Search: “model-releases”

Frontier Lag: A Bibliometric Audit of Capability Misrepresentation in Academic AI Evaluation

arXiv:2605.04135v1 Announce Type: cross Abstract: Readers of applied-domain LLM capability evaluations want to know what AI systems can currently do. That literature answers a related, but consequenti

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Model Releases

Gaze4HRI: Zero-shot Benchmarking Gaze Estimation Neural-Networks for Human-Robot Interaction

DGX agent

arXiv:2605.04770v1 Announce Type: new Abstract: While zero-shot appearance-based 3D gaze estimation offers significant cost-efficiency by directly mapping RGB images to gaze vectors, its reliability i

model-releasesarxiv-cs-cv

7 May 2026

Generalization Bounds of Spiking Neural Networks via Rademacher Complexity

arXiv:2605.02927v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) have garnered increasing attention as one of bio-inspired models due to their great potential in neuromorphic computing

Generative Quantum-inspired Kolmogorov-Arnold Eigensolver

arXiv:2605.04604v1 Announce Type: cross Abstract: High-performance computing (HPC) is increasingly important for scalable quantum chemistry workflows that couple classical generative models, quantum c

Geometric Evolution Graph Convolutional Networks: Enhancing Graph Representation Learning via Ricci Flow

arXiv:2603.26178v2 Announce Type: replace Abstract: We introduce the Geometric Evolution Graph Convolutional Network (GEGCN), a novel framework that enhances graph representation learning through expl

Gradient Scaling Effects in Adaptive Spectral PINNs for Stiff Nonlinear ODEs

arXiv:2605.04502v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) often struggle to train reliably on stiff and oscillatory dynamical systems due to poor optimization conditioni

Gradients with Respect to Semantics Preserving Embeddings Tell the Uncertainty of Large Language Models

arXiv:2605.04638v1 Announce Type: new Abstract: Uncertainty quantification (UQ) is an important technique for ensuring the trustworthiness of LLMs, given their tendency to hallucinate. Existing state-

Helmlab: A Two-Space Family of Analytical, Data-Driven Color Spaces for UI Design Systems

arXiv:2602.23010v3 Announce Type: replace-cross Abstract: We present Helmlab, a family of two purpose-built color spaces for UI design systems sharing a common 11-stage analytical structure: MetricSpa

Heterogeneous Ordinal Structure Learning with Bayesian Nonparametric Complexity Discovery

arXiv:2605.04191v1 Announce Type: cross Abstract: Public attitudes toward artificial intelligence are heterogeneous, ordinally measured, and poorly captured by any single dependency graph. Existing or

HUGO-CS: A Hybrid-Labeled, Uncertainty-Aware, General-Purpose, Observational Dataset for Cold Spray

arXiv:2605.04257v1 Announce Type: new Abstract: Cold spraying is an increasingly common approach for repairing and manufacturing components due to its solid-state manufacturing capabilities. However,

ICPR 2026 Competition on Privacy-Preserving Person Re-Identification from Top-View RGB-Depth Camera (TVRID)

arXiv:2605.04977v1 Announce Type: new Abstract: This companion paper reports the ICPR 2026 TVRID competition on privacy-aware top-view person re-identification. We present the competition setting, the

Imagery Dataset for Remaining Useful Life Estimation of Synthetic Fibre Ropes

arXiv:2605.04262v1 Announce Type: new Abstract: Remaining useful life (RUL) estimation of synthetic fibre ropes (SFRs) is critical for safe operation in offshore-crane, wind turbine installation, and

Improving FMQA via Initial Training Data Design Considering Marginal Bit Coverage in One-Hot Encoding

arXiv:2605.04825v1 Announce Type: new Abstract: Factorization machine with quadratic-optimization annealing (FMQA) is a black-box optimization method that combines a factorization machine (FM) surroga

Information Coordination as a Bridge: A Neuro-Symbolic Architecture for Reliable Autonomous Driving Scene Understanding

arXiv:2605.04475v1 Announce Type: new Abstract: Reliable autonomous driving requires scene understanding that is semantically consistent across heterogeneous sensors and verifiable at the reasoning st

Intermediate Representations are Strong AI-Generated Image Detectors

arXiv:2605.04358v1 Announce Type: new Abstract: The rapid advancement in generative AI models has enabled the creation of photorealistic images. At the same time, there are growing concerns about the

Jacobian-Velocity Bounds for Deployment Risk Under Covariate Drift

arXiv:2605.04932v1 Announce Type: cross Abstract: We study long-horizon deployment of a frozen predictor under dynamic covariate shift. A time-domain Poincare inequality reduces temporal risk volatili

