Search: “models”

Probabilistic electrical power demand forecasting with uncertainty quantification

arXiv:2609.34120v1 Announce Type: new Abstract: The majority of research on electricity consumption forecasting has focused on deterministic approaches, which generate a single point estimate for each

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Research

Proxy2World: Learning to Generate Worlds From Lightweight Proxies without Seeing Them

DGX agent

arXiv:2609.35023v1 Announce Type: new Abstract: Lightweight scene proxies let creators control scene layout and motion while leaving room for imagination in appearance, lighting, and visual effects. H

researcharxiv-cs-cv

29 Sept 2026

PulseQuant: Propagation-Guided Subspace Correction for 4-Bit Video Diffusion Transformers

arXiv:2609.33384v1 Announce Type: new Abstract: Quantization errors in video diffusion transformers can be amplified or attenuated by subsequent denoising updates, making local reconstruction error an

local-aiarxiv-cs-cv

QAM: Quadratic-Accurate Checkpoint Merging via Sequential Consistency

arXiv:2609.35168v1 Announce Type: new Abstract: Saved checkpoints record states along a training trajectory, but generally do not determine the updates at states that would be visited under a differen

local-aiarxiv-cs-lg

QuacamFM: Quaternion-Constrained Flow Matching for Camera Pose Estimation

arXiv:2609.32455v1 Announce Type: new Abstract: Camera pose estimation from multi-view images remains a challenge in computer vision. Traditional methods often address this problem using Structure-fro

R2T: Rule-Encoded Loss Functions for Sequence Tagging in Low-Resource Languages

arXiv:2510.13854v2 Announce Type: replace-cross Abstract: We introduce Rule-to-Tag (R2T), a framework that turns linguistic rules into the training signal for neural sequence taggers in low-resource l

ResDiffFRG: Residual Diffusion for Multiple Appropriate Facial Reaction Generation

arXiv:2609.33749v1 Announce Type: new Abstract: In dyadic human speaker-listener conversations, the listener's facial reactions allows the speaker to accurately perceive the listener's emotional state

agentsarxiv-cs-lg

Rethinking the Fully Hyperbolic Vision Transformer in Polar Coordinates

arXiv:2609.32899v1 Announce Type: new Abstract: Hyperbolic space can embed intrinsic hierarchies in data with low distortion due to the exponential growth of volume with distance from the origin. Howe

ReVision3D: Attribution-Guided Recursive Self-Improvement for 3D Medical Perception

arXiv:2609.32984v1 Announce Type: new Abstract: Recursive self-improvement (RSI) offers a promising path for overcoming the limited visual capability of current medical imaging agents. Yet applying RS

Rondo: Unsupervised Discovery of Recurring Temporal Structure

arXiv:2609.32500v1 Announce Type: new Abstract: Many real-world time series data exhibit structural properties at multiple scales, from short, recurring units to complex sequences composed of these un

Tutorials

S^2COPE: Self-Supervised Concept Discovery via Preference Learning

arXiv:2606.14586v2 Announce Type: replace Abstract: Self-supervised learning can learn useful representations from unlabeled images. Yet these representations remain largely opaque, making it difficul

tutorialsarxiv-cs-cv

SemReward-VL: Semantic Reward-Guided Video-Language Adaptation for Developmental Behavior Assessment

arXiv:2609.33082v1 Announce Type: new Abstract: Developmental screening videos show how children perform specific behaviors, but clinical records usually contain outcomes rather than descriptions of w

safetyarxiv-cs-cv

seq2cause: One Autoregressive Backbone, Four Causal Discovery Tasks in Event Sequences

arXiv:2609.31801v1 Announce Type: new Abstract: Complex systems such as vehicles, patients, or genomes emit discrete event sequences whose operative question is causal, not predictive: which events ca

SNIP++: Fine-Grained Symbolic-Numerical Alignment for Symbolic Regression

arXiv:2609.31965v1 Announce Type: cross Abstract: Mathematical expressions and the numerical behavior they produce are two views of the same underlying function, and connecting them is central to scie

safetyarxiv-cs-lg

SPOC-Net: Single-Primitive Online Composition Network for GNSS Jamming Set Recognition

arXiv:2609.34875v1 Announce Type: new Abstract: Reliable positioning, navigation, and timing support intelligent transportation, autonomous systems, and space-air-ground integrated networks. However,

agentsarxiv-cs-cv

Temporal-Attention Head Specialization During Video Diffusion Training

arXiv:2609.31654v1 Announce Type: new Abstract: Video diffusion transformers depend on temporal attention to coordinate information across frames, yet nearly everything known about this mechanism come

