Search: “framework”

Graph-Guided Universum Learning in Generalized Eigenvalue Proximal SVMs for Alzheimer's Disease Classification

arXiv:2606.04699v1 Announce Type: cross Abstract: Early and accurate detection of Alzheimer's disease (AD) is important for timely intervention and disease management. Generalized Eigenvalue Proximal

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Impostor: An Agent-Curated Benchmark for Realistic AIGC Manipulation Localization

DGX agent

arXiv:2606.04545v1 Announce Type: new Abstract: Recent advances in generative image editing have improved the realism and controllability of localized image manipulation, raising new challenges for im

model-releasesarxiv-cs-cv

4 Jun 2026

LaVIDE: Language-Prompted Satellite Change Detection via Map-Image Alignment

arXiv:2411.19758v2 Announce Type: replace-cross Abstract: Remote sensing change detection based on a map reference and an up-to-date image boosts timely observation of the Earth's surface when earlier

Listening to the Workforce: Measuring Construction Worker Safety Attitudes from Social Media Discourse Using LLMs

arXiv:2606.04450v1 Announce Type: new Abstract: Worker safety attitudes are key determinants of whether protective practices are applied or bypassed on construction sites. Yet measuring them at scale

safetyarxiv-cs-cl

M3imic: Learning a Versatile Whole-Body Controller for Multimodal Motion Mimicking

arXiv:2606.04829v1 Announce Type: new Abstract: Building a general-purpose whole-body controller is essential for enabling diverse motion capabilities in humanoid robots across a wide range of downstr

safetyarxiv-cs-ro

MaCo-GAN: Manifold-Contrastive Adversarial Learning for Single Image Super-Resolution

arXiv:2606.05068v1 Announce Type: new Abstract: Conventional Generative Adversarial Networks (GANs) for Single Image Super-Resolution (SISR) often struggle with hallucinated artifacts, largely because

MorphoQuant: Modality-Aware Quantization for Omni-modal Large Language Models

arXiv:2606.04349v1 Announce Type: cross Abstract: Conventional Post-Training Quantization (PTQ) methods struggle with 4-bit Omni-modal Large Language Models (OLLMs) due to the extreme distribution het

Tutorials

Motion-Guided Causal Disentanglement for Robust Multi-View Cine Cardiac MRI Diagnosis

arXiv:2606.04414v1 Announce Type: new Abstract: Multi-view cardiac magnetic resonance (CMR) imaging provides complementary anatomical information and is widely used for noninvasive disease assessment.

tutorialsarxiv-cs-cv

Tutorials

ParetoPilot: Zero-Surrogate Offline Multi-Objective Optimization via Infer-Perturb-Guide Diffusion

arXiv:2606.04468v1 Announce Type: cross Abstract: Offline multi-objective optimization (Offline MOO) aims to discover novel Pareto-optimal designs based on static datasets without expensive environmen

tutorialsarxiv-cs-ai

Radiomic Feature Selection Using Gradient Loss of Deep Neural Network for Lung Cancer Stage Detection

arXiv:2606.04453v1 Announce Type: new Abstract: Radiomics enables extraction of quantitative imaging biomarkers from medical images and has become an important tool for computer-aided cancer diagnosis

Rethinking Sales Lead Scoring with LLM-based Hierarchical Preference Ranking

arXiv:2606.04387v1 Announce Type: cross Abstract: Sales lead conversion in high-stakes domains (e.g., automotive, real estate) differs fundamentally from e-commerce recommendation due to prolonged dec

RIDE: An Open Dataset and Benchmark for Train Delay Prediction

model-releasesarxiv-cs-lg

arXiv:2606.05070v1 Announce Type: new Abstract: Train delay prediction is an important problem for both passengers and railway operators, yet progress in the field remains difficult to assess due to t

Hardware

Scaling Novel Graph Generation via Lightweight Structure-Guided Autoregressive Models

arXiv:2606.04287v1 Announce Type: cross Abstract: Generating realistic and diverse graphs is a key problem in machine learning, with applications in molecular discovery, circuit design, cybersecurity,

hardwarearxiv-cs-ai

SFMP: Fine-Grained, Hardware-Friendly and Search-Free Mixed-Precision Quantization for Large Language Models

arXiv:2602.01027v2 Announce Type: replace Abstract: Mixed-precision quantization is a promising approach for compressing large language models under tight memory budgets. However, existing mixed-preci

Speculative Thinking: Enhancing Small-Model Reasoning with Large Model Guidance at Inference Time

arXiv:2504.12329v2 Announce Type: replace-cross Abstract: Recent advances leverage post-training to enhance model reasoning performance, which typically requires costly training pipelines and still su

StepPRM-RTL: Stepwise Process-Reward Guided LLM Fine-Tuning for Enhanced RTL Synthesis

arXiv:2606.04246v1 Announce Type: new Abstract: Automatic generation of RTL code for digital hardware designs remains challenging due to long-horizon reasoning, multi-step dependencies, and strict cor

