Search: “pretraining”

AI Outperforms Humans in Personalized Image Aesthetics Assessment via LLM-Based Interviews and Semantic Feature Extraction

arXiv:2605.14761v1 Announce Type: new Abstract: Accurately predicting individual aesthetic evaluation for images is a fundamental challenge for AI. Various deep learning (DL)-based models have been pr

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AnchorRoute: Human Motion Synthesis with Interval-Routed Sparse Contro

DGX agent

arXiv:2605.14716v1 Announce Type: cross Abstract: Sparse anchors provide a compact interface for human motion authoring: users specify a few root positions, planar trajectory samples, or body-point ta

model-releasesarxiv-cs-cv

15 May 2026

Architecture-Aware Explanation Auditing for Industrial Visual Inspection

arXiv:2605.14255v1 Announce Type: cross Abstract: Industrial visual inspection systems increasingly rely on deep classifiers whose heatmap explanations may appear visually plausible while failing to i

Attractor Geometry of Transformer Memory: From Conflict Arbitration to Confident Hallucination

arXiv:2605.05686v2 Announce Type: replace Abstract: Language models draw on two knowledge sources: facts baked into weights (parametric memory, PM) and information in context (working memory, WM). We

AudioMosaic: Contrastive Masked Audio Representation Learning

arXiv:2605.14231v1 Announce Type: cross Abstract: Audio self-supervised learning (SSL) aims to learn general-purpose representations from large-scale unlabeled audio data. While recent advances have b

AutoMoT: A Unified Vision-Language-Action Model with Asynchronous Mixture-of-Transformers for End-to-End Autonomous Driving

arXiv:2603.14851v3 Announce Type: replace Abstract: Integrating vision-language models (VLMs) into end-to-end (E2E) autonomous driving (AD) systems has shown promise in improving scene understanding.

safetyarxiv-cs-cv

ClickRemoval: An Interactive Open-Source Tool for Object Removal in Diffusion Models

arXiv:2605.14461v1 Announce Type: new Abstract: Existing object removal tools often rely on manual masks or text prompts, making precise removal difficult for non-expert users in complex scenes and of

Cognitive-Uncertainty Guided Knowledge Distillation for Accurate Classification of Student Misconceptions

arXiv:2605.14752v1 Announce Type: cross Abstract: Accurately identifying student misconceptions is crucial for personalized education but faces three challenges: (1) data scarcity with long-tail distr

CSI-JEPA: Towards Foundation Representations for Ubiquitous Sensing with Minimal Supervision

arXiv:2605.14171v1 Announce Type: new Abstract: Channel state information (CSI) provides a widely available sensing modality for human and environment perception, but existing CSI sensing models usual

applicationsarxiv-cs-lg

Discovering Physical Directions in Weight Space: Composing Neural PDE Experts

arXiv:2605.14546v1 Announce Type: new Abstract: Recent advances in neural operators have made partial differential equation (PDE) surrogate modeling increasingly scalable and transferable through larg

Agents

DriveCtrl: Conditioned Sim-to-Real Driving Video Generation

arXiv:2605.15116v1 Announce Type: new Abstract: Large-scale labelled driving video data is essential for training autonomous driving systems. Although simulation offers scalable and fully annotated da

agentsarxiv-cs-cv

Eradicating Negative Transfer in Multi-Physics Foundation Models via Sparse Mixture-of-Experts Routing

arXiv:2605.15179v1 Announce Type: cross Abstract: Scaling Scientific Machine Learning (SciML) toward universal foundation models is bottlenecked by negative transfer: the simultaneous co-training of d

HASTE: Training-Free Video Diffusion Acceleration via Head-Wise Adaptive Sparse Attention

arXiv:2605.14513v1 Announce Type: cross Abstract: Diffusion-based video generation has advanced substantially in visual fidelity and temporal coherence, but practical deployment remains limited by the

HDRFace: Rethinking Face Restoration with High-Dimensional Representation

model-releasesarxiv-cs-cv

arXiv:2605.14821v1 Announce Type: new Abstract: Face restoration under complex degradations still remains an ill-posed inverse problem due to severe information loss. Although diffusion models benefit

Head Forcing: Long Autoregressive Video Generation via Head Heterogeneity

arXiv:2605.14487v1 Announce Type: cross Abstract: Autoregressive video diffusion models support real-time synthesis but suffer from error accumulation and context loss over long horizons. We discover

