Search: “models”

Conditional Flow Matching for Visually-Guided Acoustic Highlighting

arXiv:2602.03762v3 Announce Type: replace-cross Abstract: Visually-guided acoustic highlighting seeks to rebalance audio in alignment with the accompanying video, creating a coherent audio-visual expe

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Conditional neural control variates for variance reduction in Bayesian inverse problems

DGX agent

arXiv:2602.21357v2 Announce Type: replace-cross Abstract: Bayesian inference for inverse problems involves computing expectations under posterior distributions--e.g., posterior means, variances, or pr

researcharxiv-cs-lg

23 Jun 2026

Applications

Context-Aware Autoregressive Diffusion for Gloss-Wise Sign Language Production

arXiv:2606.21234v1 Announce Type: new Abstract: To generate natural and accurate sentence-level sign language, synthesizing the 'gloss', the fundamental semantic unit, is essential. However, most curr

applicationsarxiv-cs-cv

Continuous-Time Probabilistic Correctors for Uncertainty-Aware Physics-Based Spacecraft Trajectory Forecasting

arXiv:2606.21021v1 Announce Type: new Abstract: Long-horizon spacecraft trajectory forecasting suffers from error accumulation due to the absence of corrective observations in the forecast regime, mak

Counsel: A Meta-Evaluation Dataset for Agentic Tasks

arXiv:2606.21627v1 Announce Type: cross Abstract: As agentic systems tackle increasingly complex multi-step tasks, evaluating their trajectories presents a major bottleneck - human annotation of a sin

Counterfactual learning of new adaptive instructional policies using logged data

arXiv:2606.23015v1 Announce Type: new Abstract: Optimizing instructional policies in Intelligent Tutoring Systems (ITS) typically requires costly online experimentation or student simulators that may

CoVStream: Edge-Cloud Collaboration for Understanding of Long Video Streams

arXiv:2606.22804v1 Announce Type: new Abstract: Long, continuous video streams are an increasingly critical driver of multimedia intelligence. Existing efforts often handle long videos with a sample-e

Dataset-Aware Cold-Start Active Learning for Annotation-Efficient 3D Medical Image Segmentation

arXiv:2606.20765v1 Announce Type: cross Abstract: Deep learning for 3D medical image segmentation requires extensive manual annotations, a major bottleneck in volumetric medical imaging. Active learni

local-aiarxiv-cs-lg

Deep Learning for Soil Moisture Estimation: Fusing Satellite Data with Optimally-Lagged Meteorological Features

arXiv:2606.21475v1 Announce Type: new Abstract: Accurate soil moisture estimation in semi-arid agricultural regions requires integrating remote sensing and meteorological information while accounting

DeformX: A Versatile Co-Simulation Framework for Deformable Linear Objects

arXiv:2606.22116v1 Announce Type: new Abstract: Deformable linear objects (DLOs) such as wires, cables, and ropes are common in robotic manipulation tasks, yet simulating them with both visual realism

safetyarxiv-cs-ro

Applications

DIPBox: A Multi-scale Testing Framework for Tracking Dataset Regeneration

arXiv:2606.21240v1 Announce Type: cross Abstract: Training datasets have tremendous proprietary value and are vulnerable to unauthorized copying. Existing defenses mainly focus on tracking individual

applicationsarxiv-cs-cv

DP-FedSOFIM: Differentially Private Federated Stochastic Optimization using Regularized Fisher Information Matrix

arXiv:2601.09166v3 Announce Type: replace Abstract: Differentially private federated learning (DP-FL) often suffers from slow convergence under tight privacy budgets because the noise required for pri

DVL-DeepONet: A Physics-Guided Operator Learning for Resilient Underwater Navigation

arXiv:2606.23502v1 Announce Type: new Abstract: Autonomous Underwater Vehicles (AUVs) rely heavily on the fusion of inertial sensors and Doppler velocity logs (DVLs) for navigation. In standard autono

agentsarxiv-cs-ro

Efficient Traffic State Prediction With Dynamic Joint Spatio-Temporal Relation Inference

arXiv:2504.08061v2 Announce Type: replace Abstract: Traffic prediction is difficult due to the complex interplay of temporal evolution, spatial interactions, and delayed spatio-temporal propagation ov

Eigenspace-Based Clustering for Personalized System Identification

arXiv:2606.20811v1 Announce Type: cross Abstract: We study the problem of system identification in heterogeneous settings, where different systems may follow distinct underlying dynamics. Existing clu

local-aiarxiv-cs-lg

Enhancing LLMs for Graph Tasks via Graph-aware LoRA Generation

arXiv:2606.22429v1 Announce Type: new Abstract: Graph neural networks (GNNs) tightly couple their input-output parameters to dataset-specific feature spaces and target sets, exhibiting limited transfe

