Search: “pretraining”

Attention-based multiple instance learning for predominant growth pattern prediction in lung adenocarcinoma wsi using foundation models

arXiv:2604.21530v1 Announce Type: cross Abstract: Lung adenocarcinoma (LUAD) grading depends on accurately identifying growth patterns, which are indicators of prognosis and can influence treatment de

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CHRep: Cross-modal Histology Representation and Post-hoc Calibration for Spatial Gene Expression Prediction

DGX agent

arXiv:2604.21573v1 Announce Type: new Abstract: Spatial transcriptomics (ST) enables spatially resolved gene profiling but remains expensive and low-throughput, limiting large-cohort studies and routi

safetyarxiv-cs-cv

24 Apr 2026

Explainable Disentangled Representation Learning for Generalizable Authorship Attribution in the Era of Generative AI

arXiv:2604.21300v1 Announce Type: new Abstract: Learning robust representations of authorial style is crucial for authorship attribution and AI-generated text detection. However, existing methods ofte

tutorialsarxiv-cs-cl

Frequency-Forcing: From Scaling-as-Time to Soft Frequency Guidance

arXiv:2604.20902v1 Announce Type: cross Abstract: While standard flow-matching models transport noise to data uniformly, incorporating an explicit generation order - specifically, establishing coarse,

Generalizing Numerical Reasoning in Table Data through Operation Sketches and Self-Supervised Learning

model-releasesarxiv-cs-ai

arXiv:2604.21495v1 Announce Type: cross Abstract: Numerical reasoning over expert-domain tables often exhibits high in-domain accuracy but limited robustness to domain shift. Models trained with super

How Much Is One Recurrence Worth? Iso-Depth Scaling Laws for Looped Language Models

arXiv:2604.21106v1 Announce Type: cross Abstract: We measure how much one extra recurrence is worth to a looped (depth-recurrent) language model, in equivalent unique parameters. From an iso-depth swe

researcharxiv-cs-cl

Applications

HypEHR: Hyperbolic Modeling of Electronic Health Records for Efficient Question Answering

arXiv:2604.21027v1 Announce Type: new Abstract: Electronic health record (EHR) question answering is often handled by LLM-based pipelines that are costly to deploy and do not explicitly leverage the h

applicationsarxiv-cs-ai

LatRef-Diff: Latent and Reference-Guided Diffusion for Facial Attribute Editing and Style Manipulation

arXiv:2604.21279v1 Announce Type: new Abstract: Facial attribute editing and style manipulation are crucial for applications like virtual avatars and photo editing. However, achieving precise control

Preserving Knowledge in Large Language Model with Model-Agnostic Self-Decompression

arXiv:2406.11354v3 Announce Type: replace-cross Abstract: Humans can retain old knowledge while learning new information, but Large Language Models (LLMs) often suffer from catastrophic forgetting whe

Probably Approximately Consensus: On the Learning Theory of Finding Common Ground

arXiv:2604.21811v1 Announce Type: cross Abstract: A primary goal of online deliberation platforms is to identify ideas that are broadly agreeable to a community of users through their expressed prefer

Prototype-Based Test-Time Adaptation of Vision-Language Models

arXiv:2604.21360v1 Announce Type: new Abstract: Test-time adaptation (TTA) has emerged as a promising paradigm for vision-language models (VLMs) to bridge the distribution gap between pre-training and

Replay-buffer engineering for noise-robust quantum circuit optimization

arXiv:2604.21863v1 Announce Type: cross Abstract: Deep reinforcement learning (RL) for quantum circuit optimization faces three fundamental bottlenecks: replay buffers that ignore the reliability of t

Revealing Geography-Driven Signals in Zone-Level Claim Frequency Models: An Empirical Study using Environmental and Visual Predictors

model-releasesarxiv-cs-lg

arXiv:2604.21893v1 Announce Type: cross Abstract: Geographic context is often consider relevant to motor insurance risk, yet public actuarial datasets provide limited location identifiers, constrainin

Sculpt4D: Generating 4D Shapes via Sparse-Attention Diffusion Transformers

arXiv:2604.21592v1 Announce Type: new Abstract: Recent breakthroughs in 3D generative modeling have yielded remarkable progress in static shape synthesis, yet high-fidelity dynamic 4D generation remai

SemEval-2026 Task 4: Narrative Story Similarity and Narrative Representation Learning

arXiv:2604.21782v1 Announce Type: new Abstract: We present the shared task on narrative similarity and narrative representation learning - NSNRL (pronounced 'nass-na-rel'). The task operationalizes na

researcharxiv-cs-cl

StyleID: A Perception-Aware Dataset and Metric for Stylization-Agnostic Facial Identity Recognition

arXiv:2604.21689v1 Announce Type: cross Abstract: Creative face stylization aims to render portraits in diverse visual idioms such as cartoons, sketches, and paintings while retaining recognizable ide

