Search: “models”

Full Nonlinear Nonholonomic Dynamics and Motion Analysis of a 3-DoF Underactuated Spherical Rolling Robot

arXiv:2606.22169v1 Announce Type: new Abstract: This paper presents a full nonlinear constrained dynamic model of MonoRollBot, a novel 3-DoF spherical rolling robot driven by a single motor, a lead-sc

researcharxiv-cs-ro

Model Releases

GeoRouteNet: Geometry-Enhanced Non-Autoregressive Neural Solver for the Traveling Salesman Problem

DGX agent

arXiv:2606.22776v1 Announce Type: new Abstract: The traveling salesman problem (TSP) is a canonical NP-hard combinatorial optimization benchmark that tests the representational capacity and generaliza

model-releasesarxiv-cs-lg

23 Jun 2026

HilDA: Hierarchical Distillation with Diffusion for Advancing Self-Supervised LiDAR Pre-training

arXiv:2606.20189v2 Announce Type: replace Abstract: Leveraging Vision Foundation Models (VFMs) for camera-to-LiDAR knowledge distillation offers a promising solution to the scarcity of annotated data

safetyarxiv-cs-cv

How Omio is building the future of conversational travel

Omio, a travel platform, is leveraging OpenAI's technology to enhance its services through conversational AI capabilities. This implementation likely enables customers to search for and book travel op

model-releasesopenai

HUGE-Bench: A Benchmark for High-Level UAV Vision-Language-Action Tasks

arXiv:2603.19822v2 Announce Type: replace Abstract: Existing UAV vision-language navigation (VLN) benchmarks have enabled language-guided flight, but they largely focus on long, step-wise route descri

IMAGIN-4D: Image-Guided Controllable Interaction Generation

arXiv:2606.23675v1 Announce Type: new Abstract: Generating human-object interactions (HOI) is central to character animation, robotics, AR/VR, and embodied AI. Recent HOI generation methods synthesize

Integrating Facial Generation into Full-Duplex Spoken Dialogue Systems

arXiv:2606.21970v1 Announce Type: cross Abstract: Full-duplex spoken dialogue models, such as Moshi, enable natural, low-latency voice conversations. However, they remain limited to the audio modality

safetyarxiv-cs-cv

Interpretable Kolmogorov-Arnold Network with Feature-Isolated Temporal Attention Mechanism for Electricity Load Forecasting

arXiv:2606.23425v1 Announce Type: new Abstract: Accurate electricity load forecasting is a crucial prerequisite for stable power system operations. While prevalent deep learning models present competi

Jury Duty: Calibration and Orientation Failures in MLLM-as-a-Judge Under Cultural Ambiguity

arXiv:2606.20676v1 Announce Type: new Abstract: MLLM-as-a-Judge is conventionally validated by agreement with human annotations, but this metric is undefined when the human pool is culturally heteroge

Tutorials

Leveraging AutoML for Sustainable Deep Learning: A Multi-Objective HPO Approach on Deep Shift Neural Networks

arXiv:2606.23208v1 Announce Type: new Abstract: Deep Learning (DL) has advanced various fields by extracting complex patterns from large datasets. However, the computational demands of DL models pose

tutorialsarxiv-cs-lg

LOGOS: LiDAR-Only Gaussian Elevation Splatting for Unified Tiny Obstacle Segmentation

arXiv:2606.21527v1 Announce Type: cross Abstract: Robust obstacle segmentation is essential for the safety of intelligent robots, where LiDAR-based perception systems play a fundamental role in the ro

Mat-Pref: Verifiable-Reward Training Improves Compositional Reasoning in Inorganic Materials

arXiv:2606.21830v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) has driven rapid progress in mathematical and code reasoning, but when extended to science, existi

Metric-Dependent Annotation Saturation for Learning from Label Distributions

researchapple-ml-research

When annotators disagree on a label, the disagreement itself carries signal—and the number of annotators needed to capture it depends on the evaluation metric. We fine-tune NLI models on label distrib

Local Ai

MIRAGE: Stealthy Visual Prompt Injection for Vulnerability Detection in Web Agents

arXiv:2606.20717v1 Announce Type: new Abstract: Multimodal Large Language Model (MLLM)-based web agents provide practical, high-precision solutions for visual browser automation; however, they inheren

local-aiarxiv-cs-cv

Mixture-of-Experts Graph Transformers for Interpretable Particle Collision Detection

arXiv:2501.03432v3 Announce Type: replace Abstract: The Large Hadron Collider at CERN produces immense volumes of complex data from high-energy particle collisions, demanding sophisticated analytical