EPSVec: Efficient and Private Synthetic Data Generation via Dataset Vectors

arXiv:2602.21218v2 Announce Type: replace-cross Abstract: High-quality data is essential for modern machine learning, yet many valuable corpora are sensitive and cannot be freely shared. Synthetic dat

Applications

Estimating Learners' Skill Acquisition Without Temporal Information

arXiv:2606.20611v1 Announce Type: cross Abstract: Recent research in educational data mining, especially knowledge tracing, has focused on predicting learners' future knowledge states to support adapt

applicationsarxiv-cs-lg

Flow6D: Discrete-to-Continuous Flow Matching for Efficient and Accurate Category-Level 6D Pose Estimation

arXiv:2606.23293v1 Announce Type: new Abstract: 6D pose estimation is a key task in computer vision and embodied AI, widely used in robotic manipulation, augmented reality, etc. Existing methods direc

ForeHOI: Feed-forward 3D Object Reconstruction from Daily Hand-Object Interaction Videos

arXiv:2602.06226v2 Announce Type: replace Abstract: The ubiquity of monocular videos capturing daily hand-object interactions presents a valuable resource for embodied intelligence. While 3D hand reco

From Driving Videos to Simulatable Scenarios

arXiv:2606.21993v1 Announce Type: cross Abstract: Autonomous vehicles (AVs) face driving scenarios ranging from routine traffic to rare events. To assess safety it is crucial to reproduce these scenar

safetyarxiv-cs-cv

From Zipf's Law to Neural Scaling through Heaps' Law and Hilberg's Hypothesis

arXiv:2512.13491v3 Announce Type: replace-cross Abstract: We inspect the deductive connection between the neural scaling law and Zipf's law -- two statements discussed in machine learning and quantita

GLM 5.2 is already top 10 on OpenRouter this week, sitting right next to Opus 4.8. it's also been really strong in Deep Agents across long-h…

GLM 5.2 is already top 10 on OpenRouter this week, sitting right next to Opus 4.8. it's also been really strong in Deep Agents across long-horizon coding, big context, tool use, and verifying work bef

agentsharrison-chase--x

GLM-5.2 is available in Perplexity's Agent API. Just tested it, and it's powerful when paired with the Search SDK inside a sandbox. - Spin u…

GLM-5.2 is available in Perplexity's Agent API. Just tested it, and it's powerful when paired with the Search SDK inside a sandbox. - Spin up a sandbox environment - Call the web search tool (people s

agentszhipu-ai--x

GRAIN: Group Aggregation via Min-Norm Objective

arXiv:2606.22917v1 Announce Type: new Abstract: Learning instability is a long-standing problem across machine learning, but it is especially acute in the overparameterized regime that defines modern

Hard or Just Unreached? Diagnosing the Sampling Blind Spot in Math-Reasoning Difficulty Estimation

arXiv:2606.19636v2 Announce Type: replace Abstract: Math and science reasoning benchmarks rely on pass@k, the fraction of sampled chains that reach gold, as the canonical per-example difficulty signal

Heterogeneous Policy Networks for Composite Robot Team Communication and Coordination

arXiv:2606.20962v1 Announce Type: new Abstract: High-performing human-human teams learn intelligent and efficient communication and coordination strategies to maximize their joint utility. These teams

safetyarxiv-cs-ro

Horizon Adaptive Offline Policy Learning via Value Stitching

arXiv:2606.21136v1 Announce Type: new Abstract: Learning accurate value functions plays a decisive role for reinforcement learning (RL) agents to solve long-horizon, complex tasks. Conventional tempor

Tutorials

How Businesses Are Building Specialized AI They Can Trust

Companies are asking how to build specialized AI that fits with the way their workflows actually run. The first wave of enterprise AI was about access. Companies experimented with new frontier and ope

tutorialsnvidia-blog

Humanoid-OmniOcc: Stereo-Based Full-View Occupancy Dataset for Embodied AI

arXiv:2606.22971v1 Announce Type: cross Abstract: Occupancy prediction at voxel-level granularity is essential for safe robotic navigation and interaction in complex environments. Existing occupancy d

agentsarxiv-cs-cv

Hardware

i dont think anyone is correctly doing the math around how SpaceX, the NeoCloud+NeoLab, is currently going to market? SpaceX has already rec…

i dont think anyone is correctly doing the math around how SpaceX, the NeoCloud+NeoLab, is currently going to market? SpaceX has already recouped about HALF its investment in Cursor, in compute deals.

hardwareswyx--x

Influencer Cartels

arXiv:2405.10231v3 Announce Type: replace-cross Abstract: Social media influencers account for a growing share of marketing worldwide. We demonstrate the existence of a novel form of market failure in

