Search: “models”

EvoBrain: Continual Learning of EEG Foundation Models Across Heterogeneous BCI Tasks

arXiv:2606.01767v1 Announce Type: new Abstract: Electroencephalography (EEG) is the cornerstone of non-invasive brain-computer interfaces (BCIs), yet conventional decoding relies on fragmented, task-s

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Planktonzilla: Multimodal dataset and models for understanding plankton ecosystems

DGX agent

arXiv:2606.00080v1 Announce Type: cross Abstract: Marine plankton underpin aquatic food webs and play a key role in global CO2 sequestration, making reliable species identification critical for unders

researcharxiv-cs-ai

2 Jun 2026

PolarMem: A Training-Free Polarized Latent Graph Memory for Verifiable Vision-Language Models

arXiv:2602.00415v2 Announce Type: replace Abstract: Memory is not merely a storage mechanism for intelligent systems, but a structure for organizing evidence and constraining belief. This is especiall

Quantum Tunneling-Aware Machine Learning: Physics-Derived Noise Models for Robust Deployment

arXiv:2606.00741v1 Announce Type: cross Abstract: Transistor scaling is approaching a quantum-mechanical limit, as thin gate oxides induce electron leakage through quantum tunneling. Unlike convention

Thinking in Blender: Staged Executable Inverse Graphics with Vision-Language Models

arXiv:2606.02580v1 Announce Type: new Abstract: Inverse graphics is a longstanding and highly underconstrained problem that seeks to reconstruct images as editable 3D scenes which can be rendered, rel

agentsarxiv-cs-cv

When Meaning Travels: A Granular Lens on Hybrid-MoE's Role in Idiomatic Understanding for Language Models

arXiv:2606.01671v1 Announce Type: new Abstract: In the contemporary epoch of multilingual education, learning idioms provides a fascinating gateway towards creativity, cultural values, historical cont

safetyarxiv-cs-cl

NumLeak: Public Numeric Benchmarks as Latent Labels in Foundation Models

arXiv:2605.30393v1 Announce Type: cross Abstract: Public numeric benchmarks appear in pretraining, so an evaluation that conditions on a date may be measuring memorized recall rather than out-of-sampl

applicationsarxiv-cs-ai

1 Jun 2026

Hardware

SubsurfaceGen: Procedural Generation of Field-Scale Earth Models and Seismic Data

arXiv:2605.30541v1 Announce Type: new Abstract: Full waveform inversion (FWI) is the gold standard for subsurface imaging, with applications from carbon sequestration to energy and mineral exploration

hardwarearxiv-cs-lg

1 Jun 2026

Comparing Post-Hoc Explainable AI Methods for Interpreting Black-Box EEG Models in Depression Detection

arXiv:2605.28977v1 Announce Type: cross Abstract: Recent advances in deep learning have enabled increasingly accurate electroencephalography (EEG)-based classification of Major Depressive Disorder (MD

Conf-Gen: Conformal Uncertainty Quantification for Generative Models

arXiv:2605.28920v1 Announce Type: cross Abstract: Conformal prediction (CP) and its extension, conformal risk control (CRC), are established frameworks for quantifying uncertainty in supervised machin

RewardFlow: Topology-Aware Reward Propagation on State Graphs for Agentic RL with Large Language Models

arXiv:2603.18859v2 Announce Type: replace Abstract: Reinforcement learning (RL) shows promise for enhancing LLM agentic reasoning, yet sparse terminal rewards hinder fine-grained optimization. Process

agentsarxiv-cs-ai

Local Ai

Towards Localized and Disentangled Knowledge Editing for Multimodal Large Language Models

arXiv:2605.29826v1 Announce Type: cross Abstract: Existing methods in Multimodal Knowledge Editing (MKE) have advanced the ability to correct outdated or inaccurate knowledge in Multimodal Large Langu

local-aiarxiv-cs-ai

A Multiscale Kinetic Framework for Image Segmentation: From Particle Systems to Continuum Models

arXiv:2605.28619v1 Announce Type: new Abstract: In this work, we present a multiscale kinetic framework for consensus-based image segmentation. By interpreting an image as a system of interacting part

A Systematic Evaluation of Retrieval-Augmented Generation and Language Models for Space Operations

arXiv:2605.27444v1 Announce Type: cross Abstract: The rapid expansion of space activities has led to an unprecedented accumulation of technical documentation, operational guidelines, and scientific li