TIDE: Teacher-Student Transition via Informative Distillation and Exploration for Agentic RL

arXiv:2609.35058v1 Announce Type: new Abstract: Effective multi-turn agents require interaction strategies that coordinate information gathering, actions, and feedback over long horizons. GRPO is a re

safetyarxiv-cs-lg

Universality and Generalization of Causal Transformers Across Context Lengths

arXiv:2609.35055v1 Announce Type: new Abstract: Long contexts are central to modern transformer systems, but most expressivity results choose a different network for each fixed sequence length. We stu

Using Machine Learning to Investigate Predictors of Fasting Blood Glucose: Insights into Circadian Timing and Age Interactions

arXiv:2609.32386v1 Announce Type: new Abstract: Impaired glucose regulation is a major contributor to metabolic dysfunction and type 2 diabetes. This study developed an interpretable machine-learning

V-Gym: Enhancing Agentic Visual Reasoning via Skill-Data Co-Evolution

arXiv:2609.34682v1 Announce Type: new Abstract: Advances in multimodal understanding, reasoning, and tool use enable agents to tackle increasingly complex visual reasoning tasks. By distilling past ex

agentsarxiv-cs-cv

VisionHOPE: Visual Backbones as Self-Modifying Learning Systems

arXiv:2609.33325v1 Announce Type: new Abstract: Visual backbones have evolved from Convolutional Neural Networks (CNNs) with local aggregation to Vision Transformers (ViTs) with global interactions, S

local-aiarxiv-cs-cv

What everyone was talking about at WeAreDevelopers World Congress North America

After 237 talks across eight stages, code review emerged as the bottleneck for AI-generated code. Here are the production eval, sandbox, context, and agent experience themes that kept showing up. The

agentsarize-ai

Tutorials

When Can Attention Heads Be Statically Defined?

arXiv:2609.34650v1 Announce Type: new Abstract: Some attention heads learn similar patterns across inputs. Reusing these patterns could reduce training cost by avoiding repeated query-key score comput

tutorialsarxiv-cs-lg

When local gains fail to transfer: Frozen Earth-observation embeddings across wildfires

arXiv:2609.34602v1 Announce Type: new Abstract: Frozen Earth-observation embeddings are judged almost entirely by spatially blocked cross-validation inside one study region. We show that this number d

When Should the Count Change? Learning State Maintenance for Causal Video Counting

arXiv:2609.35416v1 Announce Type: new Abstract: Continuous video counting requires distinguishing new observations from new objects or completed events. We introduce StaMina (State Maintenance), which

applicationsarxiv-cs-cv

Who Is Left of Whom? Tracing Spatial Evidence and Role Binding in Relative-Position Reasoning

arXiv:2609.35486v1 Announce Type: cross Abstract: High instance-level accuracy can mask inconsistencies in spatial reasoning when objects exchange positions or their roles are reversed in the query. T

WSM-Aware HRI: An IoT-Enhanced Framework for Early Detection and Norm-Guided Repair of Failures with LLM Guidance

arXiv:2609.32336v1 Announce Type: new Abstract: Human-robot interaction (HRI) failures remain a major barrier to deploying robots in real-world environments. Prior work often treats failures as isolat

safetyarxiv-cs-ro

A Flatness-Generalization Relation in the Teacher-Student Tree-Committee Machine

arXiv:2609.31101v1 Announce Type: cross Abstract: The flatness of the loss landscape at a minimizer is a widely used heuristic for reasoning about neural-network generalization, yet evidence for this

A Flow Matching Framework for Neural Representational Dissimilarity

arXiv:2609.31544v1 Announce Type: new Abstract: Neural representational dissimilarity quantifies differences between neural response distributions, and is essential for comparing neural codes across s

researcharxiv-cs-ai

Accuracy Evaluation of INS/ZUPT Filtering Methods Based on Different Geometric Error Definitions

arXiv:2609.31057v1 Announce Type: new Abstract: Geometric filters have recently been introduced to improve the accuracy and consistency of inertial-based integrated navigation systems. Error states we

researcharxiv-cs-ro

Adapting Personalized Speech Enhancement for Low-Latency Audio-Visual Target-Speaker Extraction

arXiv:2609.30631v1 Announce Type: cross Abstract: Online audio-visual target-speaker extraction aims to remove competing voices while preserving speech quality and bounding lookahead. Existing extract

