Search: “models”

Shoot from the HIP: Hessian Interatomic Potentials without derivatives

arXiv:2509.21624v3 Announce Type: replace Abstract: Fundamental tasks in computational chemistry, from transition state search to vibrational analysis, rely on molecular Hessians, which are the second

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SICAGE: Speaker-Independent Culture-Aware Gesture Generation using TED4C-L Dataset

DGX agent

arXiv:2606.30001v1 Announce Type: new Abstract: Recent co-speech gesture generation methods often overlook cultural differences, limiting their effectiveness in human-agent interaction. Moreover, cult

agentsarxiv-cs-cv

30 Jun 2026

SoccerNet 2026 Player-Centric Ball Action Spotting: Per-Player Attention with Agreement-Based Ensembling

arXiv:2606.28389v1 Announce Type: new Abstract: We present our submission to the SoccerNet 2026 Player-Centric Ball Action Spotting challenge, which uses a two-stage pipeline: a Track-Aware Action Det

Solver-Integrated Adversarial Attacking and Training of Neural Operators

arXiv:2510.18989v2 Announce Type: replace Abstract: Neural operators are commonly utilized as fast surrogates for numerical solvers in PDE problems, mapping input functions to solution functions. Howe

Hardware

Spanning the Visual Analogy Space with a Weight Basis of LoRAs

arXiv:2602.15727v2 Announce Type: replace-cross Abstract: Visual analogy learning enables image editing via demonstration rather than textual description, allowing users to specify complex transformat

hardwarearxiv-cs-ai

SpecMind: Cognitively Inspired, Interactive Multi-Turn Framework for Postcondition Inference

arXiv:2602.20610v3 Announce Type: replace-cross Abstract: Specifications are vital for ensuring program correctness, yet writing them manually remains challenging and time-intensive. Recent large lang

safetyarxiv-cs-cl

Sphere-VIO: Fast and Robust Visual-Inertial Odometry via Unified Spherical Representation for Heterogeneous Multi-Camera Systems

arXiv:2606.29910v1 Announce Type: new Abstract: Multi-camera visual-inertial odometry (VIO) overcomes the inherent limitations of pure visual systems by expanding the field of view. However, existing

safetyarxiv-cs-ro

Towards Biosignals-Free Autonomous Prosthetic Hand Control via Imitation Learning

arXiv:2506.08795v2 Announce Type: replace-cross Abstract: Limb loss affects millions globally, impairing physical function and reducing quality of life. Most traditional surface electromyographic (sEM

agentsarxiv-cs-ai

Applications

Towards Improved Anomaly Detection for Cloud Cybersecurity via Graph Neural Networks

arXiv:2606.28923v1 Announce Type: new Abstract: Detecting security threats in an organization's cloud computing environment has become necessary due to the increased reliance on cloud infrastructure.

applicationsarxiv-cs-lg

UCOB: Learning to Utilize and Evolve Agentic Skills via Credit-Aware On-Policy Bidirectional Self-Distillation

arXiv:2606.29502v1 Announce Type: new Abstract: Skill memories can improve agentic reinforcement learning by reusing past experience as textual guidance, but retrieved skills are not oracular: they ma

local-aiarxiv-cs-ai

UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention

arXiv:2510.16325v3 Announce Type: replace Abstract: Ultra-high-resolution text-to-image generation is increasingly vital for applications requiring fine-grained textures and global structural fidelity

UniTriSplat: A Unified 3D Gaussian Splatting Framework with Uniform Spherical Rasterization for Universal Cameras

arXiv:2606.29794v1 Announce Type: new Abstract: Existing 3D Gaussian Splatting (3DGS) frameworks rely on camera-specific rasterization, suffering from inconsistent solid-angle sampling and degraded pe

UniVAD v2: Unified Visual Anomaly Detection via Support-Conditioned Boundary Construction

arXiv:2606.29714v1 Announce Type: new Abstract: Unified visual anomaly detection seeks to train a single detector that can be deployed across categories, domains, and application scenarios. In the few

Universality of empirical risk minimization

arXiv:2202.08832v3 Announce Type: replace-cross Abstract: We study a general class of optimization problems with decision variable oldsymbol{Theta} in R^{p imes k} and cost function which is the sum o

VIB-AVSR: Variational Information Bottleneck for Noise-Robust LLM-Based Audio-Visual Speech Recognition

arXiv:2606.29632v1 Announce Type: cross Abstract: Audio-Visual Speech Recognition takes two input modalities, acoustic and visual streams, where visual information from lip movements aids recognition

A Study of Temporal Fusion Strategies for Named Entity Recognition in Historical Texts

arXiv:2606.27881v1 Announce Type: cross Abstract: Temporal variation poses a unique challenge for named entity recognition (NER) in historical texts, where entities drift in surface form and salience