Integrated Marketing Attribution: A Bayesian Framework for Privacy-Safe Granular Measurement Anchored in MMM

arXiv:2606.16878v3 Announce Type: replace Abstract: Retail marketing measurement increasingly requires granular campaign-level insights without relying on user-level tracking. However, the two dominan

ITNet: A Learnable Integral Transform That Subsumes Convolution, Attention, and Recurrence

arXiv:2606.19538v2 Announce Type: replace-cross Abstract: Convolutional networks, recurrent networks, and transformers each encode different inductive biases -- locality, sequential memory, and conten

local-aiarxiv-cs-lg

Johnson-Lindenstrauss Lemma Guided Network for Efficient 3D Medical Segmentation

arXiv:2509.22307v2 Announce Type: replace Abstract: Lightweight 3D medical image segmentation remains constrained by a fundamental extit{``efficiency / robustness conflict''}, particularly when proces

KITE: Decoupling Kinematics and Interaction for Zero-Shot Cross-Embodiment Manipulation

arXiv:2606.22113v1 Announce Type: new Abstract: Generalizing manipulation policies across robot embodiments remains difficult because standard policies entangle task reasoning with embodiment-specific

safetyarxiv-cs-ro

Tutorials

LEViL: Label-Efficient Video Learning via Zero-Shot Distillation over VLM-Generated Pseudo-Label Spaces

arXiv:2606.21358v1 Announce Type: new Abstract: Supervised video pretraining is a common transfer learning practice for improving downstream action recognition performance. However, it requires large-

tutorialsarxiv-cs-cv

LLM-Guided Test-Time Discovery of Quantum-Chemical Approximation Algorithms

arXiv:2606.20729v1 Announce Type: cross Abstract: Quantum chemistry simulations underpin modern materials discovery, yet their impact is limited by steep computational cost and dependence on fixed app

agentsarxiv-cs-lg

LOLLA: Deep Reinforcement Learning for Closed-Loop Link Adaptation Towards a GPU-Accelerated AI-RAN

arXiv:2606.23110v1 Announce Type: cross Abstract: Outer-loop link adaptation (OLLA) is widely deployed in 5G NR to track channel variations, yet its reliance on first-order, single-bit feedback degrad

LSTM Variants for Chaotic Dynamical Systems: An Empirical Study on the Lorenz Attractor

arXiv:2606.22662v1 Announce Type: new Abstract: Forecasting chaotic dynamical systems such as the Lorenz attractor is notoriously difficult: small numerical errors are amplified exponentially over lon

LVQAC: Lattice Vector Quantization Coupled with Spatially Adaptive Companding for Efficient Learned Image Compression

arXiv:2304.12319v2 Announce Type: replace-cross Abstract: Recently, numerous end-to-end optimized image compression neural networks have been developed and proved themselves as leaders in rate-distort

MeshFlow: Mesh Generation with Equivariant Flow Matching

arXiv:2606.23489v1 Announce Type: cross Abstract: Meshes are among the most common 3D scene representations, but directly generating meshes is challenging because the representation contains important

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning

arXiv:2606.21943v1 Announce Type: new Abstract: Reinforcement learning (RL) has become central to LLM post-training, yet the methods that dominate current pipelines, PPO and GRPO, represent only a nar

Odoriko: A Shape-Aware Multimodal Diffusion Framework for Human Motion

arXiv:2606.21135v1 Announce Type: new Abstract: Human motion generation has been widely studied across diverse input modalities, text, music, and video, and recent efforts have unified these into sing

Omega: Operator-based Mixture Ensemble for Generative Assimilation

arXiv:2606.20920v1 Announce Type: new Abstract: Characterizing non-Gaussian posterior distributions in partially observed high-dimensional nonlinear systems remains a fundamental challenge in data ass

On-Manifold Variational Learning with Heat-Kernel Priors

arXiv:2606.18658v2 Announce Type: replace Abstract: Learning unsupervised representations of medical imaging cohorts can reveal clinically meaningful prototypes without expert labels, which are often

On the Sparsity-Storage-Accuracy Tradeoff in Parsimoniously Activated Dictionary Learning

arXiv:2606.22352v1 Announce Type: new Abstract: Dictionary learning has long been studied from both optimization and probabilistic perspectives. While formulations with element-wise sparsity regulariz

OphthaDT: Generative Digital Twins for Forecasting Visual Acuity Trajectories in Ophthalmology

arXiv:2606.22101v1 Announce Type: cross Abstract: Precision medicine in ophthalmology requires accurate longitudinal predictions, but the fragmented nature of multimodal clinical data remains a barrie