Adaptive multi-resolution Gaussian processes: Scalable exact inference with naturally data-sparse covariance matrices

arXiv:2609.30348v1 Announce Type: cross Abstract: Gaussian processes constitute a cornerstone of probabilistic machine learning, yet scaling them to large datasets typically forces a trade-off between

researcharxiv-cs-ai

Aerial Manipulation in the Wild with Onboard Perception, Policy Learning, and Whole-Body Control

arXiv:2609.30521v1 Announce Type: new Abstract: Aerial manipulation in outdoor environments remains challenging due to the simultaneous requirements of reliable state estimation, stable aerial motion,

safetyarxiv-cs-ro

Agentic AI is breaking the token meter, and enterprises need a plan for what comes next

Per-token pricing was the best thing to happen to enterprises looking to experiment with artificial intelligence, but it may be the worst thing for AI in production. That’s the quandary at the center

agentssiliconangle

Agentic AI security pushes vendors toward shared safeguards

Agentic AI security is becoming a cross-industry challenge as autonomous systems move among products and platforms. Okta Inc. argues that building trust will require coordinated safeguards rather than

agentssiliconangle

Industry

AI is supercharging hacking, and your local hospitals and banks aren’t ready

In March, Janice Malone began getting calls about suspicious activity from her nonprofit organization, Vivian's Door. Vivian's Door, headquartered in Alabama, typically provided training, resources, a

industrythe-verge-ai

AppDirect acquires interactive AI avatar firm Soul Machines for advisers and businesses

AppDirect Inc., the cloud-based business commerce platform and marketplace provider, today announced it acquired Soul Machines Ltd., an artificial intelligence human-like avatar experience provider, t

applicationssiliconangle

Asymmetric Classifier-Free Guidance for Target-Speaker ASR

arXiv:2609.30476v1 Announce Type: cross Abstract: Target-speaker automatic speech recognition (TS-ASR) must identify and transcribe a desired speaker under varying overlap and noise conditions. These

researcharxiv-cs-cl

Bayesian Tensor Autoencoder with Physics-informed Predictive Prior for Multi-dimensional Time Series Anomaly Detection

arXiv:2609.31157v1 Announce Type: new Abstract: Multi-dimensional time series, inherently tensorial, are common in practice. Despite great progress in time series anomaly detection, most existing meth

Bayesian Uncertainty Quantification for fMRI Functional Connectivity via Simulation-Based Inference

arXiv:2609.30445v1 Announce Type: cross Abstract: Optimizing fMRI scan duration and spatial resolution is critical for experimental design, yet traditional correlation-based approaches cannot quantify

Cognitive Skills in the Age of AI: Computing Students and Experts Perceptions

arXiv:2609.31272v1 Announce Type: cross Abstract: AI is becoming increasingly integrated into daily workflows, especially in computing. We are gradually shifting towards an AI-rich future, an impendin

researcharxiv-cs-ai

Hardware

Compress What You See, Not What You Say: Anchored Context Distillation for Latent-Observation Software Engineering Agents

arXiv:2609.31430v1 Announce Type: new Abstract: Tool observations dominate the context of software-engineering agents, making long interaction histories costly to maintain. Existing context compressio

hardwarearxiv-cs-ai

Conditional Predictive Sufficient Statistics for Visual Representation Learning

arXiv:2609.30647v1 Announce Type: new Abstract: A useful visual representation is a statistic of the observed past that retains the latent factors shared with the future and discards patch-private noi

Coupled Usage-Sense Processes: Temporal and Attributable Lexical Semantic Change

arXiv:2609.30974v1 Announce Type: new Abstract: Lexical semantic change is usually summarized by a scalar distance between independently sampled period distributions. This measures how much a word cha

researcharxiv-cs-cl

DeepEdu-v1: Efficient and Scalable Agentic LLMs for Vietnamese Education

arXiv:2609.31568v1 Announce Type: new Abstract: AI tutoring could markedly improve learning outcomes for students in developing regions such as Vietnam, yet the two obvious paths both fall short. Clou

local-aiarxiv-cs-ai

DiffusionShadow: Diffusion-based Shadow Caching for Neural Volume Rendering

arXiv:2609.30658v1 Announce Type: cross Abstract: Implicit neural representations (INRs) have gained momentum in scientific visualization due to their compactness and scalability to large datasets, ma

Do Neural Networks Preserve Case Structure? Case-Based Decomposition, Interpretation, and Decision Consistency

arXiv:2607.11347v2 Announce Type: replace Abstract: Neural networks increasingly inform consequential decisions, making their reliability increasingly important. Yet their internal mechanisms provide

applicationsarxiv-cs-ai

Enhancing Assessment of Self-Consistency in LLM Explanations using Perturbation Strength

arXiv:2609.30849v1 Announce Type: new Abstract: Prior work has examined the self-consistency of LLM-generated explanations using surface-level perturbation methods. However, the strength of these pert

researcharxiv-cs-cl