Search: “tutorials”

Learned Interventions in Lean 4 grind

arXiv:2607.22972v1 Announce Type: new Abstract: Lean~4's grind{} tactic combines congruence closure, ematch{}ing, and case-splitting into a single automated solver, and like any such solver, it relies

Learning Dense 2D-3D Correspondence for X-ray-to-CT Registration of Knee Bones

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DGX agent

arXiv:2607.22803v1 Announce Type: cross Abstract: Recovering the 6-DoF pose of the knee bones from a plain radiograph, given the patient's segmented pre-operative CT, turns a routine low-dose image in

tutorialsarxiv-cs-cv

28 Jul 2026

Learning Distributions from Multiple Data Providers

arXiv:2607.24732v1 Announce Type: cross Abstract: Motivated by learning from heterogeneous and overlapping data providers, we study a stylized model of distribution learning from restricted conditiona

Like a Baby: Visually Situated Neural Language Acquisition

arXiv:1805.11546v3 Announce Type: replace-cross Abstract: We examine the benefits of visual context in training neural language models to perform next-word prediction. A multi-modal neural architectur

Like a bilingual baby: The advantage of visually grounding a bilingual language model

arXiv:2210.05487v3 Announce Type: replace Abstract: Unlike most neural language models, humans learn language in a rich, multi-sensory and, often, multi-lingual environment. Current language models ty

Mamba-CL: Optimizing Selective State Space Model in Null Space for Continual Learning

arXiv:2411.15469v3 Announce Type: replace Abstract: Continual Learning (CL) aims to equip AI models with the ability to learn a sequence of tasks over time, without forgetting previously learned knowl

Masked Autoencoders Learn Perception-Relevant Representations from Resting State Neural Data

arXiv:2607.22615v1 Announce Type: cross Abstract: Clinical neuroprosthetics face a data bottleneck: labeled perception trials are scarce while hours of spontaneous neural activity are largely underuti

Memory for Attention: Language-Conditioned Re-Perception with a Vision--Language--Motion Map

arXiv:2607.23797v1 Announce Type: new Abstract: A robot carrying a persistent, behavior-annotated map faces two planning questions, and its memory answers only one well. The spatial-navigation questio

MicroZoom: Structure-Preserving Detail Synthesis at Extreme Scale

arXiv:2607.24729v1 Announce Type: new Abstract: We introduce MicroZoom, a generative framework for gigapixel image synthesis at the microscopic scale. Given a standard photograph and a sparse set of c

Multimodal Semantic-Probabilistic Objectness for Open World Object Detection

arXiv:2607.23981v1 Announce Type: cross Abstract: Open-world object detection (OWOD) requires a detector to recognize known categories, discover unnamed objects from unseen categories, and incremental

No Free Lunch in Flow Surrogates under Time-Varying Boundary Conditions: A Two-Regime Study

arXiv:2607.23667v1 Announce Type: cross Abstract: A flow surrogate validated on a simple regime is often taken as evidence that the approach will carry to a richer one. We test this assumption on two

Offline-Online Curriculum RL for Multimodal Reasoning

arXiv:2607.23700v1 Announce Type: new Abstract: Multimodal large language models exhibit capabilities on reasoning tasks, yet often produce flawed intermediate steps while yielding correct final answe

Offline-to-Online Creative Optimization with Generative Models and Adaptive Testing

arXiv:2607.23696v1 Announce Type: new Abstract: Ad creative optimization is increasingly constrained by evaluation rather than generation. Generative models can produce many plausible creatives, but r

On Non-Stationary Dynamic Pricing: Adaptivity and Optimality

arXiv:2607.24115v1 Announce Type: cross Abstract: We study the contextual dynamic pricing problem under non-stationarity, where a firm sells products to T sequentially arriving consumers that behave a

PathSelect: Sequential Token Selection for Whole Slide Pathology

arXiv:2607.23631v1 Announce Type: new Abstract: Gigapixel Whole-Slide Images (WSIs) present a fundamental computational bottleneck for vision-language models (VLMs) due to extreme sequence lengths. Ex

Patient-Agnostic Synthetic Pretraining for Efficient Patient-Specific Intraoperative 2D/3D Registration

arXiv:2607.23343v1 Announce Type: cross Abstract: Intraoperative 2D/3D registration aligns preoperative CT volumes with intraoperative X-ray or fluoroscopic images and is essential for image-guided in

