Search: “tutorials”

An Analysis of Self-supervised Pre-training with Dependent Samples

arXiv:2609.05031v1 Announce Type: cross Abstract: Self-supervised learning relies on so-called data augmentations phi(x) of unlabeled datapoints x --- for example, masking random pixels in an image x

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Attention-guided super-resolution of 4D flow MRI in carotid arteries

DGX agent

arXiv:2609.04891v1 Announce Type: cross Abstract: Four-dimensional (4D) flow magnetic resonance imaging (MRI) is a powerful non-invasive technique for visualizing and quantifying complex blood flow pa

tutorialsarxiv-cs-ai

7 Sept 2026

Autoregressive Guidance of Deep Spatially Selective Filters using Bayesian Tracking for Efficient Extraction of Moving Speakers

arXiv:2603.23723v3 Announce Type: replace-cross Abstract: Deep spatially selective filters achieve high-quality enhancement with real-time capable architectures for stationary speakers of known direct

Better Understanding, Better Fixes? A Study of Hallucination in LLM-based Automated Program Repair

arXiv:2609.04909v1 Announce Type: cross Abstract: Large language models (LLMs) have significantly advanced automated program repair (APR), yet existing evaluations remain largely result-centric and pr

Beyond Homoscedasticity: Decoupled Uncertainty Optimization for Deep Imbalanced Regression

arXiv:2609.04995v1 Announce Type: new Abstract: Deep Imbalanced Regression (DIR) is pervasive in continuous prediction tasks across diverse modalities, such as age estimation, depth prediction, and pr

DART: Depth-as-Target Pretraining for Surgical Vision Foundation Models

arXiv:2609.04555v1 Announce Type: new Abstract: Vision foundation models (VFMs) are valuable in data-scarce domains such as surgery, where a single pretrained backbone can provide rich representations

Dual-Part Multi-Lateral Branched Network for Multi-Class Segmentation in Cardiovascular Catheterization Angiograms

arXiv:2609.04590v1 Announce Type: cross Abstract: Catheterisation image processing requires segmentation models that are fast, accurate and explainable. While most of the existing studies usually focu

Dynamic Heterogeneous Graph Representation Learning: A Survey

arXiv:2609.04779v1 Announce Type: cross Abstract: Graph representation learning (GRL) serves as a canonical paradigm for modeling complex networks. However, real-world AI systems inherently manifest a

Modular Deep Recurrent Neural Network: Application to Quadrotors

arXiv:2609.04339v1 Announce Type: new Abstract: A modular deep Recurrent Neural Network (RNN) is introduced to facilitate the process of deploying various architectures of RNNs, and to automatically c

Predicting Spatiotemporal Mobile Sensing-Based PM2.5 Concentrations Using Low-Rank Adapted Spatially Attentive Graph Neural Network

arXiv:2609.04693v1 Announce Type: new Abstract: Urban air quality can vary significantly along transit corridors, necessitating high-resolution monitoring. This work introduces a novel mobile-sensing

SMILE: Bridging Continuous Optimization and Discrete Symbolic Recovery

arXiv:2609.04639v1 Announce Type: new Abstract: Symbolic regression (SR) discovers closed-form mathematical expressions from data, offering interpretability beyond black-box models. Existing methods s

Too Rare to Learn: Prescribed Cyclone Tracks Degrade a Bay of Bengal Ocean Emulator

arXiv:2609.04635v1 Announce Type: new Abstract: Neural ocean emulators are being proposed for regional forecasting in cyclone-exposed coastal seas, and a natural design choice is to hand the network t

Topology-Aware Training and Spatial Diagnostics for Fiber Bundle Segmentation in Tracer Histology

arXiv:2609.04454v1 Announce Type: new Abstract: Anatomic tracer studies reveal how axon bundles project from an injection site, branch into smaller groups of axons, and course through the brain to rea

Towards a universal language of concepts: A survey

arXiv:2609.04528v1 Announce Type: new Abstract: Humans can learn and generalize novel concepts from sparse data because they express knowledge in rich structural formats. In this paper, we propose tha

Training Large Language Models for Small-Molecule Design with Synthetic Task Scaling

arXiv:2609.04735v1 Announce Type: new Abstract: Designing viable drug candidates requires searching a combinatorially large and rugged chemical space for molecules that satisfy multiple, often competi

TSMini: A Simple Yet Highly Effective Trajectory Similarity Learning Model

arXiv:2502.00285v3 Announce Type: replace-cross Abstract: Trajectory similarity is fundamental to many spatio-temporal data mining applications. Recent studies propose deep learning models to approxim