Agentic AI-Powered Re-Identification: An Emerging, Scalable Threat to Mobility Microdata Privacy

arXiv:2606.27936v1 Announce Type: cross Abstract: The widespread collection of fine-grained location data by commercial data brokers creates a re-identification risk that is not widely recognised by t

agentsarxiv-cs-ai

Can LLMs Judge Better Than They Generate? Evaluating Task Asymmetry, Mechanistic Interpretability and Transferability for In-Context QA

arXiv:2606.28050v1 Announce Type: cross Abstract: LLM-as-a-Judge and self-evaluation pipelines implicitly assume that evaluation is easier than generation. We test this in a controlled in-context QA s

CoIn: Comprehensive 2D-3D Inpainting with Gaussian Splatting Guidance

arXiv:2606.27584v1 Announce Type: cross Abstract: 3D scene inpainting is essential for reconstructing areas corrupted by occlusions or limited viewpoints. While recent methods leverage Gaussian Splatt

Cross-Platform Chinese Offensive Comment Detection via Dual-Threshold Hard Example Mining

arXiv:2606.27629v1 Announce Type: cross Abstract: Cross-platform deployment of offensive comment detection for Chinese social media suffers performance degradation. The paper proposes a dual-threshold

Tutorials

Distributed Air-Gap Flux and Rotor-Current Fusion for Operating-Regime Identification in a 10-MW Kaplan Hydrogenerator

arXiv:2606.27800v1 Announce Type: cross Abstract: Reliable monitoring of hydroelectric generators requires descriptors that capture both electrical loading and electromagnetic field behavior. This wor

tutorialsarxiv-cs-lg

Dual-Learning based Penalized Multi-Align Clustering for Multi-View Incomplete and Disorderly Data

arXiv:2606.27984v1 Announce Type: new Abstract: Multimodal feature fusion can effectively capture complex patterns in real-world data by integrating complementary information from different modalities

safetyarxiv-cs-lg

Applications

Effects of relational graph modularity and depth on the learning performance of neural networks

arXiv:2507.10005v2 Announce Type: replace Abstract: In recent years, graph-based machine learning techniques, such as reinforcement learning and graph neural networks, have garnered significant attent

applicationsarxiv-cs-lg

Elastic Time: Dynamic Frame Rate Bottlenecks for Neural Audio Coding

arXiv:2606.27320v1 Announce Type: cross Abstract: Neural audio autoencoders have become a core component of compression, feature extraction, and generation. However, while existing systems support var

Exposure Bias Can Alleviate Itself via Directional and Frequency Rectification in Flow Matching

arXiv:2606.28226v1 Announce Type: cross Abstract: Flow Matching (FM) has achieved remarkable generative performance, yet it suffers from exposure bias due to discrepancies between training and inferen

hia-gat: A Heterogeneous Interaction-Aware Graph Attention Network For Frame-Level Traffic Conflict Risk Prediction On Freeways

arXiv:2606.27577v1 Announce Type: cross Abstract: This paper formulates frame-level freeway risk assessment as a multi-agent scene graph-level binary classification problem, where each video or trajec

Higher-Order Fourier Neural Operator: Explicit Mode Mixer for Nonlinear PDEs

arXiv:2606.28122v1 Announce Type: cross Abstract: Neural operators provide deep neural networks for learning mappings between function spaces. Among them, the Fourier Neural Operator (FNO) is particul

Long-Term Prediction of Local and Global Human Motion with Occlusion Recovery

arXiv:2606.27900v1 Announce Type: new Abstract: Human motion describes the three-dimensional full-body movement of a person. Anticipating such motion holds significant relevance across a wide range of

NormGuard: Reward-Preserving Norm Constraints in Flow-Matching Reinforcement Learning

arXiv:2606.27771v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training improves the reward alignment of flow-based generators, but often degrades perceptual quality in ways that a

Reasoning-Enhanced Rare-Event Prediction with Balanced Outcome Correction

arXiv:2601.16406v2 Announce Type: replace-cross Abstract: Rare-event prediction is critical in domains such as healthcare, finance, reliability engineering, customer support, aviation safety, where po

Reduction of Probabilistic Chemical Reaction Networks

arXiv:2606.27737v1 Announce Type: new Abstract: Programming adaptive behaviors at the cellular level is a long-standing goal that raises the question of how probabilistic computation can be implemente

Scene Generation at Absolute Scale: Utilizing Semantic and Geometric Guidance From Text for Accurate and Interpretable 3D Indoor Scene Generation

arXiv:2603.13910v2 Announce Type: replace Abstract: We present GuidedSceneGen, a text-to-3D generation framework that produces metrically accurate, globally consistent, and semantically interpretable

safetyarxiv-cs-cv

SEADA: An efficient methodology for optimizing mixed-precision DNNs on multi-precision spatial architectures

arXiv:2606.27884v1 Announce Type: cross Abstract: Mixed-precision computation has been introduced in deep neural networks (DNNs) as an effective approach to reduce latency, energy consumption, and mem