StyleVAR: Controllable Image Style Transfer via Visual Autoregressive Modeling

arXiv:2604.21052v1 Announce Type: cross Abstract: We build on the Visual Autoregressive Modeling (VAR) framework and formulate style transfer as conditional discrete sequence modeling in a learned lat

safetyarxiv-cs-ai

Task-specific Subnetwork Discovery in Reinforcement Learning for Autonomous Underwater Navigation

arXiv:2604.21640v1 Announce Type: cross Abstract: Autonomous underwater vehicles are required to perform multiple tasks adaptively and in an explainable manner under dynamic, uncertain conditions and

safetyarxiv-cs-ai

Teacher-Guided Routing for Sparse Vision Mixture-of-Experts

arXiv:2604.21330v1 Announce Type: new Abstract: Recent progress in deep learning has been driven by increasingly large-scale models, but the resulting computational cost has become a critical bottlene

local-aiarxiv-cs-cv

The Recurrent Transformer: Greater Effective Depth and Efficient Decoding

model-releasesarxiv-cs-lg

arXiv:2604.21215v1 Announce Type: new Abstract: Transformers process tokens in parallel but are temporally shallow: at position t, each layer attends to key-value pairs computed based on the previous

Validating a Deep Learning Algorithm to Identify Patients with Glaucoma using Systemic Electronic Health Records

arXiv:2604.20921v1 Announce Type: new Abstract: We evaluated whether a glaucoma risk assessment (GRA) model trained on All of Us national data can identify patients at high probability of glaucoma usi

researcharxiv-cs-lg

A novel attention mechanism for noise-adaptive and robust segmentation of microtubules in microscopy images

arXiv:2507.07800v3 Announce Type: replace-cross Abstract: Segmenting cytoskeletal filaments in microscopy images is essential for studying their roles in cellular processes. However, this task is high

A Vision-Language-Action Model for Adaptive Ultrasound-Guided Needle Insertion and Needle Tracking

model-releasesarxiv-cs-ai

arXiv:2604.20347v1 Announce Type: cross Abstract: Ultrasound (US)-guided needle insertion is a critical yet challenging procedure due to dynamic imaging conditions and difficulties in needle visualiza

Applications

Amodal SAM: A Unified Amodal Segmentation Framework with Generalization

arXiv:2604.20748v1 Announce Type: new Abstract: Amodal segmentation is a challenging task that aims to predict the complete geometric shape of objects, including their occluded regions. Although exist

applicationsarxiv-cs-cv

CoRe: Joint Optimization with Contrastive Learning for Medical Image Registration

arXiv:2603.23694v2 Announce Type: replace Abstract: Medical image registration is a fundamental task in medical image analysis, enabling the alignment of images from different modalities or time point

safetyarxiv-cs-cv

Degrees, Levels, and Profiles of Contextuality

arXiv:2603.26692v3 Announce Type: replace-cross Abstract: We introduce a new notion, that of a contextuality profile of a system of random variables. Rather than characterizing a system's contextualit

Diagnosing Urban Street Vitality via a Visual-Semantic and Spatiotemporal Framework for Street-Level Economics

arXiv:2604.19798v1 Announce Type: cross Abstract: Micro-scale street-level economic assessment is fundamental for precision spatial resource allocation. While Street View Imagery (SVI) advances urban

FA-Seg: A Fast and Accurate Diffusion-Based Method for Open-Vocabulary Segmentation

arXiv:2506.23323v5 Announce Type: replace Abstract: Open-vocabulary semantic segmentation (OVSS) aims to segment objects from arbitrary text categories without requiring densely annotated datasets. Al

local-aiarxiv-cs-cv

Forecasting Individual NetFlows using a Predictive Masked Graph Autoencoder

arXiv:2604.20483v1 Announce Type: cross Abstract: In this paper, we propose a proof-of-concept Graph Neural Network model that can successfully predict network flow-level traffic (NetFlow) by accurate

researcharxiv-cs-lg

From Ideal to Real: Stable Video Object Removal under Imperfect Conditions

arXiv:2603.09283v2 Announce Type: replace Abstract: Removing objects from videos remains difficult in the presence of real-world imperfections such as shadows, abrupt motion, and defective masks. Exis

tutorialsarxiv-cs-cv

Integrated AI Nodule Detection and Diagnosis for Lung Cancer Screening Beyond Size and Growth-Based Standards Compared with Radiologists and Leading Models

arXiv:2512.00281v2 Announce Type: replace Abstract: Early detection of malignant lung nodules remains limited by reliance on size- and growth-based screening criteria, which can delay diagnosis. We pr

Lucky High Dynamic Range Smartphone Imaging

arXiv:2604.19976v1 Announce Type: new Abstract: While the human eye can perceive an impressive twenty stops of dynamic range, smartphone camera sensors remain limited to about twelve stops despite dec