Joint Treatment Effect Estimation from Incomplete Healthcare Data: Temporal Causal Normalizing Flows with LLM-driven Evolutionary MNAR Imputation

arXiv:2605.05125v1 Announce Type: new Abstract: Target trial emulation (TTE) enables causal questions to be studied with observational data when randomized controlled trials (RCTs) are infeasible. Yet

Jordan-RoPE: Non-Semisimple Relative Positional Encoding via Complex Jordan Blocks

arXiv:2605.04217v1 Announce Type: cross Abstract: Relative positional encodings determine which functions of query-key lag can enter the primitive attention logit. RoPE supplies a rotary phase, while

KernelBench-X: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

arXiv:2605.04956v1 Announce Type: new Abstract: LLM-based Triton kernel generation has attracted significant interest, yet a fundamental empirical question remains unanswered: where does this capabili

KGLAMP: Knowledge Graph-guided Language model for Adaptive Multi-robot Planning and Replanning

model-releasesarxiv-cs-ro

arXiv:2602.04129v2 Announce Type: replace Abstract: Heterogeneous multi-robot systems are increasingly used in long-horizon missions requiring coordinated planning across diverse capabilities. However

Laundering AI Authority with Adversarial Examples

arXiv:2605.04261v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly deployed as trusted authorities -- fact-checking images on social media, comparing products, and modera

LoViF 2026 The First Challenge on Holistic Quality Assessment for 4D World Model (PhyScore)

arXiv:2605.05187v1 Announce Type: new Abstract: This paper reports on the LoViF 2026 PhyScore challenge, a competition on holistic quality assessment of world-model-generated videos across both 2D and

Low-Rank Adaptation of Geospatial Foundation Models for Wildfire Mapping Using Sentinel-2 Data

arXiv:2605.04989v1 Announce Type: new Abstract: Wildfire burned-area mapping is essential for damage assessment, emissions modeling, and understanding fire-climate interactions across diverse ecologic

LUCAS-MEGA: A Large-Scale Multimodal Dataset for Representation Learning in Soil-Environment Systems

arXiv:2605.04323v1 Announce Type: new Abstract: Understanding soil is fundamental to agriculture, carbon cycling, and environmental sustainability, yet progress is limited by fragmented and heterogene

Magic-Informed Quantum Architecture Search

arXiv:2605.03932v1 Announce Type: cross Abstract: Nonstabilizerness, commonly referred to as magic, is a fundamental resource underpinning quantum advantage. In this paper, we propose a magic-informed

Making Knowledge Accessible: Divergent Readability-Accuracy Strategies of Mistral and QWen in Biomedical Text Simplification

arXiv:2511.05080v4 Announce Type: replace Abstract: The growing public demand for accessible biomedical information calls for scalable text simplification. While large language models (LLMs) offer sol

Manifold of Failure: Behavioral Attraction Basins in Language Models

arXiv:2602.22291v3 Announce Type: replace Abstract: While prior work has focused on projecting adversarial examples back onto the manifold of natural data to restore safety, we argue that a comprehens

Memory as a Markov Matrix: Sample Efficient Knowledge Expansion via Token-to-Dictionary Mapping

arXiv:2605.04308v1 Announce Type: new Abstract: Continual incorporation of new knowledge is essential for the long-term evolution of large language models (LLMs). Existing approaches typically rely on

MEMTIER: Tiered Memory Architecture and Retrieval Bottleneck Analysis for Long-Running Autonomous AI Agents

arXiv:2605.03675v1 Announce Type: new Abstract: Long-running autonomous AI agents suffer from a well-documented memory coherence problem: tool-execution success rates degrade 14 percentage points over

MOSAIC-Bench: Measuring Compositional Vulnerability Induction in Coding Agents

arXiv:2605.03952v1 Announce Type: cross Abstract: Coding agents often pass per-prompt safety review yet ship exploitable code when their tasks are decomposed into routine engineering tickets. The chal

MP-ISMoE: Mixed-Precision Interactive Side Mixture-of-Experts for Efficient Transfer Learning

arXiv:2605.04058v1 Announce Type: new Abstract: Parameter-efficient transfer learning (PETL) has emerged as a pivotal paradigm for adapting pre-trained foundation models to downstream tasks, significa

