Search: “tutorials”

Learning New Words from Unlabeled Test Data in Automatic Speech Recognition

arXiv:2609.28877v1 Announce Type: cross Abstract: New words are invented every day. A human listener can learn a new word by hearing it clearly once and inferring its usage from sentence context. This

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Let Training Guide Selection: Online Synthetic Data Filtering via Real-Anchored Utility

DGX agent

arXiv:2609.29988v1 Announce Type: new Abstract: Synthetic data can scale training supervision when real-world data are limited, but noise and distribution mismatch can reduce its value. Existing synth

tutorialsarxiv-cs-lg

25 Sept 2026

MorphIK: Morphology-Conditioned Neural Inverse Kinematics for Unknown Robots

arXiv:2609.29908v1 Announce Type: cross Abstract: Neural models can learn to generate various solutions to the inverse kinematics problem from data, but are usually limited to a single robot. We prese

Neuro-symbolic AI for Industrial Configuration

arXiv:2609.29947v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown impressive performance on a wide range of generative tasks. Yet their probabilistic nature makes them, in isolat

Nope. It's still true. Where is your domestic robot? Where is your Level-5 self-driving car? Where is your robot car that can learn to drive…

Nope. It's still true. Where is your domestic robot? Where is your Level-5 self-driving car? Where is your robot car that can learn to drive in a few hours of practice like any 17 year old? Where is y

tutorialsyann-lecun--x

PePESeg3D: Perception Prior Enhances Multi-Scale Segmentation for 3D Gaussian Splatting

arXiv:2609.28645v1 Announce Type: new Abstract: Recent advancements in 3D Gaussian Splatting (3DGS) have extended its capabilities to multi-scale segmentation. Existing methods reconstruct a scene wit

Personalised federated learning for Riemannian and Euclidean EEG decoding

arXiv:2609.29037v1 Announce Type: cross Abstract: Federated learning (FL) lets EEG decoders learn from recordings of several subjects without pooling them. We consider two light EEG decoders, the Riem

RAPTOR: RAndom-projection Physics-informed Transient sOlveR

arXiv:2609.29714v1 Announce Type: cross Abstract: The complexity of time-domain simulation of modern power systems has increased significantly because converter-based resources introduce control dynam

Right Choice of Classification Algorithms Based on Reinforcement Learning for Prediction of Non-Alcoholic Fatty Liver

arXiv:2609.29181v1 Announce Type: new Abstract: There are many complex issues in the world of artificial intelligence. Some of these problems are solved using other artificial intelligence methods, wh

RLVR landscapes for iterated multiplications can be benign: Insights from spin-glass theory

arXiv:2609.28625v1 Announce Type: new Abstract: Despite the importance of reinforcement learning with verifiable rewards (RLVR), the extent to which it can learn new reasoning capabilities remains deb

Scaling MoE reinforcement learning on Amazon EKS with EFA and DeepEP with 40% more throughput

Learn how to scale Mixture-of-Experts (MoE) reinforcement learning on Amazon EKS using Elastic Fabric Adapter (EFA) and DeepEP. This post presents an architecture that combines Amazon EKS, EFA, and Am

tutorialsaws-ml-blog

Self-Play Pretraining with Zero Data

arXiv:2609.30063v1 Announce Type: new Abstract: Advances in language modeling have been driven by scaling pretraining on ever more data. Yet, the training data is still largely curated on the model's

SplatLabel: Pseudo-Labelling through 4D Gaussian Splatting

arXiv:2609.29836v1 Announce Type: new Abstract: While 2D Vision Foundation Models offer a pathway to automate 3D semantic pseudo-labelling, translating these priors into robust 3D representations typi

Streaming-WAM: Action-Conditioned World-Action Model for Asynchronous Robot Manipulation

arXiv:2609.28927v1 Announce Type: new Abstract: World action models (WAMs) that use future visual prediction at inference time incur substantial generation costs. Asynchronous execution reduces waitin

tutorialsarxiv-cs-ro

TimeBraid: Unifying Time Series and Language for Understanding and Forecasting

arXiv:2609.29792v1 Announce Type: cross Abstract: We present TimeBraid, a series of unified time-series and language models that align pretrained language models and pretrained time-series foundation

ToCo-Mesh: Topology-Consistent Dynamic Mesh Reconstruction via Adaptive Tessellation and Surface-Aligned 2DGS

arXiv:2609.29529v1 Announce Type: cross Abstract: Reconstructing dynamic meshes with consistent topology from multi-view temporal images remains a challenge. Existing approaches typically face a dilem