Morphology-Aware Multimodal Representation Learning for Insect Phylogenetic Reconstruction

arXiv:2606.22077v1 Announce Type: new Abstract: Morphological traits provide important evidence for phylogenetic reconstruction and evolutionary relationship analysis. Recent image-based approaches ha

MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learninga

arXiv:2606.22220v1 Announce Type: new Abstract: Memorization in machine learning models enables high performance on rare in-distribution samples by capturing their atypical patterns. However, it also

researcharxiv-cs-cv

Applications

Neural Concept Verifier: Scaling Prover-Verifier Games via Concept Encodings

arXiv:2507.07532v4 Announce Type: replace Abstract: While Prover-Verifier Games (PVGs) offer a promising path toward verifiability in nonlinear classification models, they have not yet been applied to

applicationsarxiv-cs-lg

New Smooth Loss functions for Robust Regression that Closely Approximate Absolute Error and Provide Improved Performance on Datasets With Significant Outliers

arXiv:2606.22068v1 Announce Type: new Abstract: The performance of supervised machine learning models is directly related to the quality of the training dataset. In particular, the presence of signifi

Next-Gen CAPTCHAs: Leveraging the Cognitive Gap for Scalable and Diverse GUI-Agent Defense

arXiv:2602.09012v2 Announce Type: replace Abstract: The rapid evolution of GUI-enabled agents has rendered traditional CAPTCHAs obsolete. While previous benchmarks like OpenCaptchaWorld established a

OFMU: Optimization-Driven Framework for Machine Unlearning

arXiv:2509.22483v2 Announce Type: replace Abstract: Large language models deployed in sensitive applications increasingly require the ability to unlearn specific knowledge, such as user requests, copy

safetyarxiv-cs-lg

Agents

OmniSpace: Efficient Geometry Awareness for Autonomous Vehicles MLLMs

arXiv:2606.22617v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable performance on 2D visual tasks, yet enhancing their spatial intelligence for real-worl

agentsarxiv-cs-cv

Tutorials

On the Memorization Behavior of LLMs in Generative Recommendation: Observations, Implications, and Training Strategies

arXiv:2606.17276v3 Announce Type: replace-cross Abstract: Generative recommendation (GR) has emerged as a promising direction for recommender systems. Recently, large language models (LLMs) have been

tutorialsarxiv-cs-lg

One Size does not Fit All: Heterogeneous Latent Space Alignment for Unsupervised Domain Adaptation

arXiv:2606.21415v1 Announce Type: new Abstract: Domain shift remains a major obstacle to the reliable deployment of machine learning models in high-stakes environments such as healthcare. While Domain

safetyarxiv-cs-lg

Orthogonal Discrepancy Kernels for Learning with Partial Physics

arXiv:2606.21199v1 Announce Type: cross Abstract: We introduce a semi-parametric framework for nonlinear system identification, which decouples discrepancy functions from physics-based components. Ort

OVIG: Optimistic Verification of AI Training Integrity via Gradient Signals

arXiv:2606.21045v1 Announce Type: cross Abstract: The rapid growth of AI has increased the demand for domain-specific post-training, while the cost and specialization of accelerator infrastructure pus

PHOEBI: An Open-World Benchmark for Bacterial Identification in Phase-Contrast Microscopy

arXiv:2606.22890v1 Announce Type: new Abstract: Optical microscopy enables rapid, label-free imaging of live bacteria and is the standard instrument for species identification across clinical, environ

Physics-Guided Fully Convolutional Spatiotemporal Learning Toward Digital-Twin-Enabled Microstructure Evolution Prediction

arXiv:2606.20983v1 Announce Type: new Abstract: Understanding and predicting microstructure evolution is central to materials design, yet purely data-driven spatiotemporal learning models often suffer

Polycepta: Object-Centric Appearance Estimation for Multi-Object Tracking

arXiv:2606.23604v1 Announce Type: new Abstract: The tracking-by-detection paradigm in multi-object tracking (MOT) typically relies on static appearance descriptors to complement motion estimation. How

Precision Recall Controllable Radiology Report Generation via Hybrid Natural Language and Clinical Reward Learning

arXiv:2606.21447v1 Announce Type: cross Abstract: Automated radiology report generation (RRG) has gained increasing attention because it can reduce the heavy workload of clinical report writing. Howev

Rebuttals Move Peer-Review Scores, but Initial-Review Structure Bounds the Movement

arXiv:2606.22166v1 Announce Type: cross Abstract: Author rebuttals are the main post-submission window in peer review, but their effect on reviewer scores remains hard to measure because score updates