Model Internal Sleuthing: Finding Lexical Identity and Inflectional Features in Modern Language Models

arXiv:2506.02132v5 Announce Type: replace Abstract: Large transformer-based language models dominate modern NLP, yet our understanding of how they encode linguistic information relies primarily on stu

researcharxiv-cs-cl

Multi-Objective Reinforcement Learning for Generating Covalent Inhibitor Candidates

arXiv:2604.20019v1 Announce Type: new Abstract: Rational design of covalent inhibitors requires simultaneously optimizing multiple properties, such as binding affinity, target selectivity, or electrop

safetyarxiv-cs-lg

Physics-Conditioned Synthesis of Internal Ice-Layer Thickness for Incomplete Layer Traces

arXiv:2604.20783v1 Announce Type: new Abstract: Internal ice layers imaged by radar provide key evidence of snow accumulation and ice dynamics, but radar-derived layer boundary observations are often

tutorialsarxiv-cs-lg

Semi-Supervised Flow Matching for Mosaiced and Panchromatic Fusion Imaging

arXiv:2604.20128v1 Announce Type: new Abstract: Fusing a low resolution (LR) mosaiced hyperspectral image (HSI) with a high resolution (HR) panchromatic (PAN) image offers a promising avenue for video

SwiftRepertoire: Few-Shot Immune-Signature Synthesis via Dynamic Kernel Codes

arXiv:2602.01051v4 Announce Type: replace Abstract: Repertoire-level analysis of T cell receptors offers a biologically grounded signal for disease detection and immune monitoring, yet practical deplo

researcharxiv-cs-lg

Applications

VAN-AD: Visual Masked Autoencoder with Normalizing Flow For Time Series Anomaly Detection

arXiv:2603.26842v2 Announce Type: replace-cross Abstract: Time series anomaly detection (TSAD) is essential for maintaining the reliability and security of IoT-enabled service systems. Existing method

applicationsarxiv-cs-ai

Video-ToC: Video Tree-of-Cue Reasoning

arXiv:2604.20473v1 Announce Type: new Abstract: Existing Video Large Language Models (Video LLMs) struggle with complex video understanding, exhibiting limited reasoning capabilities and potential hal

A Proxy Consistency Loss for Grounded Fusion of Earth Observation and Location Encoders

arXiv:2604.18881v1 Announce Type: cross Abstract: Supervised learning with Earth observation inputs is often limited by the sparsity of high-quality labeled or in-situ measured data to use as training

tutorialsarxiv-cs-ai

Agents

A Survey on MLLM-based Visually Rich Document Understanding: Methods, Challenges, and Emerging Trends

arXiv:2507.09861v2 Announce Type: replace-cross Abstract: Visually Rich Document Understanding (VRDU) has become a pivotal area of research, driven by the need to automatically interpret documents tha

agentsarxiv-cs-ai

AlignedCut: Visual Concepts Discovery on Brain-Guided Universal Feature Space

arXiv:2406.18344v2 Announce Type: replace Abstract: We study the intriguing connection between visual data, deep networks, and the brain. Our method creates a universal channel alignment by using brai

safetyarxiv-cs-cv

Attend what matters: Leveraging vision foundational models for breast cancer classification using mammograms

arXiv:2604.19350v1 Announce Type: new Abstract: Vision Transformers (exttt{ViT}) have become the architecture of choice for many computer vision tasks, yet their performance in computer-aided diagnost

local-aiarxiv-cs-cv

CAHAL: Clinically Applicable resolution enHAncement for Low-resolution MRI scans

arXiv:2604.18781v1 Announce Type: new Abstract: Large-scale automated morphometric analysis of brain MRI is limited by the thick-slice, anisotropic acquisitions prevalent in routine clinical practice.

safetyarxiv-cs-cv

Detoxification for LLM: From Dataset Itself

arXiv:2604.19124v1 Announce Type: new Abstract: Existing detoxification methods for large language models mainly focus on post-training stage or inference time, while few tackle the source of toxicity

local-aiarxiv-cs-cl

Easy Samples Are All You Need: Self-Evolving LLMs via Data-Efficient Reinforcement Learning

arXiv:2604.18639v1 Announce Type: cross Abstract: Previous LLMs-based RL studies typically follow either supervised learning with high annotation costs, or unsupervised paradigms using voting or entro

EfficientPENet: Real-Time Depth Completion from Sparse LiDAR via Lightweight Multi-Modal Fusion

arXiv:2604.18790v1 Announce Type: new Abstract: Depth completion from sparse LiDAR measurements and corresponding RGB images is a prerequisite for accurate 3D perception in robotic systems. Existing m

ExpertGen: Scalable Sim-to-Real Expert Policy Learning from Imperfect Behavior Priors

arXiv:2603.15956v2 Announce Type: replace-cross Abstract: Learning generalizable and robust behavior cloning policies requires large volumes of high-quality robotics data. While human demonstrations (

safetyarxiv-cs-ai