Diffusion Large Language Models for Visual Speech Recognition

arXiv:2605.28456v1 Announce Type: new Abstract: Existing Visual Speech Recognition (VSR) systems commonly rely on left-to-right autoregressive decoding, which can force premature decisions on visually

safetyarxiv-cs-ai

Fine-Tuning Vision-Language Models for Understanding Current Damage and Scoring Priority with Quality Guard Agent

arXiv:2605.27452v1 Announce Type: new Abstract: Bridge inspection in Japan requires mandatory visual assessments every five years, yet qualitative damage ratings (levels a-e) assigned by different eng

agentsarxiv-cs-cv

Large Language Models as Automatic Annotators and Annotation Adjudicators for Fine-Grained Opinion Analysis

arXiv:2601.16800v3 Announce Type: replace Abstract: Fine-grained opinion analysis of text provides a detailed understanding of expressed sentiments, including the addressed entity. Although this level

agentsarxiv-cs-cl

Skillful high-resolution weather forecasting independent of physical models

arXiv:2605.28153v1 Announce Type: cross Abstract: Accurate and timely weather forecasts are critical for high-impact decisions in modern society. Machine-learning-based weather prediction is emerging

researcharxiv-cs-lg

Stage-wise Distortion-Perception Traversal in Zero-shot Inverse Problems with Diffusion Models

arXiv:2605.28711v1 Announce Type: new Abstract: The distortion-perception (D-P) tradeoff is a fundamental phenomenon of Bayesian inverse problems, which characterizes the inherent tension between dist

Tutorials

Personalized Generative Models for Contextual Debiasing

arXiv:2605.26353v1 Announce Type: cross Abstract: Different visual patterns appear with different frequencies in the world: e.g., beach balls appear on sand more often than they do on a road. These st

tutorialsarxiv-cs-ai

27 May 2026

Self-Cascaded Diffusion Models for Arbitrary-Scale Image Super-Resolution

arXiv:2506.07813v2 Announce Type: replace-cross Abstract: Arbitrary-scale image super-resolution aims to upsample images to any desired resolution, offering greater flexibility than traditional fixed-

27 May 2026

The Need for an External Observer Formalizing the Sufficiency Gap: A Mathematical Extension of Mixture Identifiability and Contextual Grounding in Sequence Models

arXiv:2605.26711v1 Announce Type: new Abstract: We construct a binary mixed-regime process with one deterministic textual regime and one random regime governed by an unobserved latent state. Even an i

agentsarxiv-cs-cl

27 May 2026

Automated Detection and Classification of Delusion-related Content in Naturalistic Audio Diaries Using Multi-Agent Language Models

arXiv:2605.24755v1 Announce Type: new Abstract: Speech monologues recorded in naturalistic settings provide opportunities to characterize mental illness phenomenology and detect symptom exacerbation.

agentsarxiv-cs-ai

26 May 2026

MedMamba: Multi-View State Space Models with Adaptive Graph Learning for Medical Time Series Classification

arXiv:2605.24961v1 Announce Type: new Abstract: Medical time series are central to healthcare, enabling continuous monitoring and supporting timely clinical decisions. Despite recent progress, existin

26 May 2026

Private Adaptive Covariance Estimation via Gaussian Graphical Models

arXiv:2605.24295v1 Announce Type: new Abstract: We propose PACE-GGM, a data-adaptive differentially private method for covariance estimation that concentrates its privacy budget on the most informativ

26 May 2026

Tutorials

An Open-Source Training Dataset for Foundation Models for Black-box Optimization

arXiv:2605.23417v1 Announce Type: new Abstract: Most black-box optimization methods require extensive hyperparameter tuning, often limiting their ability to generalize across different optimization do

tutorialsarxiv-cs-lg

25 May 2026

Debiased Negative Mining Improves Out-of-distribution Detection with Pre-trained Vision-Language Models

arXiv:2605.23797v1 Announce Type: cross Abstract: Aiming at identifying unexpected inputs from unknown classes, out-of-distribution (OOD) detection has emerged as a pivotal approach to enhancing the r

safetyarxiv-cs-cv

25 May 2026

Flow Mismatching: Unsupervised Anomaly Detection via Velocity Discrepancies in Flow Matching Models

arXiv:2605.23070v1 Announce Type: new Abstract: We propose Flow Mismatching, an unsupervised anomaly detection method that deliberately avoids reconstruction-based paradigms. Instead, we treat flow ma

25 May 2026

A Human-in-the-Loop Framework for Efficient Prompt Selection in Microscopy Vision-Language Models

arXiv:2605.20495v1 Announce Type: new Abstract: Deep-learning pipelines for microscopy image classification often require expensive, labor- and time-intensive expert annotation to produce high-quality

Activation-Free Backbones for Image Recognition: Polynomial Alternatives within MetaFormer-Style Vision Models

arXiv:2605.20839v1 Announce Type: new Abstract: Modern vision backbones treat pointwise activations (e.g., ReLU, GELU) and exponential softmax as essential sources of nonlinearity, but we demonstrate

Large Language Models Unpack Complex Political Opinions through Target-Stance Extraction

arXiv:2603.23531v2 Announce Type: replace Abstract: Political polarization emerges from a complex interplay of beliefs about policies, figures, and issues. However, most computational analyses reduce