Self-Supervised Consistency Enhanced Disentangled Learning for Neural Decoding Generalization in Brain-Machine Interface

arXiv:2607.24023v1 Announce Type: new Abstract: Brain-Machine Interfaces (BMIs) provide a direct communication pathway between the brain and external devices, enabling humans to control assistive and

Structure over Depth: A Single-Block Spatio-Temporal Transformer for Multi-Entity Reasoning

arXiv:2607.23077v1 Announce Type: new Abstract: Modeling multi-entity temporal data requires capturing dependencies across entities, time, and their interactions. Transformer-based approaches perform

Surgical Re-enactment for Operating Room Workflow Datasets

arXiv:2607.24206v1 Announce Type: cross Abstract: The introduction of new technologies, such as surgical robots, is driving the vision of a connected, smart operating room (OR). However, realizing thi

The balance between compactness and forecast accuracy of data-driven latent-space reduced-order models in controlled wake flows

arXiv:2607.24569v1 Announce Type: cross Abstract: Model-based active flow control requires predictive models that are accurate, stable, and fast enough for real-time optimisation. In controlled wake f

Towards Nexus-Score: Metadata Gaps Limit Scholarly AI Attribution

arXiv:2607.22684v1 Announce Type: cross Abstract: Artificial intelligence systems increasingly mediate how science is found and credited. We asked whether missing metadata prevents AI systems from cre

Towards Ultrafast Depth Sensing Via Active Event-based Stereo Vision

arXiv:2607.23684v1 Announce Type: new Abstract: Conventional frame-based imaging for active stereo systems has encountered major challenges in fast-motion scenarios. However, how to design a novel par

VIPER: Visual In-Context Physics Reasoning for Physically Plausible Video Generation

arXiv:2607.23472v1 Announce Type: new Abstract: Modern video generation models can synthesize visually compelling and temporally coherent clips, yet controlling their physical behavior remains difficu

WARL: Wrench-Augmented Reinforcement Learning for Task-Agnostic Learning in Legged Robots

arXiv:2607.24036v1 Announce Type: new Abstract: While reinforcement learning for legged robots has achieved high motor performance, it has been constrained by the limited exploration capability of act

When Activation Oracles Learn Not to Read: Concept-Specific Blind Spots in Fine-Tuned Oracles

arXiv:2607.23379v1 Announce Type: cross Abstract: Activation Oracles (AOs) are language models trained to answer natural-language questions about another model's internal activations. They offer a fle

Alleviating Regional Shortcuts for Few-Shot Class-Incremental Learning

arXiv:2607.22072v1 Announce Type: new Abstract: Few-shot class-incremental learning (FSCIL) aims to incrementally learn novel classes with only a few samples while avoiding forgetting base classes. Ho

Correlating Cross-Iteration Noise for DP-SGD using Model Curvature

arXiv:2510.05416v3 Announce Type: replace Abstract: Differentially private stochastic gradient descent (DP-SGD) offers the promise of training deep learning models while mitigating many privacy risks.

Deep Convolutional Large-Margin ell_p-SVDD for Visual Anomaly Detection

arXiv:2607.22212v1 Announce Type: new Abstract: Visual anomaly detection requires adaptive representations and reliable decision boundaries, particularly when anomalous training samples are scarce and

FSE: Continual Learning for Named Entity Recognition by Fast-Slow Experts

arXiv:2607.22075v1 Announce Type: new Abstract: Continual Learning for Named Entity Recognition (CLNER) enable models to incrementally learn new entity types without forgetting previously acquired one

GeoDiff-SAR: A Geometric Prior Guided Diffusion Model for SAR Image Generation

arXiv:2601.03499v2 Announce Type: replace-cross Abstract: Synthetic aperture radar (SAR) image generation can mitigate data scarcity, but controllablegeneration under sparse observation angles remains

Humanly: A Configurable and Traceable Environment for Human-AI Collaborative Writing

arXiv:2607.21758v1 Announce Type: new Abstract: Teachers, conference chairs, and public readers all judge writing from limited evidence, seeing only a finished document and not the process that produc

Learning Adaptive Semantic Gaussian Allocation for 3D Occupancy

arXiv:2607.21896v1 Announce Type: new Abstract: Semantic 3D Gaussians provide a compact representation for 3D semantic occupancy prediction by rendering semantic primitives into a voxel volume under v