Applications

Robust Zero-Shot Generalization for Open-Vocabulary Action Recognition via Task Arithmetic

arXiv:2606.20734v1 Announce Type: new Abstract: Open Vocabulary Action Recognition (OVAR) enables the recognition of novel actions by leveraging vision-language representations, overcoming the limitat

applicationsarxiv-cs-cv

Robustness Cannot be Reduced to Regularization: Studying Adversarial Training Beyond the Linear Case

arXiv:2606.21488v1 Announce Type: new Abstract: The vulnerability of ML models to adversarial examples has recently emerged as a major concern. While adversarial training is one of the most effective

RT-DocLayout: Real-Time End-to-End Document Layout Analysis with Reading Order in the Wild

arXiv:2606.23344v1 Announce Type: new Abstract: Accurate document layout analysis remains a critical bottleneck for document parsing systems, due to the intricate coupling among heterogeneous document

RubricRL: Simple Generalizable Rewards for Text-to-Image Generation

arXiv:2511.20651v2 Announce Type: replace Abstract: Reinforcement learning (RL) has recently emerged as a promising approach for aligning text-to-image generative models with human preferences. A key

safetyarxiv-cs-cv

Local Ai

Scaling Diverse Language Generation for 3D Visual Grounding

arXiv:2606.20946v1 Announce Type: cross Abstract: Developing robust models for 3D visual grounding (3DVG), the localization of entities in a 3D scene described in natural language, is important for en

local-aiarxiv-cs-cv

Hardware

SCENIC: Semantic-Conditioned Edge-Aware Neural Framework for Structured IoT Command Generation

arXiv:2606.22296v1 Announce Type: new Abstract: Edge Internet of Things (IoT) agents are often constrained by memory capacity, privacy requirements, communication latency, and recurring inference cost

hardwarearxiv-cs-lg

Streaming Dense Voxel Representations for 3D Occupancy Prediction

arXiv:2503.22087v3 Announce Type: replace Abstract: In this paper, we explore dense voxel streaming for accurate and efficient 3D occupancy prediction. While dense voxel representations offer fine-gra

Subject-Level Unknown-Identity Identification from Leap Motion Controller 2 Hand Landmarks

arXiv:2606.22986v1 Announce Type: new Abstract: This work studies subject recognition from Leap Motion Controller 2 (LMC2) hand landmark data under a subject-level unknown-identity identification prot

Surgical Anatomy Recognition with Context Learning using Foundation Representations

arXiv:2606.22124v1 Announce Type: new Abstract: Accurate recognition of anatomical structures is essential for safe and effective minimally invasive surgery (MIS), yet it remains underexplored in surg

researcharxiv-cs-cv

T-MOR: Learning Motion-Aware Skeleton Representations for Human Action Recognition

arXiv:2606.21607v1 Announce Type: new Abstract: Vision-language models such as CLIP have recently achieved strong performance on a wide range of visual understanding tasks. However, most existing mode

researcharxiv-cs-cv

Task-Differentiated Atomic Skill Expansion and Routing for Continual Learning Across Highly Heterogeneous Tasks

arXiv:2606.21307v1 Announce Type: new Abstract: Continual learning (CL) is commonly studied under the assumption that sequential tasks are semantically related or structurally similar. However, in hig

Thalia: A Global, Multi-Modal Dataset for Volcanic Activity Monitoring

arXiv:2505.17782v4 Announce Type: replace Abstract: Monitoring volcanic activity is of paramount importance to safeguarding lives, infrastructure, and ecosystems. However, only a small fraction of kno

The Power of Light: Improving Synthetic-to-Real Domain Adaptation through Physically-Based Indirect Illumination

arXiv:2606.22574v1 Announce Type: new Abstract: While synthetic data generation resolves the manual labeling bottleneck in computer vision, minimizing the syn-to-real domain gap requires optimizing re

Towards Practical Lossless Neural Compression for LiDAR Point Clouds

arXiv:2603.25260v2 Announce Type: replace Abstract: LiDAR point clouds are fundamental to various applications, yet the extreme sparsity of high-precision geometric details hinders efficient context m

Towards Robust Training in NNGPT AutoML Pipeline: A Loss-Optimizer Pairing Selection Study

arXiv:2606.20933v1 Announce Type: new Abstract: The choice of loss function and optimizer is an important decision, that shapes further model training. Yet automated architecture search pipelines (Aut

Local Ai

Transcribing Bengali Text with Regional Dialects to IPA using District Guided Tokens

arXiv:2403.17407v4 Announce Type: replace-cross Abstract: Accurate transcription of Bengali text to the International Phonetic Alphabet (IPA) is a challenging task due to the complex phonology of the

local-aiarxiv-cs-lg

VeriEvol: Scaling Multimodal Mathematical Reasoning via Verifiable Evol-Instruct

arXiv:2606.23543v1 Announce Type: cross Abstract: Scaling reinforcement learning for visual mathematical reasoning requires more than generating harder questions: as data volume grows, the reward labe