Search: “models”

The Complexity Ceiling Benchmark: A Multi-Domain Evaluation of Sequential Reasoning Under Depth Scaling

arXiv:2606.29278v1 Announce Type: new Abstract: We introduce the Complexity Ceiling Benchmark (CCB), a controlled evaluation of how language-model reasoning decays as the number of required sequential

30 Jun 2026

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Agents

The Emergence of Autonomous Penetration Capabilities in Large Language Model-Powered AI Systems

DGX agent

arXiv:2606.13079v2 Announce Type: replace-cross Abstract: Nowadays, the autonomous execution of cyberattacks capable of causing substantial real-world harm is widely regarded as one of the critical re

agentsarxiv-cs-ai

30 Jun 2026

Local Ai

Unified Complex-valued Neural Network: A Magnitude-Phase Computational Model for Event-Driven Neuromorphic Learning

arXiv:2606.29099v1 Announce Type: cross Abstract: Artificial neural networks (ANN) provide accurate continuous-valued representation, whereas spiking neural networks (SNN) offer event-driven temporal

local-aiarxiv-cs-ai

30 Jun 2026

EchoSonar-R: A Multi-View Reasoning-Enabled Model for Disease Classification and Report Generation in Echocardiography

arXiv:2606.28164v1 Announce Type: new Abstract: Echocardiography is the most widely used non-invasive cardiac imaging modality, providing essential information for cardiovascular diagnosis. Interpreti

HumanMoveVQA: Can Video MLLMs reason about human movement in videos?

model-releasesarxiv-cs-cv

arXiv:2606.27999v1 Announce Type: new Abstract: Despite the rapid advance of Multimodal Large Language Models (MLLMs) in high-level video understanding, a fundamental bottleneck remains: these models

Learning Complementary Action Modeling from Automotive Maintenance Instructions

arXiv:2606.27808v1 Announce Type: new Abstract: A minute lexical variation can reverse the procedural meaning of an instruction even when the rest of the sentence remains unchanged. In automotive main

researcharxiv-cs-cl

Non-Linear Model-Based Sequential Decision-Making in Agriculture

arXiv:2509.01924v4 Announce Type: replace-cross Abstract: Agricultural decision-making faces a dual challenge: sustaining high yields to meet global food security needs while reducing the environmenta

applicationsarxiv-cs-lg

On the Inseparability of Instructions and Data in Shared-Embedding Sequence Models

arXiv:2606.27567v1 Announce Type: cross Abstract: Prompt injection is the top security risk for LLM-integrated applications, yet every defense proposed so far has been broken. We prove this is not a c

A Pipeline for Generating Longitudinal Synthetic Clinical Notes Using Large Language Models

arXiv:2606.26879v1 Announce Type: new Abstract: Synthetic data is increasingly used to enable the development and evaluation of AI systems in domains where access to real-world data is restricted. In

applicationsarxiv-cs-ai

Automating Potential-based Reward Shaping with Vision Language Model Guidance

arXiv:2606.27180v1 Announce Type: cross Abstract: Sparse rewards are inherently challenging for reinforcement learning agents as they lack intermediate feedback to guide exploration and to correctly a

Charting the Growth of Social-Physical HRI (spHRI): A Systematic Review Pipeline Augmented by Small Language Models

arXiv:2606.26382v1 Announce Type: cross Abstract: Social-physical human-robot interaction (spHRI) has grown rapidly across robotics, human-computer interaction, human-robot interaction, and haptics. Y

researcharxiv-cs-ai

Embarrassingly Simple Self-Distillation Improves Code Generation

model-releasesarxiv-cs-cl

arXiv:2604.01193v2 Announce Type: replace Abstract: Can a large language model (LLM) improve at code generation using only its own raw outputs, without a verifier, a teacher model, or reinforcement le

LLM-based Models for Detecting Emerging Topics in Service Feedback

arXiv:2606.26595v1 Announce Type: new Abstract: Enhancing the analysis of service feedback is essential for public sector organizations, particularly tax administrations, where trust and compliance de

NebulaExp-8B: An Empirical Post-Training Pipeline via Full-Scale Ablation Research

arXiv:2606.26671v1 Announce Type: new Abstract: Post-training alignment determines the reasoning and human preference following capabilities of large language models, yet most existing works withhold

State-Specific Respiratory Signatures for Affective and Stress Recognition: Interpretable Respiratory Markers, Autocorrelation Lags, and Compact CNN Models

arXiv:2606.26723v1 Announce Type: cross Abstract: Respiratory activity is a direct and interpretable physiological channel for wearable stress and affective-state recognition, yet many studies emphasi

Thinking Like a Scientist? A Structural Study of LLM-Generated Research Methods

arXiv:2606.26130v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used to guide research methodology, yet their default methodological tendencies under minimal prompting