Ultrasound-Based Prediction of Cirrhosis Decompensation Using Large-Scale Computer Vision Models

arXiv:2609.04365v1 Announce Type: cross Abstract: Decompensation represents a critical transition in the course of cirrhosis, yet clinicians have limited non-invasive tools to reliably predict its ons

WeakMCN: Multi-task Collaborative Network for Weakly Supervised Referring Expression Comprehension and Segmentation

arXiv:2505.18686v3 Announce Type: replace Abstract: Weakly supervised referring expression comprehension(WREC) and segmentation(WRES) aim to learn object grounding based on a given expression using we

Who Should Grade My Work? Student Perspectives on Transparent AI-Assisted Writing Assessment in Higher Education

arXiv:2609.05346v1 Announce Type: new Abstract: The integration of GenAI tools into higher education assessment raises important questions about how students understand, interpret, and respond to AI-m

Why We Care About Understanding: Competence through Predictive Compression

arXiv:2609.04962v1 Announce Type: new Abstract: What is the relation between understanding and compression, and why does human understanding take such a heavily compressed form? Across information the

Loops and graphs. Sam Altman is now the ultimate advocate for (neuro)symbolic AI and he doesn’t even know it.

Loops and graphs. Sam Altman is now the ultimate advocate for (neuro)symbolic AI and he doesn’t even know it. Sam Altman (CEO of OpenAI): 'You don't need to write prompts anymore. You need loops and g

tutorialsgary-marcus--x

6 Sept 2026

Today we're releasing data on models accelerating research at OpenAI. Recursive self-improvement could be the most important contributor to …

Today we're releasing data on models accelerating research at OpenAI. Recursive self-improvement could be the most important contributor to AI capabilities over the next few years, but by default it w

tutorialssam-altman--x

6 Sept 2026

Beyond Retrieval: Progressive Latent Memory Evolution for Streaming Video Understanding

arXiv:2609.04131v1 Announce Type: new Abstract: Streaming video understanding requires multimodal large language models (MLLMs) to process continuous visual inputs and respond to user queries under st

Customizing your knowledge base on Amazon Bedrock for large and complex documents using Amazon Textract

Learn how to customize an Amazon Bedrock knowledge base for large, complex documents by combining the high-accuracy text extraction of Amazon Textract with the generative AI of Amazon Bedrock. This po

tutorialsaws-ml-blog

Dancing with REEM-C: A robot-to-human physical-social communication study

arXiv:2408.05301v3 Announce Type: replace Abstract: Humans often work closely together and relay a wealth of information through physical interaction. Robots, on the other hand, are not yet able to wo

tutorialsarxiv-cs-ro

Data Market Design through Deep Learning

arXiv:2310.20096v2 Announce Type: replace-cross Abstract: The data market design problem is a problem in economic theory to find a set of signaling schemes (statistical experiments) to maximize expect

Deploy a multimodal WhatsApp ordering assistant with Amazon Bedrock AgentCore

Learn how to deploy a multimodal WhatsApp ordering assistant that takes customer orders through text, voice notes, and real-time voice calls on a single business number, built on Amazon Bedrock AgentC

tutorialsaws-ml-blog

EPIC: Explicit Posterior Item Conditioning for Semantic ID Diffusion Recommendation

arXiv:2609.03522v1 Announce Type: cross Abstract: Semantic ID (SID) generative recommendation predicts the next item by generating a short tuple of discrete tokens. Recent masked-diffusion methods imp

From Nowcasting to Forecasting: Adapting a Reanalysis-Trained

arXiv:2609.03763v1 Announce Type: new Abstract: Accurate cloud-cover forecasts are important for temperature prediction, radiation forecasting, and solar-power operations. Short-range forecasting meth

Guide, Not Bind: Why Defeasible Priors Fail in Augmented Lagrangian Causal Discovery

arXiv:2609.03442v1 Announce Type: new Abstract: Differentiable causal discovery methods increasingly encode expert priors as forbidden-edge constraints enforced by an Augmented Lagrangian (ALM) penalt

Knowledge Acquisition During Pre-training? Large Language Models Learn Better With Auxiliary Views

arXiv:2609.04180v1 Announce Type: cross Abstract: Gaps remain in our understanding of how large language models (LLMs) acquire knowledge during pre-training. We posit that auxiliary views, reformulati