Learning Diverse Humanoid Tasks via Synthetic Video Scenarios without Real World Data

arXiv:2607.21648v1 Announce Type: new Abstract: The human-like morphology of humanoid robots grants them exceptional potential for agile and versatile motor capabilities, but it also introduces signif

Learning to Reason for Factuality

arXiv:2508.05618v2 Announce Type: replace Abstract: Reasoning Large Language Models (R-LLMs) have significantly advanced complex reasoning tasks but often struggle with factuality, generating substant

Quality Text, Robust Vision: The Role of Language in Enhancing Visual Robustness of Vision-Language Models

arXiv:2507.16257v2 Announce Type: replace Abstract: Defending pre-trained vision-language models (VLMs), such as CLIP, against adversarial attacks is crucial, as these models are widely used in divers

Robot-Factored World Models via Robot Rendering

arXiv:2607.22535v1 Announce Type: cross Abstract: Action-conditioned video world models predict future observations from an initial observation and an action signal. In robotics, actions influence fut

Statistical mechanics of extensive-width Bayesian neural networks near interpolation

arXiv:2505.24849v2 Announce Type: replace-cross Abstract: For three decades statistical mechanics has been providing a framework to analyse neural networks. However, the theoretically tractable models

Variance-Reduced Q-Learning over Static and Time-Varying Networks

arXiv:2607.21876v1 Announce Type: new Abstract: We investigate a decentralized reinforcement learning problem involving multiple agents that interact with the same Markov Decision Process (MDP). The a

Visual Saliency Steering Distillation for Multimodal Chain-of-Thought Reasoning

arXiv:2607.22013v1 Announce Type: new Abstract: Multimodal chain-of-thought (CoT) reasoning integrates visual and textual cues through step-by-step inference. In small models with limited token budget

Artificial Epanorthosis: Why large language models overuse a classical rhetorical figure, and how to mitigate it

arXiv:2607.21498v1 Announce Type: cross Abstract: A rhetorical figure that Cicero and Quintilian catalogued two thousand years ago reappears, systematically, in the text of large language models: epan

Beyond SBDD: Geometric Deep Learning in Polypharmacology and Multi-target Drug Design

arXiv:2607.20550v1 Announce Type: cross Abstract: The traditional 'one drug, one target' paradigm of structure-based drug design (SBDD) frequently proves inadequate for treating multifactorial disease

C-PTQ: Fisher-weighted Channel-wise Sensitivity for Post-training Quantization of MLLMs

arXiv:2607.21076v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) require huge memory and computational costs, which limits their practical deployment. Post-training quantizatio

CLOAK: Contrastive Guidance for Latent Diffusion-Based Data Obfuscation

arXiv:2512.12086v2 Announce Type: replace Abstract: Data obfuscation is a promising technique for mitigating attribute inference attacks by semi-trusted parties with access to time-series data emitted

CLOE: Christoffel Loss Autoencoder for Anomaly Detection

arXiv:2607.20530v1 Announce Type: cross Abstract: Semi-supervised anomaly detection plays a key role in diverse fields such as process monitoring, healthcare, and finance. However, lightweight methods

DART: A Degradation-Aware Recurrent Transformer for Archival Film Restoration

arXiv:2607.21219v1 Announce Type: new Abstract: Archival film restoration is a challenging problem because historical footage contains compound degradations such as scratches, dust, blur, noise, flick

DCVC-MV: Deep Contextual Multiview Video Compression with Efficient Inter-View Prediction

arXiv:2509.03922v2 Announce Type: replace Abstract: Multiview video is a key format for 3D applications such as free-viewpoint broadcasting and virtual reality, yet its large data volume poses signifi

ElasticTTT: Prior-Preserving Test-Time Tuning for Video Editing

arXiv:2607.21529v1 Announce Type: cross Abstract: Test-Time Tuning (TTT) on pretrained diffusion models has emerged as a powerful paradigm for video editing. However, there exists a foundational misma

Emergent Compositional Skills in Mixture-of-Experts VLAs

arXiv:2607.20771v1 Announce Type: cross Abstract: We consider the problem of learning compositional robot policies end-to-end from expert demonstrations, without any pre-specified notion of task decom