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations

arXiv:2606.25629v1 Announce Type: new Abstract: Robot navigation in safety-critical scenarios faces significant challenges from unforeseen semantic events, where collisions arise primarily from the un

safetyarxiv-cs-ro

Neural operator-based digital twins for modeling amyloid-eta and tau propagation and treatment optimization in Alzheimer's disease

arXiv:2606.25185v1 Announce Type: new Abstract: Accurately predicting the spatiotemporal evolution of amyloid-eta and tau proteins at the individual level is critical for improving the diagnosis and t

Reclaim Evaluation: A Lossy Memory Is Worse Than an Empty One

model-releasesarxiv-cs-cl

arXiv:2606.25449v1 Announce Type: new Abstract: A language model's memory can be worse than having no memory at all. Give a model a memory that kept a wrong conclusion but dropped the work behind it,

TensorLDM: A Component-Wise Latent Diffusion Model for Volumetric DTI Reconstruction from Sparse DWIs

arXiv:2606.25545v1 Announce Type: new Abstract: Reconstructing diffusion tensors from sparse DWIs is critical for accelerating Diffusion Tensor Imaging (DTI) in clinical settings, yet current deep lea

Local Ai

WinDOM: Self-Family Distillation for Small-Model GUI Grounding

arXiv:2606.25964v1 Announce Type: cross Abstract: Small (sim2B) GUI-grounding agents are attractive for on-device deployment, accessibility tooling, and low-cost iteration, but at this scale they face

local-aiarxiv-cs-lg

BluTrain: A C++/CUDA Framework for AI Systems

arXiv:2606.24780v1 Announce Type: new Abstract: Progress in deep learning is, at scale, more a matter of systems engineering than of modelling: the behaviour of a model in training (its throughput, it

Does My Embedding Reflect That A = B? Evaluating Mathematical Equivalence in Embedding Models

arXiv:2606.23959v1 Announce Type: new Abstract: Because mathematics is highly abstract, a single statement can take very different forms depending on what subfield it is framed in. There are many exam

researcharxiv-cs-cl

GENA3D: Generative Amodal 3D Modeling by Bridging 2D Priors and 3D Coherence

arXiv:2511.21945v3 Announce Type: replace Abstract: Generating complete 3D objects under partial occlusions (i.e., amodal scenarios) is a practically important yet challenging problem, as large portio

High-Fidelity Synthetic Transmission Electron Microscopy Image Generation Using Diffusion Probabilistic Models for Data-Limited Semiconductor Metrology

arXiv:2606.24817v1 Announce Type: new Abstract: Advanced semiconductor nodes drastically increased demand for Transmission Electron Microscopy (TEM), yet destructive sample preparation, slow imaging a

Hybrid Event Frame Sensors: Modeling, Calibration, and Simulation

arXiv:2511.18037v2 Announce Type: replace Abstract: Hybrid event-frame sensors integrate an Event Vision Sensor (EVS) and an Active Pixel Sensor (APS) within a single chip, combining the high dynamic

Matching Tasks to Objectives: Fine-Tuning and Prompt-Tuning Strategies for Encoder-Decoder Pre-trained Language Models

arXiv:2606.24841v1 Announce Type: new Abstract: Prompt-based learning has emerged as a dominant paradigm in natural language processing. This study explores the impact of diverse pre-training objectiv

researcharxiv-cs-ai

Policy Gradient with Self-Attention for Model-Free Distributed Nonlinear Multi-Agent Games

arXiv:2509.18371v2 Announce Type: replace-cross Abstract: Multi-agent games in dynamic nonlinear settings are challenging due to the time-varying interactions among the agents and the non-stationarity

safetyarxiv-cs-ro

REALM: A Unified Red-Teaming Benchmark for Physical-World VLMs

model-releasesarxiv-cs-cv

arXiv:2606.23892v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly used as perception-reasoning backbones for embodied intelligence in safety-critical physical systems, whe

SLEEPING-DISCO 9M: A large-scale pre-training dataset for generative music modeling

arXiv:2506.14293v4 Announce Type: replace-cross Abstract: We present Sleeping-DISCO 9M, a large-scale pre-training dataset for music and song. To the best of our knowledge, there are no open-source hi

applicationsarxiv-cs-lg

When AI Meets Finance (StockAgent): Large Language Model-based Stock Trading in Simulated Real-world Environments

arXiv:2407.18957v5 Announce Type: replace-cross Abstract: Can AI Agents simulate real-world trading environments to investigate the impact of external factors on stock trading activities (e.g., macroe

Asymptotic Signal Subspace Recovery in Softmax Attention Models

arXiv:2606.22406v1 Announce Type: new Abstract: Attention mechanisms have demonstrated remarkable empirical success in identifying relevant information from large collections of tokens, yet the theore

