Search: “tutorials”

Therapy as an NLP Task: Comparing LLMs and Human Peers Behaviors in CBT Sessions

arXiv:2409.02244v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly being used as ad hoc therapists. While prior research has found that LLMs outperform human couns

23 Sept 2026

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Tutorials

Towards Mitigating Excessive Forgetting in LLM Unlearning via Entanglement-Guidance with Proxy Constraint

DGX agent

arXiv:2508.20443v3 Announce Type: replace Abstract: Large language models (LLMs) are trained on massive datasets that may include private or copyrighted content. Due to growing privacy and ownership c

tutorialsarxiv-cs-lg

23 Sept 2026

UNet-AF: Alias-free UNet architectures

arXiv:2603.11323v2 Announce Type: replace Abstract: The simplicity and effectiveness of UNet architectures make them ubiquitous in image restoration, segmentation, and diffusion models. They are often

23 Sept 2026

You've Seen Enough: Quality-Constrained Image Coding for Machines

arXiv:2609.25108v1 Announce Type: new Abstract: Visual data is increasingly consumed by machine-vision systems rather than by human observers. Image Coding for Machines (ICM) compresses images assumin

23 Sept 2026

Actionable Insights from Observational Data: The Case of Advanced Classes in K-12 Education

arXiv:2609.23836v1 Announce Type: new Abstract: A fundamentally challenging question in K-12 education is about the effects of taking more advanced or challenging classes. It is particularly complex b

Adapting Boltz-2 with limited experimental activity data improves early enrichment in virtual screening

arXiv:2609.24302v1 Announce Type: cross Abstract: Virtual screening aims to prioritize active compounds from large chemical libraries within a limited experimental budget. When applying Boltz-2 to vir

AffordanceWAM: Affordance-Aware Joint World-Action Modeling for Robot Manipulation

arXiv:2609.22332v1 Announce Type: cross Abstract: Generalizable robot manipulation requires predicting how a scene will evolve, identifying where interactions are feasible, and determining how to act.

Authorship identification under domain shift: a survey of stylistic measures and learned author representations

arXiv:2310.00436v2 Announce Type: replace Abstract: Authorship identification uses patterns in writing to infer who wrote a text, but those patterns also reflect topic, genre, and register. This surve

Bayesian Deck-of-cards-based Ordinal Regression with Sequential Preference Elicitation

arXiv:2609.23212v1 Announce Type: cross Abstract: The Deck-of-cards-based Ordinal Regression (DOR) infers a value function from a ranking of reference alternatives in which the Decision Maker (DM) ins

Benchmarking Hybrid Deep Learning Architectures for Predictive Maintenance in Industry 4.0

arXiv:2609.22583v1 Announce Type: new Abstract: Predictive maintenance in Industry 4.0 refers to using data from sensors, machines, and production systems to estimate when equipment is likely to fail,

Beyond Visual Quality: A Study of Test-Time Planning with World Action Models

arXiv:2609.24745v1 Announce Type: new Abstract: World action models generate actions together with visual predictions of their consequences. These paired outputs create the potential for planning by s

Bilinear Optimization Divergence: Diagnosing Factor-Constrained LoRA Continual Learning

arXiv:2609.23594v1 Announce Type: new Abstract: Orthogonality in a LoRA factor does not by itself specify what the composed update protects: the answer depends on the task-start state, the parameteriz

Blind Thermodynamic Ontology Discovery from Anonymous Experiments

arXiv:2609.23387v1 Announce Type: new Abstract: Before a machine learning model can learn a thermodynamic equation of state, it must discover what its measurements represent: which channels scale with

CausalWM: Causal Chain-of-Thought Reasoning for Embodied World Model

arXiv:2609.23184v1 Announce Type: new Abstract: Embodied world models learn to predict future physical dynamics from visual observations and control signals, where physical knowledge is implicitly ent

Clustering-Based Collective Anomaly Detection in IoT Systems: A Graph Neural Network Approach

arXiv:2609.22166v1 Announce Type: new Abstract: The rapid advancement of Internet of Things (IoT) technology has led to the widespread deployment of smart, interconnected devices across a range of dom

Common Cause, Not Cross-Attention: Blocking Visual Shortcuts in Audio-Video Generation

arXiv:2609.22361v1 Announce Type: new Abstract: Joint audio--video generators are trained on data in which what an event looks like and what it sounds like are strongly, often spuriously, correlated:

