605.04412v1 Announce Type: new Abstract: 3D asset generation plays a pivotal role in fields such as gaming and virtual reality, enabling the rapid synthesis of high-fidelity 3D objects from a s

Taming Outlier Tokens in Diffusion Transformers

arXiv:2605.05206v1 Announce Type: new Abstract: We study outlier tokens in Diffusion Transformers (DiTs) for image generation. Prior work has shown that Vision Transformers (ViTs) can produce a small

Adaptive Data Compression and Reconstruction for Memory-Bounded EEG Continual Learning

arXiv:2605.03085v1 Announce Type: new Abstract: Electroencephalography (EEG) signals provide millisecond-level temporal resolution but their analysis is limited by remarkable noise and inter-subject v

researcharxiv-cs-lg

Audio-Visual Intelligence in Large Foundation Models

arXiv:2605.04045v1 Announce Type: new Abstract: Audio-Visual Intelligence (AVI) has emerged as a central frontier in artificial intelligence, bridging auditory and visual modalities to enable machines

safetyarxiv-cs-cv

Direct Simultaneous Translation Activation for Large Audio-Language Models

arXiv:2509.15692v2 Announce Type: replace-cross Abstract: Simultaneous speech-to-text translation (Simul-S2TT) aims to translate speech into target text in real time, outputting translations while rec

tutorialsarxiv-cs-cl

Give LLMs 1. A latent space diffusion-like reasoning. 2. A real recurrent state. 3. A world-model pre-pre-training. And we are done.

tutorialsjeremy-howard--x

Jeremy Howard proposes three key enhancements for large language models: incorporating latent space diffusion-like reasoning processes, adding a persistent recurrent state mechanism, and implementing

Hierarchical Memorization in Large Language Models: Evidence from Citation Generation

model-releasesarxiv-cs-cl

arXiv:2511.08877v2 Announce Type: replace Abstract: Large language models (LLMs) generate fluent text across a wide range of tasks, but the fabrication of non-existent academic citations remains a cri

MILE: Mixture of Incremental LoRA Experts for Continual Semantic Segmentation across Domains and Modalities

arXiv:2605.03555v1 Announce Type: new Abstract: Continual semantic segmentation requires models to adapt to new domains or modalities without sacrificing performance on previously learned tasks. Exper

Local Ai

MindMelody: A Closed-Loop EEG-Driven System for Personalized Music Intervention

arXiv:2605.01235v1 Announce Type: cross Abstract: Driven by the escalating global burden of mental health conditions, music-based interventions have attracted significant attention as a non-invasive,

local-aiarxiv-cs-ai

Ortho-Hydra: Orthogonalized Experts for DiT LoRA

arXiv:2605.03252v1 Announce Type: cross Abstract: LoRA fine-tuning of diffusion transformers (DiT) on multi-style data suffers from style bleed: a single low-rank residual cannot represent several dis

Personalized Digital Health Modeling with Adaptive Support Users

arXiv:2605.02004v1 Announce Type: new Abstract: Personalized models are essential in digital health because individuals exhibit substantial physiological and behavioral heterogeneity. Yet personalizat

applicationsarxiv-cs-ai

PRISM-CTG: A Foundation Model for Cardiotocography Analysis with Multi-View SSL

arXiv:2605.02917v1 Announce Type: new Abstract: Supervised deep learning models for automated CTG analysis are typically constrained by narrowly curated labelled datasets and limited patient cohorts,

tutorialsarxiv-cs-lg

Local Ai

Refining Compositional Diffusion for Reliable Long-Horizon Planning

arXiv:2605.03075v1 Announce Type: cross Abstract: Compositional diffusion planning generates long-horizon trajectories by stitching together overlapping short-horizon segments through score compositio

local-aiarxiv-cs-lg

Reproducing Complex Set-Compositional Information Retrieval

model-releasesarxiv-cs-cl

arXiv:2605.03824v1 Announce Type: new Abstract: Complex information needs may involve set-compositional queries using conjunction, disjunction, and exclusion, yet it remains unclear whether current re

RFPrompt: Prompt-Based Expert Adaptation of the Large Wireless Model for Modulation Classification

arXiv:2605.03279v1 Announce Type: new Abstract: Automatic modulation classification (AMC) in real-world deployments demands robustness to distribution shifts arising from hardware impairments, unseen

Stream-R1: Reliability-Perplexity Aware Reward Distillation for Streaming Video Generation

arXiv:2605.03849v1 Announce Type: new Abstract: Distillation-based acceleration has become foundational for making autoregressive streaming video diffusion models practical, with distribution matching

safetyarxiv-cs-cv

TeamUp: Semantic Project Matching and Team Formation for Learning at Scale

arXiv:2605.03237v1 Announce Type: cross Abstract: Project-based learning improves student engagement and learning outcomes, yet allocating students to appropriately challenging projects while forming

safetyarxiv-cs-cl

Text-Conditional JEPA for Learning Semantically Rich Visual Representations

arXiv:2605.03245v1 Announce Type: cross Abstract: Image-based Joint-Embedding Predictive Architecture (I-JEPA) offers a promising approach to visual self-supervised learning through masked feature pre

Unified Multimodal Visual Tracking with Dual Mixture-of-Experts

arXiv:2605.03716v1 Announce Type: new Abstract: Multimodal visual object tracking can be divided into to several kinds of tasks (e.g. RGB and RGB+X tracking), based on the input modality. Existing met

Action Agent: Agentic Video Generation Meets Flow-Constrained Diffusion

model-releasesarxiv-cs-ro

arXiv:2605.01477v1 Announce Type: new Abstract: We present Action Agent, a two-stage framework that unifies agentic navigation video generation with flow-constrained diffusion control for multi-embodi

Activation Compression in LLMs: Theoretical Analysis and Efficient Algorithm

arXiv:2605.01255v1 Announce Type: new Abstract: Training large language models (LLMs) is highly memory-intensive, as training must store not only weights and optimizer states but also intermediate act

Adaptive Pluralistic Alignment: A pipeline for dynamic artificial democracy

arXiv:2605.01642v1 Announce Type: new Abstract: Prevailing alignment methods target a fixed set of preferences and therefore risk forcing value lock-in as societal norms evolve over time. We introduce

safetyarxiv-cs-lg

Adaptive Texture-aware Masking for Self-Supervised Learning in 3D Dental CBCT Analysis

arXiv:2605.01741v1 Announce Type: new Abstract: Cone Beam Computed Tomography (CBCT) is pivotal for 3D diagnostic imaging in dentistry. However, the development of robust AI models for volumetric anal

An ALE-Consistent Graph Neural Operator-Transformer Framework for Fluid-Structure Interaction

arXiv:2605.00937v1 Announce Type: cross Abstract: We propose an arbitrary Lagrangian-Eulerian (ALE)-consistent machine learning framework for long-term fluid-structure interaction (FSI) prediction on

Automatic Correction of Writing Anomalies in Hausa Texts

arXiv:2506.03820v2 Announce Type: replace Abstract: Hausa texts are often characterized by writing anomalies, such as incorrect character substitutions and spacing errors, which sometimes hinder natur

researcharxiv-cs-cl