Stepwise Reasoning Enhancement for LLMs via External Subgraph Generation

model-releasesarxiv-cs-cl

arXiv:2606.04454v1 Announce Type: new Abstract: Large language models have shown strong performance in natural language generation and downstream reasoning tasks, but they still struggle with logical

Tutorials

TGSD: Topology-Guided State-Space Diffusion for EEG Spatial Super-Resolution

arXiv:2606.03998v1 Announce Type: cross Abstract: Low-density EEG is more suitable for wearable and IoT-based brain sensing, but sparse electrode sampling often lacks sufficient spatial information to

tutorialsarxiv-cs-cv

Hardware

TITAN-FedAnil+: Trust-Based Adaptive Blockchain Federated Learning for Resource-Constrained Intelligent Enterprises

arXiv:2606.04388v1 Announce Type: cross Abstract: Federated Learning (FL) has emerged as an effective paradigm for collaborative intelligence while preserving data privacy. However, data heterogeneity

hardwarearxiv-cs-ai

Tree-Based Formalization of Multi-Agent Complementarity in Human-AI Interactions

arXiv:2606.04779v1 Announce Type: new Abstract: Complementarity is the case in which a human--AI interaction (HAI) outperforms the best prediction benchmark available among its members. Although this

Applications

Uncertainty-Aware End-to-End Co-Design of Neural Network Processors: From Training and Mapping to Fabrication

arXiv:2606.04850v1 Announce Type: cross Abstract: Designing a neural network processor is an end-to-end co-design problem: network architecture and training budget determine the inference workload; ha

applicationsarxiv-cs-ai

Local Ai

Uncertainty-Aware (Un)Supervised Few-Shot User Adaptation for On-Device Personalized Human Activity Recognition

arXiv:2606.04798v1 Announce Type: new Abstract: Sensor-based Human Activity Recognition (HAR) models often degrade on unseen users due to domain shifts caused by individual movement patterns and senso

local-aiarxiv-cs-lg

UniFine: A Unified and Fine-grained Approach for Zero-shot Vision-Language Understanding

arXiv:2307.00862v3 Announce Type: replace-cross Abstract: Vision-language tasks, such as VQA, SNLI-VE, and VCR are challenging because they require the model's reasoning ability to understand the sema

researcharxiv-cs-cl

A Sparse Bayesian Learning Algorithm for Estimation of Interaction Kernels in Motsch-Tadmor Model

arXiv:2505.07068v2 Announce Type: replace-cross Abstract: In this paper, we investigate the data-driven identification of asymmetric interaction kernels in the Motsch-Tadmor model based on observed tr

AirDreamer: Generalist Drone Navigation with World Models

arXiv:2606.03252v1 Announce Type: cross Abstract: Navigating a drone in unseen and cluttered environments requires reliable generalization to unseen scene layouts and understanding of environmental st

APIC: Amortized Physics-Informed Calibration using Neural Processes

model-releasesarxiv-cs-lg

arXiv:2606.03355v1 Announce Type: new Abstract: Physics models are inherently imperfect due to misspecified or missing mechanisms, resulting in systematic discrepancies between model predictions and r

Applying Two-Grid Preconditioner for Subsurface Flow Simulation using Attention-enhanced Hybrid Network to Accelerate Multiscale Discretization in High-contrast Media

arXiv:2606.02582v1 Announce Type: cross Abstract: In this paper, we study the efficient numerical solution of Darcy equations in strongly heterogeneous media with high-contrast permeability and propos

ASAP: Exploiting the Satisficing Generalization Edge in Neural Combinatorial Optimization

arXiv:2501.17377v4 Announce Type: replace-cross Abstract: Deep Reinforcement Learning (DRL) has emerged as a promising approach for solving Combinatorial Optimization (CO) problems, such as the 3D Bin

BEAST3D: Animal behavioral analysis and neural encoding from multi-view video via Gaussian splatting

arXiv:2606.02937v1 Announce Type: cross Abstract: Multi-view video recordings are increasingly used to capture the 3D movements of animals in experimental settings, yet extracting rich 3D representati

Applications

Binary Road Surface Classification Using Machine Learning on Production Vehicle Signals During Cruising

arXiv:2606.02762v1 Announce Type: new Abstract: Knowledge of real-time road slipperiness, or even better, a refined estimate of peak grip potential, is a critical input for vehicle warning and interve

applicationsarxiv-cs-lg

Bionic Human-Motion Style Transfer for Physically Executable Whole-Body Control of Humanoid Robots

arXiv:2606.03536v1 Announce Type: new Abstract: Expressive whole-body motion is important for humanoid robots operating in human environments, where robots are expected to move stably while presenting

safetyarxiv-cs-ro

Bridging Predictive Uncertainty and Safe Action: Sample-Conditioned Differentiable Planning for Autonomous Driving

arXiv:2606.03296v1 Announce Type: new Abstract: Complex, dynamic, and interactive driving environments pose significant challenges for autonomous driving, primarily due to the pervasive uncertainty of

safetyarxiv-cs-ro

CANMOT: Class-Aware Noise Modeling for Multi-Object Tracking in Autonomous Driving

model-releasesarxiv-cs-ro

arXiv:2606.03590v1 Announce Type: new Abstract: Kalman filter (KF)-based multi-object tracking (MOT) remains a strong baseline for autonomous driving due to its strong performance, computational effic