Leveraging Large Language Models for Sentiment Analysis: Multi-Modal Analysis of Decentraland's MANA Token

arXiv:2605.20192v1 Announce Type: new Abstract: Decentraland, a decentralized virtual reality platform operating within the expanding Metaverse ecosystem, utilizes its native MANA token to facilitate

Hardware

OlmoEarth v1.1: A more efficient family of OlmoEarth models

arXiv:2605.20804v1 Announce Type: new Abstract: We present a set of improvements to the OlmoEarth family. These improvements allow us to cut compute costs during training (1.7 imes reduction in GPU ho

hardwarearxiv-cs-cv

Tracing the ongoing emergence of human-like reasoning in Large Language Models

arXiv:2605.21299v1 Announce Type: new Abstract: Humans effortlessly go beyond literal meanings: If you mow the lawn, I will give you fifty dollars, is typically understood as implying that the speaker

Can Large Language Models Revolutionize Survey Research? Experiments with Disaster Preparedness Responses

arXiv:2605.19229v1 Announce Type: new Abstract: Survey research faces mounting structural challenges: declining response rates, sample bias, block-wise missingness among at-risk respondents, and AI-as

safetyarxiv-cs-ai

20 May 2026

TabQL: In-Context Q-Learning with Tabular Foundation Models

arXiv:2605.18979v1 Announce Type: new Abstract: We propose Tabular Q-Learning (TabQL), a reinforcement learning framework that replaces the conventional parametric Q-network in Deep Q-Learning (DQN) w

researcharxiv-cs-lg

20 May 2026

Towards Family-Grouped Hierarchical Federated Learning on Sub-5KB Models: A Feasibility Study of Privacy-Preserving ECG Monitoring for Ultra-Resource-Constrained Wearables

arXiv:2605.18862v1 Announce Type: cross Abstract: Cardiovascular disease remains the leading cause of death worldwide, and early detection of arrhythmias through continuous ECG monitoring on wearable

20 May 2026

Face inpainting with Identity Preserving Latent Diffusion Models

arXiv:2605.16696v1 Announce Type: new Abstract: Face inpainting techniques recover missing or occluded facial regions in a visually realistic manner, but preserving the identity in the final output re

safetyarxiv-cs-cv

Isolating Nonlinear Independent Sources in fMRI with eta-TCVAE Models

arXiv:2605.16708v1 Announce Type: new Abstract: Learning meaningful latent representations from nonlinear fMRI data remains a fundamental challenge in neuroimaging analysis. Traditional independent co

Isotonic Survival Regression: Calibrated Survival Distributions from Deep Cox Models

arXiv:2605.16571v1 Announce Type: cross Abstract: Time-to-event data is widespread across the life sciences and engineering, but it is typically encountered together with censoring, which complicates

applicationsarxiv-cs-ai

Tutorials

Joint Enhancement and Classification using Coupled Diffusion Models of Signals and Logits

arXiv:2602.15405v2 Announce Type: replace Abstract: Robust classification in noisy environments remains a fundamental challenge in machine learning. Standard approaches typically treat signal enhancem

tutorialsarxiv-cs-lg

Position: Age Estimation Models Do Not Process Biometric Data

arXiv:2605.17347v1 Announce Type: cross Abstract: When a neural network estimates someone's age from a photograph, does it process biometric data? The answer depends on whether identity-discriminative

safetyarxiv-cs-cv

Rethinking 1-bit Optimization Leveraging Pre-trained Large Language Models

arXiv:2508.06974v2 Announce Type: replace Abstract: 1-bit LLM quantization offers significant advantages in reducing storage and computational costs. However, existing methods typically train 1-bit LL

Hardware

Spherical Harmonic Optimal Transport: Application to Climate Models Comparisons

arXiv:2605.18389v1 Announce Type: new Abstract: Optimal transport provides a powerful framework for comparing measures while respecting the geometry of their support, but comes with an expensive compu

hardwarearxiv-cs-lg

Artificial Aphasias in Lesioned Language Models

arXiv:2605.16222v1 Announce Type: new Abstract: Aphasias, selective language impairments which can arise from brain damage, reveal the functional organization of human language by providing causal lin

CTF4Nuclear: Common Task Framework for Nuclear Fission and Fusion Models

arXiv:2605.15549v1 Announce Type: cross Abstract: The demand for clean energy is ever increasing, with new nuclear technologies presenting a complementary solution to renewable energies. However, desi

safetyarxiv-cs-ai

Detecting Heel Strike and toe off Events Using Kinematic Methods and LSTM Models

arXiv:2503.00794v2 Announce Type: replace Abstract: Accurate gait event detection is crucial for gait analysis, rehabilitation, and assistive technology, particularly in exoskeleton control, where pre

safetyarxiv-cs-ro

Entropy-Based Characterisation of the Polarised Regime in Latent Variable Models

arXiv:2605.15965v1 Announce Type: new Abstract: Variational Autoencoders (VAEs) often exhibit a polarised regime in which latent variables separate into active, passive, and mixed subsets. Existing cr

researcharxiv-cs-lg