Dense-Prior-Guided Generative Video Compression

arXiv:2604.06655v2 Announce Type: replace Abstract: Diffusion-based generative video compression offers a promising paradigm for low-bitrate reconstruction, but existing keyframe-based controllable ap

Efficient Reasoning Exploration via State-Conditioned Latent Steering with Progress Guidance

arXiv:2609.24066v1 Announce Type: new Abstract: Best-of-N is a widely used inference strategy for complex reasoning, whose effectiveness depends on whether sampled candidates can cover diverse and hig

FIRM-WM: State-factorized factual-interventional recurrent modeling for reward-free visual planning

arXiv:2609.22816v1 Announce Type: new Abstract: Reward-free latent world models can learn from offline videos and solve new image--goal tasks by optimizing actions through predicted latent futures. Th

From Content Generation to Learning Support: Pedagogy-Guided Generative Video Tutors for STEM Learning

arXiv:2609.24083v1 Announce Type: new Abstract: Generative AI enables scalable production of educational videos, but current systems largely focus on producing visually coherent content rather than su

InterHier: Learning Interconnected Hierarchical Semantics for Open-Vocabulary Object Detection

arXiv:2609.24026v1 Announce Type: new Abstract: In this paper, we investigate the limitations of fixed, hand-crafted connectors in hierarchical semantic representations for open-vocabulary object dete

MaskVLA: Visual Masking Against Trajectory Overfitting of Vision-Language-Action Model

arXiv:2609.23565v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models integrate vision-language understanding with executable robot actions, enabling end-to-end learning for robot contro

Metadata Supervised Imaging Representations for Modelling and Controlling Acquisition Variability

arXiv:2607.11295v2 Announce Type: replace Abstract: Biomedical imaging data exhibit substantial acquisition variability, where identical biological structures can appear markedly different due to diff

MoSAT: Human Motion Generation from Spatial Audio and Textual Description

arXiv:2609.23797v1 Announce Type: cross Abstract: Human motion is shaped by both external acoustic events and behavioral intent: spatial audio conveys environmental cues that elicit or guide a respons

NeuIDO: Neural Intrinsic Dynamics Operator for Physics-Informed 4D World Models

arXiv:2609.24313v1 Announce Type: new Abstract: World models aim to capture environmental dynamics and predict future trajectories, showing growing potential for embodied intelligence. Physics-informe

OJOx: Specification-Conditioned Demonstrations for Embodied AI in Construction

arXiv:2609.22289v1 Announce Type: new Abstract: Large-scale egocentric and whole-body human demonstrations are becoming a primary source of data for embodied intelligence. They record what people perc

OpenAI wants to consult elite mathematicians about how to not fumble again

After turning a string of spectacular mathematical results into a reputational crisis, OpenAI is consulting human mathematicians to help it figure out a less disastrous path forward. On Monday, the co

tutorialsthe-verge-ai

PAC-Bayesian Meta-Learning for Few-Shot Identification of Linear Dynamical Systems

arXiv:2609.24117v1 Announce Type: new Abstract: Identifying linear time-invariant (LTI) dynamical systems is challenging when trajectories are short, noisy, or high-dimensional. Traditional system ide

People outside the AI labs should have a real say in how this technology develops, and a clear way to judge if it's happening safely. Standa…

People outside the AI labs should have a real say in how this technology develops, and a clear way to judge if it's happening safely. Standards should help prevent the concentration of power, includin

tutorialssam-altman--x

PixelDiT2: Representation-Grounded Pixel Diffusion Transformers

arXiv:2609.24919v1 Announce Type: new Abstract: Recent advances in pixel-space diffusion models have narrowed the image quality gap with latent-space diffusion, but still converge more slowly and lag

Robot Programming with Augmented Reality: The Role of Spatial Ability

arXiv:2602.03544v2 Announce Type: replace Abstract: Programming a robot arm requires users to interpret coordinate frames, joint rotations, and trajectories that are not directly visible. Augmented re

StationPDE: Station-Oriented Surface PDE Learning for Multi-Station Multivariate Weather Forecasting

arXiv:2609.22123v1 Announce Type: new Abstract: Multi-station multivariate weather forecasting aims to forecast future weather variables at multiple weather stations from historical surface observatio