MRI-Eval: A Tiered Benchmark for Evaluating LLM Performance on MRI Physics and GE Scanner Operations Knowledge

arXiv:2605.05175v1 Announce Type: cross Abstract: Background: Existing MRI LLM benchmarks rely mainly on review-book multiple-choice questions, where top proprietary models already score highly, limit

MULTIBENCH++: A Unified and Comprehensive Multimodal Fusion Benchmarking Across Specialized Domains

arXiv:2511.06452v3 Announce Type: replace Abstract: Although multimodal fusion has made significant progress, its advancement is severely hindered by the lack of adequate evaluation benchmarks. Curren

NoisyCausal: A Benchmark for Evaluating Causal Reasoning Under Structured Noise

arXiv:2605.04313v1 Announce Type: new Abstract: Causal reasoning in natural language requires identifying relevant variables, understanding their interactions, and reasoning about effects and interven

Not All That Is Fluent Is Factual: Investigating Hallucinations of Large Language Models in Academic Writing

arXiv:2605.04171v1 Announce Type: new Abstract: Large Language models (LLMs) show extraordinary abilities, but they are still prone to hallucinations, especially when we use them for generating Academ

Nsanku: Evaluating Zero-Shot Translation Performance of LLMs for Ghanaian Languages

arXiv:2605.04208v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated impressive multilingual capabilities for well-resourced languages, yet their performance on low-resource

Open-Source Image Editing Models Are Zero-Shot Vision Learners

arXiv:2605.04566v1 Announce Type: cross Abstract: Recent studies have shown that large generative models can solve vision tasks they were not explicitly trained for. However, existing evidence relies

OpenVTON-Bench: A Large-Scale High-Resolution Benchmark for Controllable Virtual Try-On Evaluation

arXiv:2601.22725v3 Announce Type: replace Abstract: Recent advances in diffusion models have significantly elevated the visual fidelity of Virtual Try-On (VTON) systems, yet reliable evaluation remain

Optimal Control with Natural Images: Efficient Reinforcement Learning using Overcomplete Sparse Codes

arXiv:2412.08893v3 Announce Type: replace Abstract: Optimal control and sequential decision making are widely used in many complex tasks. Optimal control over a sequence of natural images is a first s

OSAQ: Outlier Self-Absorption for Accurate Low-bit LLM Quantization

arXiv:2605.04738v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities. However, their massive parameter scale leads to significant resource consumption

Paraphrase-Induced Output-Mode Collapse: When LLMs Break Character Under Semantically Equivalent Inputs

arXiv:2605.04665v1 Announce Type: new Abstract: When the substantive content of a request is rewritten, do large language models still answer in the format the original task asked for? We find that th

Perceive, Verify and Understand Long Video: Multi-Granular Perception and Active Verification via Interactive Agents

arXiv:2509.24943v2 Announce Type: replace Abstract: Long videos, characterized by temporal complexity and sparse task-relevant information, pose significant reasoning challenges for AI systems. Althou

Physics-Grounded Multi-Agent Architecture for Traceable, Risk-Aware Human-AI Decision Support in Manufacturing

arXiv:2605.04003v1 Announce Type: cross Abstract: High-precision CNC machining of free-form aerospace components requires bounded compensations informed by inspection, simulation, and process knowledg

Privacy-Preserving Empathy Detection in Video Interactions

arXiv:2504.10808v3 Announce Type: replace Abstract: Detecting empathy from video interactions has emerging applications, yet raw videos that could be used for training AI models are rarely available d

Probing Structural Mathematical Reasoning in Language Models with Algebraic Trapdoors

arXiv:2605.04352v1 Announce Type: new Abstract: We introduce a benchmark suite for evaluating structural mathematical reasoning in language models, built on subgroup-construction problems in SL(3, Z)

Prompt-Anchored Vision-Text Distillation for Lifelong Person Re-identification

arXiv:2605.05027v1 Announce Type: new Abstract: Lifelong person re-identification (LReID) aims to train a generalizable model with sequentially collected data. However, such models often suffer from s

Provable Non-Convex Euclidean Distance Matrix Completion: Geometry, Reconstruction, and Robustness

arXiv:2508.00091v3 Announce Type: replace-cross Abstract: The problem of recovering the configuration of points from their partial pairwise distances, referred to as the Euclidean Distance Matrix Comp

PSK at SemEval-2026 Task 9: Multilingual Polarization Detection Using Ensemble Gemma Models with Synthetic Data Augmentation

arXiv:2605.05159v1 Announce Type: new Abstract: We present our system for SemEval-2026 Task 9: Multilingual Polarization Detection, a binary classification task spanning 22 languages. Our approach fin