Listen to the Latents: Self-Correcting Speech Recognition in Large Audio Language Models Through Hidden-State Interactions

arXiv:2609.02940v1 Announce Type: cross Abstract: Recent automatic speech recognition (ASR) systems increasingly integrate large language models (LLMs) to leverage their semantic knowledge, either ext

LLMs Learn Better In-Context from Rules than from Examples

arXiv:2609.03213v1 Announce Type: new Abstract: Large language models (LLMs) exhibit in-context learning capabilities, where they can learn new tasks from prompt contexts without weight updates. We co

tutorialsarxiv-cs-cl

OBER+: Continuity-Aware Reporting and Traceable Continuous Improvement in Outcome-Based Education

arXiv:2609.03770v1 Announce Type: cross Abstract: Institutions practising outcome-based education compute learning outcome attainment routinely, while reviews of curriculum analytics report an absence

tutorialsarxiv-cs-cl

P-CORE: Self-Supervised Surface Consistency for Point-Based Neural Editing

arXiv:2609.03349v1 Announce Type: new Abstract: Advances in neural rendering have enabled high-fidelity multi-view reconstruction of 3D scenes. However, free-form non-rigid shape editing remains a sig

RuleMem: Active Rule Memory for Long-Term Conversational Agents

arXiv:2609.03915v1 Announce Type: new Abstract: Question answering agents in long-term conversations must reason over massive, temporally dispersed dialogue histories. However, existing memory mechani

tutorialsarxiv-cs-cl

Sparse auto-regressive modeling for scene generation from multi-view images

arXiv:2609.03931v1 Announce Type: new Abstract: Generating complete 3D scenes from sparse, unconstrained views is a fundamental challenge in 3D vision which requires reasoning beyond observed content

Statistical Feature Augmentation for Anomaly Detection in Dynamic Graphs

arXiv:2609.02965v1 Announce Type: cross Abstract: Dynamic networks are being applied in many domains, from social media to logistics systems, each with their own set of special characteristics. A mode

The Shape of Time: Video-Token Contrast for Temporal Understanding in VideoLMs

arXiv:2609.04110v1 Announce Type: new Abstract: Seeing frames in order does not mean representing time. Modern VideoLMs receive ordered video streams, yet their main supervision acts on generated text

TokenMatch: 3D Mesh Correspondence Transformer with Curvature-Guided Tokenisation

arXiv:2609.04202v1 Announce Type: new Abstract: While data-driven 3D shape correspondence estimation has recently seen substantial progress, robust matching under partial observations and strong non-i

TraveL: Transformer-based Multi-view Path Distributional Representation Learning

arXiv:2609.03427v1 Announce Type: cross Abstract: Path representation learning (PRL) for road networks has received increasing research attention, due to various path-related applications. Existing wo

Zero-Shot Novel Depth Synthesis Using 3D Foundation Models Scene Representations

arXiv:2609.04174v1 Announce Type: new Abstract: 3D Foundation Models (3DFMs) such as VGGT have recently pushed the boundaries of 3D vision by predicting rich unified representations with feed-foward t

Achieving More with Less: A Tensor-Optimization-Powered Ensemble Method

arXiv:2408.02936v3 Announce Type: replace Abstract: Ensemble learning is a method that leverages weak learners to produce a strong learner. However, obtaining a large number of base learners requires

An example of useful knowledge work: I assigned GPT-6 to read through tens of thousands of my emails, my writings, my calendar appointments …

tutorialsethan-mollick--x

An example of useful knowledge work: I assigned GPT-6 to read through tens of thousands of my emails, my writings, my calendar appointments and more to assemble a personal knowledge base of research,

AutoCompass: Accurate Visual Localization on Public Maps by Learning from Weak Labels

arXiv:2609.02798v1 Announce Type: new Abstract: Neural map matchers estimate an image's 3-DoF pose relative to a 2D map. These models are trained on large-scale datasets of geo-referenced images, whos

Compositional Spectral Prompts for LLM-based Online Time Series Forecasting

arXiv:2609.02093v1 Announce Type: new Abstract: To address the sequential and evolving nature of time series, the Online Time Series Forecasting (OTSF) task has been extensively studied in multiple do

Consistency as Regularization for Unsupervised Shadow Removal

arXiv:2609.01806v1 Announce Type: new Abstract: Shadow removal is an important preprocessing step for many vision tasks, yet existing supervised methods require paired shadow and shadow-free images, w

Differentiable Electricity-Market Clearing for Gradient-Based Planning

arXiv:2609.02646v1 Announce Type: new Abstract: Planning a large data center is difficult because a facility big enough to matter changes the electricity prices it will pay. Those prices are set by ma