ClinicalMC: A Benchmark for Multi-Course Clinical Decision-Making with Large Language Models

arXiv:2606.03157v1 Announce Type: new Abstract: Large language models (LLMs) have been widely adopted in healthcare, yet they still encounter significant challenges in complex clinical decision-making

Code-on-Graph: Iterative Programmatic Reasoning via Large Language Models on Knowledge Graphs

arXiv:2606.03705v1 Announce Type: new Abstract: Knowledge Graphs (KGs) are widely used to mitigate the limitations of Large Language Models (LLMs), such as outdated knowledge and hallucinations. Exist

Conditional Latent Diffusion Model with Fourier-based Motion Modelling for Virtual Population Synthesis

arXiv:2606.03827v1 Announce Type: cross Abstract: In-silico trials of medical devices require the generation of virtual populations of anatomies. In cardiovascular applications, virtual anatomy is typ

CoralBay: A Self-Supervised CT Foundation Model

model-releasesarxiv-cs-cv

arXiv:2606.03888v1 Announce Type: new Abstract: Self-supervised learning has enabled large-scale pre-training on 2D natural images, producing general-purpose visual representations that transfer effec

Correcting Neural Operator Spectral Bias via Diffusion Posterior Sampling with Sparse Observations

arXiv:2606.03936v1 Announce Type: new Abstract: Neural operator surrogates (NO) approximate PDE solutions orders of magnitude faster than numerical solvers, but suffer from spectral bias: high-frequen

safetyarxiv-cs-lg

Curriculum-Adapted Robust Reinforcement Learning for UAV Deconfliction in Adversarial Environments

arXiv:2506.21129v2 Announce Type: replace-cross Abstract: Autonomous unmanned aerial vehicles (UAVs) increasingly rely on reinforcement learning (RL) for navigation. However, global navigation satelli

Decomposing how prompting steers behavior

arXiv:2606.03093v1 Announce Type: new Abstract: Prompting steers large language models (LLMs) and vision-language models (VLMs) without weight updates, but it remains unclear how instruction changes r

Local Ai

DMT-CBT: Longitudinal Therapeutic State Modeling for CBT Counseling

arXiv:2606.03132v1 Announce Type: new Abstract: Large language models (LLMs) have shown growing potential for Cognitive Behavioral Therapy (CBT) counseling. However, most existing approaches still for

local-aiarxiv-cs-cl

Agents

Entropy Gate: Entropy Quenching for Near-Lossless Token Compression in LLM Pipelines

arXiv:2606.03739v1 Announce Type: new Abstract: LLM pipelines waste substantial token budgets on low-information content: repeated context, verbose responses, and redundant boilerplate. We introduce E

agentsarxiv-cs-cl

Estimating Central, Peripheral, and Temporal Visual Contributions to Human Decision Making in Atari Games

arXiv:2604.04439v2 Announce Type: replace-cross Abstract: We study how different visual information sources contribute to human decision making in dynamic visual environments. Using Atari-HEAD, a larg

Fast and Expressive Multi-Byte Prediction with Probabilistic Circuits

arXiv:2511.11346v2 Announce Type: replace Abstract: Multi-token prediction (MTP) is a prominent strategy to significantly speed up generation in large language models (LLMs), especially in byte-level

FGRPO: Federated GRPO with Adaptive Aggregation on Non-IID Data

arXiv:2606.03094v1 Announce Type: new Abstract: Recent advances in language models have established reinforcement learning as the primary paradigm for eliciting self-correction and long-chain reasonin

safetyarxiv-cs-lg

FlashMLA-ETAP: Efficient Transpose Attention Pipeline for Accelerating MLA Inference on NVIDIA H20 GPUs

arXiv:2506.01969v3 Announce Type: replace-cross Abstract: Efficient inference of Multi-Head Latent Attention (MLA) is challenged by deploying the DeepSeek-R1 671B model on a single Multi-GPU server. T

Local Ai

Generalizing Graph Foundation Models via Hyperbolic Retrieval-Augmented Generation

arXiv:2606.03307v1 Announce Type: cross Abstract: Graph foundation models (GFMs) emerged as a dominant paradigm in graph representation learning by leveraging large-scale pre-training for cross-domain

local-aiarxiv-cs-ai

Applications

Hierarchical Federated Learning with Dynamic Clustering and Adaptive Regularization for Robust Infrastructure Inspection

arXiv:2606.03084v1 Announce Type: new Abstract: The deployment of data-driven computer vision models for structural health monitoring (SHM) is heavily constrained by the data silo dilemma due to strin

applicationsarxiv-cs-cv