Upholding Robustness in Federated Learning: Trends, Emerging Strategies, and Research Opportunities

arXiv:2609.28722v1 Announce Type: new Abstract: While Federated Learning (FL) has been widely adopted for protecting user privacy in machine learning, it remains vulnerable to various robustness chall

Where LLM Graders Succeed and Break: Evidence from Two Computer-Science Exams

arXiv:2609.29333v1 Announce Type: cross Abstract: One long-form exam in a large course costs hundreds of grader-hours, and qualified graders are scarce; LLM graders are a tempting alternative. To show

A Native-Reference Coordinate Geometry for L2 Pronunciation Deviation Using Self-Supervised Speech Models

arXiv:2609.28060v1 Announce Type: new Abstract: Self-supervised speech models encode rich phonetic information, but it remains unclear how to transform this information into interpretable metrics for

Aderant builds intelligent ticket triage with Amazon Nova

Learn how Aderant built an intelligent ticket triage system on Amazon Nova Lite through Amazon Bedrock, automating context gathering, classification, routing, and knowledge enrichment for its cloud op

tutorialsaws-ml-blog

Constraint-Driven Context Engineering: Designing Domain Interfaces for AI Systems

arXiv:2609.27354v1 Announce Type: cross Abstract: Generative AI systems are increasingly deployed to address domain problems. These systems operate under technical, regulatory, institutional, and norm

Discrete Diffusion Models via Evolving Variational Autoregressive Networks

arXiv:2609.27306v1 Announce Type: new Abstract: Conventional score-based diffusion models learn scores without representing normalized densities, whereas tractable normalized models support both sampl

Everytime AI spend grows where I flirt with token budgeting, Anthropic + OpenAI save me Astra had a spike then settled down lower Opus 5.5 i…

Everytime AI spend grows where I flirt with token budgeting, Anthropic + OpenAI save me Astra had a spike then settled down lower Opus 5.5 it looks like spend is lowered for current usecases Of course

tutorialsdylan-patel--x

From Change Captions to Change Detection: Semantic-Appearance Agreement Framework for Remote Sensing Change Detection

arXiv:2609.28192v1 Announce Type: new Abstract: Remote sensing change detection (RSCD) is essential for monitoring land-cover changes and urban development. However, most methods demand pixel-level ch

Global tree forecasters collapse at the hierarchical aggregate: a five-panel failure characterization

arXiv:2609.27912v1 Announce Type: new Abstract: Global forecasting models pool many series and learn one shared function. Gradient-boosted trees are their most common form. We measure a failure of thi

LLM-Powered Socially Assistive Robot-Delivered Cognitive Behavioral Therapy Exercises: an Exploratory Study with University Students

arXiv:2402.17937v2 Announce Type: replace Abstract: Mental health is a significant healthcare challenge, and cognitive behavioral therapy (CBT) is a widely used therapeutic method for treating anxiety

tutorialsarxiv-cs-ro

Meet, Compare, or Abstain: LatWeave for Deterministic Multi-Hop Question Answering on Knowledge Lattices

arXiv:2609.27225v1 Announce Type: cross Abstract: Probabilistic question-answering systems -- whether large language models (LLMs) themselves, retrieval-augmented generation (RAG), or trained multi-ho

MORSE: Multi-Context Ordering via Reverse Scoring for Evidence-Preserving Compression

arXiv:2609.27380v1 Announce Type: new Abstract: Likelihood-based context compression can account for cross-context redundancy through sequential scoring, but this makes compression outcomes sensitive

NPBoost: Neural Processes with Gradient-Boosted Fixed Effects

arXiv:2609.28122v1 Announce Type: cross Abstract: Neural Processes (NPs) are model-based meta-learners that implicitly learn a stochastic process and adapt to a new task from a small context set. Most

On the Sample Complexity of Active Learning with Membership Queries

arXiv:2609.27241v1 Announce Type: cross Abstract: This work revisits a fundamental question in active learning: how powerful is the ability to synthesize arbitrary queries? Compared to pool-based acti

Pay attention to this new wave of System One models if you are building custom harnesses. First Jev. Now, Contrastive Language Model (CLM). …

Pay attention to this new wave of System One models if you are building custom harnesses. First Jev. Now, Contrastive Language Model (CLM). CLM is 9x faster than Jev. CLM seems to be a better verifier

tutorialsdair-ai--x

Privacy-Preserving Semantic Segmentation from High-Resolution Depth and Ultra-Low-Resolution RGB

arXiv:2609.28360v1 Announce Type: new Abstract: As mobile robots become increasingly integrated into everyday environments, privacy risks arising from onboard cameras have become a growing concern. Ul