ImmuVis: Hyperconvolutional Foundation Model for Imaging Mass Cytometry

arXiv:2602.04585v2 Announce Type: replace Abstract: We present ImmuVis, a family of efficient foundation models for imaging mass cytometry (IMC), a high-throughput multiplex imaging technology that ha

applicationsarxiv-cs-cv

IPR-1: Interactive Physical Reasoner

arXiv:2511.15407v3 Announce Type: replace Abstract: Humans learn by observing, interacting with environments, and internalizing physics and causality. Here, we aim to ask whether an agent can similarl

KGPFN: Unlocking the Potential of Knowledge Graph Foundation Model via In-Context Learning

arXiv:2605.14907v1 Announce Type: new Abstract: Knowledge graph (KG) foundation models aim to generalize across graphs with unseen entities and relations by learning transferable relational structure.

local-aiarxiv-cs-ai

Language-Induced Priors for Domain Adaptation

arXiv:2605.14301v1 Announce Type: new Abstract: Domain adaptation faces a fundamental paradox in the cold-start regime. When target data is scarce, statistical methods fail to distinguish relevant sou

tutorialsarxiv-cs-lg

LLMs Should Express Uncertainty Explicitly

arXiv:2604.05306v2 Announce Type: replace-cross Abstract: Large language models (LLMs) often produce confident yet incorrect answers, which can lead to risky failures in real-world applications. We st

MD-PNOP: Equation-Recast Neural Operators for Minimal-Data Extrapolation and PDE Solver Acceleration

arXiv:2509.01416v2 Announce Type: replace Abstract: The computational overhead of traditional numerical solvers for partial differential equations (PDEs) remains a critical bottleneck for large-scale

Mini-JEPA Foundation Model Fleet Enables Agentic Hydrologic Intelligence

model-releasesarxiv-cs-cl

arXiv:2605.14120v1 Announce Type: cross Abstract: Geospatial foundation models compress multispectral observations into dense embeddings increasingly used in natural-language environmental reasoning s

NEST: Nested Event Stream Transformer for Sequences of Multisets

arXiv:2602.00520v3 Announce Type: replace Abstract: Event stream data often exhibit hierarchical structure in which multiple events co-occur, resulting in a sequence of multisets (i.e., bags of events

safetyarxiv-cs-lg

Neural Signals Generate Clinical Notes in the Wild

arXiv:2601.22197v3 Announce Type: replace-cross Abstract: Generating clinical reports that summarize abnormal patterns, diagnostic findings, and clinical interpretations from long-term EEG recordings

Predicting Response to Neoadjuvant Chemotherapy in Ovarian Cancer from CT Baseline Using Multi-Loss Deep Learning

arXiv:2605.14991v1 Announce Type: cross Abstract: Ovarian cancer is the most lethal gynecologic malignancy: around 60% of patients are diagnosed at an advanced stage, with an associated 5-year surviva

Reinforcement Learning with Semantic Rewards Enables Low-Resource Language Expansion without Alignment Tax

arXiv:2605.14366v1 Announce Type: new Abstract: Extending large language models (LLMs) to low-resource languages often incurs an 'alignment tax': improvements in the target language come at the cost o

safetyarxiv-cs-cl

Seeing Through the Brain: New Insights from Decoding Visual Stimuli with fMRI

arXiv:2510.16196v2 Announce Type: replace-cross Abstract: Understanding how the brain encodes visual information is a central challenge in neuroscience and machine learning. A promising approach is to

applicationsarxiv-cs-ai

Self-Pruned Key-Value Attention: Learning When to Write by Predicting Future Utility

arXiv:2605.14037v1 Announce Type: cross Abstract: Under modern test-time compute and agentic paradigms, language models process ever-longer sequences. Efficient text generation with transformer archit

local-aiarxiv-cs-cl

SteerSeg: Attention Steering for Reasoning Video Segmentation

arXiv:2605.14908v1 Announce Type: new Abstract: Video reasoning segmentation requires localizing objects across video frames from natural language expressions, often involving spatial reasoning and im

local-aiarxiv-cs-cv

SurF: A Generative Model for Multivariate Irregular Time Series Forecasting

arXiv:2605.14069v1 Announce Type: new Abstract: Irregularly sampled multivariate event streams remain a stubbornly difficult modality for generative modeling: tokenization-based approaches break down

applicationsarxiv-cs-lg

TabClustPFN: A Prior-Fitted Network for Tabular Data Clustering

arXiv:2601.21656v3 Announce Type: replace Abstract: Clustering tabular data is a fundamental yet challenging problem due to heterogeneous feature types, diverse data-generating mechanisms, and the abs

applicationsarxiv-cs-lg

TabPFN-3: Technical Report

arXiv:2605.13986v1 Announce Type: new Abstract: Tabular data underpins most high-value prediction problems in science and industry, and TabPFN has driven the foundation model revolution for this modal