Hardware

The Context-Ready Transformer

arXiv:2606.27538v1 Announce Type: cross Abstract: We introduce the context-ready transformer, a new recurrent neural network architecture built from a D-layer transformer block that pre-contextualizes

hardwarearxiv-cs-ai

The Remittance Blueprint: Data-driven Intelligence for Sri Lanka

arXiv:2606.28190v1 Announce Type: cross Abstract: This study analyzes Sri Lankan migration and remittances over 32 years (1994-2025). Using a 384-month harmonized dataset, we apply exploratory data an

ToxiREX: A Dataset on Toxic REasoning in ConteXt

arXiv:2606.27981v1 Announce Type: new Abstract: We introduce a new, contextual, multilingual dataset called ToxiREX: Toxic REasoning in ConteXt. The dataset consists of threads of Reddit comments and

researcharxiv-cs-cl

TruEye: Fine-Grained Detection of AI-Generated Human Subjects in Images

arXiv:2606.27505v1 Announce Type: new Abstract: AI generated images are proliferating across the Internet. While some are used for entertainment, others are weaponized for fraud and social engineering

WattLayer: Get Layers Right to Estimate Inference Energy of Neural Networks

arXiv:2606.27841v1 Announce Type: cross Abstract: The widespread adoption of Artificial Intelligence (AI) has led to increasing concerns about energy consumption, yet there is a lack of standardized m

A Process Harness for Uplifting Legacy Workflows to Agentic BPM: Design and Realization in CUGA FLO

arXiv:2606.27188v1 Announce Type: new Abstract: We introduce the process harness, a new mechanism for uplifting legacy workflows into Agentic Business Process Management (Agentic BPM) without replacin

A3C3: AI Algorithm and Accelerator Co-design, Co-search, and Co-generation

arXiv:2606.20869v2 Announce Type: replace-cross Abstract: We present a holistic methodology for artificial intelligence algorithm and accelerator co-design, co-search, and co-generation (A3C3), which

Advancing Omnimodal Embodied Agents from Isolated Skills to Everyday Physical Autonomy

arXiv:2606.27251v1 Announce Type: cross Abstract: Building persistent embodied agents in unstructured environments demands unified orchestration of heterogeneous tools spanning both cyber (APIs, IoT)

agentsarxiv-cs-ai

Agentic Analysis for Agentic Infrastructure: An LLM-Powered Pipeline for Comparative Governance of DAO and Corporate AI Protocols

arXiv:2606.26203v1 Announce Type: new Abstract: As AI agent protocols proliferate, the governance structures shaping their interoperability standards remain empirically underexamined. We introduce an

Attention-Based Prototype Calibration for Multi-Rater Few-Shot Medical Image Segmentation

arXiv:2606.16325v2 Announce Type: replace Abstract: Few-shot medical image segmentation methods typically assume a single ground-truth annotation, overlooking systematic variability across expert rate

CogAD: Cognitive-Hierarchy Guided End-to-End Autonomous Driving

arXiv:2505.21581v4 Announce Type: replace-cross Abstract: While end-to-end autonomous driving has advanced significantly, prevailing methods remain fundamentally misaligned with human cognitive princi

agentsarxiv-cs-cv

CoStream: Composing Simple Behaviors for Generalizable Complex Manipulation

arXiv:2606.26423v1 Announce Type: cross Abstract: Long-horizon, contact-rich complex manipulation tasks, such as seating a GPU into a PCIe slot, demand both millimeter high precision and out-of-the-bo

CSU-PCAST: A Dual-Branch Transformer Framework for medium-range ensemble Precipitation Forecasting

arXiv:2510.20769v2 Announce Type: replace-cross Abstract: Accurate medium-range precipitation forecasting is essential for hydrometeorological risk management but remains challenging for both numerica

safetyarxiv-cs-lg

Do Safety Guardrails Need to Reason? LeanGuard: A Fast and Light Approach for Robust Moderation

arXiv:2606.26686v1 Announce Type: new Abstract: In order to screen a prompt or a response, the recent guardrail methods generate a chain-of-thought (CoT) before they issue a verdict. This design follo

local-aiarxiv-cs-ai

DocArena: Turning Raw Documents into Controllable Training Environments for Document Search Agents

arXiv:2606.26122v1 Announce Type: new Abstract: Recent methods train search agents via reinforcement learning from (question, answer, evidence) tuples without requiring expert trajectories. The tuples

safetyarxiv-cs-cv