Tail-Aware Geometry Learning for Conformal Ellipsoids

arXiv:2609.27221v1 Announce Type: new Abstract: This paper studies multivariate conformal prediction (CP), a distribution-free uncertainty quantification framework with finite-sample coverage guarante

Task-Prototype Guided Flow Matching for Few-Shot Generalization in Vision-Language Robot Manipulation

arXiv:2609.27780v1 Announce Type: cross Abstract: Vision-language robot manipulation policies can follow semantic instructions, but adapting them to a new procedure from only a few demonstrations rema

Towards Efficient Reasoning: Learning Causal Shortcuts for Diffusion Language Models

arXiv:2609.28272v1 Announce Type: new Abstract: Diffusion Language Models (DLMs) have attracted significant attention for their strong reasoning ability. However, under a bidirectional attention mecha

A digital-twin framework for forecasting treatment-day imaging with contour uncertainty in adaptive proton radiotherapy

arXiv:2609.24725v1 Announce Type: cross Abstract: Head-and-neck anatomy changes over a six-to-seven-week proton course, and the anatomy of a later week cannot be imaged when the plan is made. We prese

A Hybrid AI Framework for Academic Advising: Integrating Ensemble-Based Grade Prediction and a Rule-Based Expert System

arXiv:2609.26243v1 Announce Type: cross Abstract: The rapidly increasing student population has posed serious challenges to the traditional academic advising process. This study designs and implements

Brain-Inspired Hierarchical Modularity for General Continual Learning

arXiv:2609.25146v1 Announce Type: new Abstract: Continual learning, the ability to learn from sequential experience while retaining and adapting prior knowledge, is central to intelligent systems oper

Bridge of Psi's: Quantum Circuit Optimization with Schrodinger Bridges

arXiv:2609.25947v1 Announce Type: cross Abstract: Quantum circuit optimization replaces a circuit with an equivalent one of fewer gates and lower depth, reducing execution cost and error rate. We ask

ClusterFewshot: Improving Few-shot Optimization for LLMs workflow

arXiv:2609.25939v1 Announce Type: new Abstract: The performance of large language model (LLM) workflows often depends on selecting a small set of in-context demonstrations to guide model behavior on n

Continuous Optimization for p-adic Models

arXiv:2609.25501v1 Announce Type: new Abstract: We present the first method for native, continuous gradient descent for machine learning models with p-adic parameters. Existing native optimizers are d

FoMo: Forking Moment in Generative Trajectory as a Perceptual Distance

arXiv:2609.25716v1 Announce Type: new Abstract: Reference-based image quality assessment (IQA) metrics aim to reflect how humans perceive the perceptual distance between a pair of images. To learn how

How to Estimate Whether You Have Found Several Needles in a Haystack: Measuring Calibration in Multi-Label Text Classification

arXiv:2609.26468v1 Announce Type: new Abstract: A key factor in deciding whether to trust an automatic prediction is its confidence score, which should be calibrated to match the actual probability of

How to train your own Jev for $17

tutorialstogether-ai-blog

We just launched our own Jev-like classifier, together/Tev1-4B-experimental, on top of Qwen3.5 4B on Together’s serverless platform. In this blog post we’ll show you how to fine-tune your own version!

Identifying Intelligent Processes via Online Sequential Testing

arXiv:2609.26193v1 Announce Type: cross Abstract: Active sequential hypothesis testing studies how to identify an unknown hypothesis with a given set of sensing actions. We study this in the setting o

In-Context Guidance: Learning Inter-Task Synergies via Numerical Foundational Models for Few-Shot Multitask Optimization

arXiv:2609.25836v1 Announce Type: new Abstract: Multi-task optimization (MTO) addresses a set of optimization tasks simultaneously, often suffering from inaccurate inter-task relationship estimation u

Less Is More in the Long Tail: Stage-Adaptive Sample Selection for Annotation-Efficient Dense Prediction

arXiv:2609.25850v1 Announce Type: new Abstract: Deep learning performance generally improves with increasing training data, yet this scaling is fundamentally constrained by annotation cost in large-sc

Lifelong Learning of Video Diffusion Models From a Single Video Stream

arXiv:2406.04814v4 Announce Type: replace-cross Abstract: Video diffusion models can enable embodied agents to anticipate plausible futures from the recent past, but they are typically trained offline