Towards the Next Frontier of LLMs, Training on Private Data: A Cross-Domain Benchmark for Federated Fine-Tuning

arXiv:2605.13936v1 Announce Type: cross Abstract: The recent success of large language models (LLMs) has been largely driven by vast public datasets. However, the next frontier for LLM development lie

V2M-Zero: Zero-Pair Time-Aligned Video-to-Music Generation

arXiv:2603.11042v2 Announce Type: replace-cross Abstract: Generating music that temporally aligns with video events is challenging for existing text-to-music models, which lack fine-grained temporal c

safetyarxiv-cs-ai

Vendor-Conditioned Contrastive Learning for Predicting Organizational Cyber Threat Targets

arXiv:2012.14425v2 Announce Type: replace-cross Abstract: Cyberattacks cause billions of dollars in damage annually, with malicious hackers often sharing exploit code and techniques on underground for

What Do EEG Foundation Models Capture from Human Brain Signals?

arXiv:2605.11410v2 Announce Type: replace Abstract: Clinical electroencephalogram (EEG) analysis rests on a hand-crafted feature catalog refined over decades, e.g., band power, connectivity, complexit

XR-1: Towards Versatile Vision-Language-Action Models via Learning Unified Vision-Motion Representations

arXiv:2511.02776v2 Announce Type: replace Abstract: Recent progress in large-scale robotic datasets and vision-language models (VLMs) has advanced research on vision-language-action (VLA) models. Howe

safetyarxiv-cs-ro

Asymmetric Flow Models

arXiv:2605.12964v1 Announce Type: new Abstract: Flow-based generation in high-dimensional spaces is difficult because velocity prediction requires modeling high-dimensional noise, even when data has s

ConRetroBert: EMA Stabilized Dual Encoders for Template-Based Single-Step Retrosynthesis

arXiv:2605.12736v1 Announce Type: new Abstract: Template based single step retrosynthesis predicts reactants by selecting and applying an explicit reaction template, making each prediction traceable t

CoRe-Gen: Robust Spectrum-to-Structure Generation under Imperfect Fingerprint Conditions

arXiv:2605.12980v1 Announce Type: cross Abstract: Molecular structure elucidation from tandem mass spectra (MS/MS) remains challenging, particularly for de novo generation beyond database coverage. A

Correcting Influence: Unboxing LLM Outputs with Orthogonal Latent Spaces

arXiv:2605.12809v1 Announce Type: cross Abstract: A critical step for reliable large language models (LLMs) use in healthcare is to attribute predictions to their training data, akin to a medical case

Decoupled and Divergence-Conditioned Prompt for Multi-domain Dynamic Graph Foundation Models

arXiv:2605.13540v1 Announce Type: cross Abstract: Dynamic graphs are ubiquitous in real-world systems, and building generalizable dynamic Graph Foundation Models has become a frontier in graph learnin

applicationsarxiv-cs-ai

Deep Delta Learning

arXiv:2601.00417v3 Announce Type: replace-cross Abstract: Transformer residual streams evolve by additive accumulation: each layer appends a feature update to a shared hidden state, but has no direct

Discrete Stochastic Localization for Non-autoregressive Generation

arXiv:2605.12836v1 Announce Type: new Abstract: Continuous diffusion is a natural framework for non-autoregressive generation but has generally lagged behind masked discrete diffusion models (MDMs) on

researcharxiv-cs-lg

Does Engram Do Memory Retrieval in Autoregressive Image Generation?

arXiv:2605.13179v1 Announce Type: new Abstract: The Engram module -- a hash-keyed, O(1) associative memory injected into Transformer layers -- was recently shown to improve large language model pretra

local-aiarxiv-cs-cv

Domain Adaptation of Large Language Models for Polymer-Composite Additive Manufacturing Using Retrieval-Augmented Generation and Fine-Tuning

arXiv:2605.12516v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) often struggle to generate reliable responses in specialized engineering domains due to limited domain gr

Dynamical Predictive Modelling of Cardiovascular Disease Progression Post-Myocardial Infarction via ECG-Trained Artificial Intelligence Model

arXiv:2605.13568v1 Announce Type: cross Abstract: Myocardial infarction (MI) is a leading cause of death, and its adverse outcomes are urgent to predict. Yet ECG-based prognostic models underperform b

Early Semantic Grounding in Image Editing Models for Zero-Shot Referring Image Segmentation

arXiv:2605.13122v1 Announce Type: new Abstract: Instruction-based image editing (IIE) models have recently demonstrated strong capability in modifying specific image regions according to natural langu