Style as Cover: Deep Image Steganography via Stylized Transmission

arXiv:2609.22392v1 Announce Type: new Abstract: Image steganography hides secret message within normal images, with most existing works relying on cover-preserving transmission. However, such a paradi

Success Leaves Detours: Learning Executable Walkthroughs for Long-Horizon Agents

arXiv:2609.22120v1 Announce Type: cross Abstract: Test-time self-evolving agents improve by reusing past experience, yet sparse-reward trajectories contain failures, loops, and detours, while summarie

The Undetected Damage of Quantization on Retrieval and How to Fix It

arXiv:2609.24322v1 Announce Type: new Abstract: We show that a quantized model that keeps its classification accuracy still changes 14 to 46% of its top-1 retrieval results, and that aggregate ranking

Topology-Informed Visual Prompting For Vision Language Action Policies

arXiv:2609.23944v1 Announce Type: new Abstract: Vision-language-action (VLA) policies can struggle with manipulation tasks with complex obstacle geometries due to partial observability. These complex

Toward a foundation model for forest point clouds

arXiv:2609.24787v1 Announce Type: new Abstract: Forest inventories increasingly rely on artificial intelligence (AI) models to derive forest attributes from large-scale 3D point clouds. Current models

Towards Training-free Automatic Proxy Discovery via Large Language Models for Mixed Precision Quantization

arXiv:2512.07419v3 Announce Type: replace-cross Abstract: Mixed-Precision Quantization (MPQ) liberates Deep Neural Networks (DNNs) from the Out-Of-Memory (OOM) bottleneck and has garnered increasing r

VividCam: Learning Unconventional Camera Motions from Virtual Synthetic Videos

arXiv:2510.24904v2 Announce Type: replace Abstract: Although recent video generative models are getting more capable of following external camera controls, imposed by either text descriptions or camer

What Matters in Designing World Action Models: An Empirical Study

arXiv:2609.24048v1 Announce Type: new Abstract: World Action Models (WAMs) have emerged as a promising paradigm for generalizable robot control. Despite the growing number of WAM systems, existing wor

AutoViewMem: Self-Configuring Orthogonal Views for Conversational Long-Term Memory

arXiv:2609.21940v1 Announce Type: new Abstract: Long-term memory is essential for large language model (LLM) agents to maintain consistency and personalization over extended interactions. Existing mem

tutorialsarxiv-cs-ai

FOCAL-VLA: Subtask-Guided Geometry Distillation and Implicit World Modeling for Vision-Language-Action Models

arXiv:2609.21228v1 Announce Type: cross Abstract: Vision-language-action (VLA) models built on pretrained vision-language models have demonstrated strong performance across diverse robotic manipulatio

tutorialsarxiv-cs-ai

ForeTac-VLA: A Forecasting-Based Tactile-Vision-Language-Action Model for Contact-Rich Robotic Manipulation

arXiv:2609.20980v1 Announce Type: new Abstract: Vision-language-action (VLA) models have demonstrated strong capabilities in robotic manipulation, yet their reliance on visual perception limits robust

GALA: Geometry-Aware Latent Action Modeling for Vision-Language-Action Model Pretraining across Embodiments

arXiv:2609.21948v1 Announce Type: cross Abstract: Learning large-scale vision-language-action (VLA) models from multi-embodiment datasets remains challenging due to heterogeneous action spaces across

GUARD: Natural Forgetting in Large Reasoning Models via Guided Answer-Reasoning Distillation

arXiv:2609.21677v1 Announce Type: new Abstract: Recent advances in large reasoning models (LRMs) have made machine unlearning more challenging, as protected facts or unsafe rationales may surface in i

tutorialsarxiv-cs-ai

How Many Posterior Samples? Calibrated Stopping for Adaptive Sensing

arXiv:2609.21813v1 Announce Type: cross Abstract: In classification-oriented adaptive sensing, posterior samples characterize uncertainty at the current measurement state and can serve two roles: they

MemeTAG: Keyword-Driven Meme Classification through Tag Embedding Reconstruction

arXiv:2609.20962v1 Announce Type: new Abstract: The proliferation of harmful internet memes poses a significant societal threat, yet their automated classification remains a formidable algorithmic cha

Morphology-Aware Ambiguity Learning for Wafer Defect Decision Support

arXiv:2609.21866v1 Announce Type: new Abstract: Wafer map defect recognition is commonly formulated as a fixed-taxonomy classification problem that assigns each wafer to a single defect class. However