Combinatorial Sparse PCA Beyond the Spiked Identity Model

arXiv:2603.02607v2 Announce Type: replace-cross Abstract: Sparse PCA is one of the most well-studied problems in high-dimensional statistics. In this problem, we are given samples from a distribution

applicationsarxiv-cs-lg

DamageArbiter: A Multimodal Arbitration Framework for Disaster Damage Assessment from Street-View Imagery

arXiv:2603.14837v2 Announce Type: replace Abstract: Analyzing street-view imagery with computer vision models offers a promising approach for rapid, hyperlocal disaster damage assessment, but existing

DBT-Bleed: Dual-Branch Temporal Modeling with Key-Frame Selection for Surgical Bleeding Detection

arXiv:2606.22829v1 Announce Type: new Abstract: Intraoperative Adverse Events (IAEs) detection is critical for improving surgical safety, with bleeding being among the most frequent events across many

DiT-Reward: Generative Representations for Text-to-Image Reward Modeling

arXiv:2606.23626v1 Announce Type: new Abstract: Can representations learned for image generation also support the evaluation of generated images? We study text-to-image reward prediction as a downstre

safetyarxiv-cs-lg

Federated Learning for Global Carbon Emission Forecasting: A Hybrid Time-Series Approach with Statistical and Neural Models

arXiv:2606.22618v1 Announce Type: new Abstract: Climate change, primarily driven by carbon dioxide (CO2) emissions, requires accurate forecasting tools to support effective mitigation policies and sus

Agents

From Discrete Plans to Real-World Execution: A World-Model-Driven Framework for Execution-Aware Multi-Agent Path Finding

arXiv:2511.21886v2 Announce Type: replace Abstract: Multi-Agent Path Finding (MAPF) studies how to coordinate multiple agents to reach their goals without collisions and underpins a range of large-sca

agentsarxiv-cs-ro

Imitation from Heterogeneous Demonstrations using Grounded Latent-Action World Models

arXiv:2606.21672v1 Announce Type: cross Abstract: Imitation learning has emerged as a powerful paradigm for learning visuomotor policies, but its generalisation and stability are limited by the scale

safetyarxiv-cs-lg

MMOU: A Massive Multi-Task Omni Understanding and Reasoning Benchmark for Long and Complex Real-World Videos

model-releasesarxiv-cs-cv

arXiv:2603.14145v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have shown strong performance in visual and audio understanding when evaluated in isolation. However,

MS-rPPG: Multi-spectral State Space Model for Remote Photoplethysmography in Driver Monitoring Systems

arXiv:2606.21115v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) is a camera-based technique for measuring physiological signals, particularly cardiac activity. From the remotely mea

applicationsarxiv-cs-cv

MV-WAM: Manifold-Aware World Action Model with Value Augmentation

arXiv:2606.21088v1 Announce Type: new Abstract: Achieving robust and generalizable manipulation across diverse environments remains a fundamental challenge in embodied robotics. Recent world action mo

safetyarxiv-cs-ro

NegAS: Negative Label Guided Attention and Scoring for Out-of-Distribution Object Detection with Vision-Language Models

arXiv:2606.22537v1 Announce Type: new Abstract: Out-of-Distribution (OOD) detection is essential for ensuring the robustness and reliability of object detection systems deployed in safety-critical app

Agents

NeuPAN: Direct Point Robot Navigation with End-to-End Model-based Learning

arXiv:2403.06828v4 Announce Type: replace Abstract: Navigating a nonholonomic robot in a cluttered, unknown environment requires accurate perception and precise motion control for real-time collision

agentsarxiv-cs-ro

Predicting High-Risk Colorectal Polyps in African Americans Using Pre-Colonoscopy Clinical Features: Machine Learning Model Development and Temporal Validation

arXiv:2606.21492v1 Announce Type: new Abstract: Risk stratification for advanced colorectal polyps typically relies on colonoscopy and/or pathology findings. However, there is growing interest in whet

Predicting Immune Biomarkers with MultiModal Mixture-of-Expert Pathology Foundation Models Empowers Precision Oncology

arXiv:2606.18123v2 Announce Type: replace Abstract: Predicting immune biomarkers associated with the tumor immune microenvironment (TIME) is critical for advancing precision oncology, yet existing app

Protein contacts are already in the attention: a single-forward-pass alternative to the Categorical Jacobian

model-releasesarxiv-cs-lg

arXiv:2606.21876v1 Announce Type: new Abstract: The Categorical Jacobian (CJ) of Zhang et al. (2024) reads protein contacts from a language model by perturbing every residue with every alternative ami

Tutorials

Provable Learning of Random Hierarchy Models and Hierarchical Shallow-to-Deep Chaining

arXiv:2601.19756v2 Announce Type: replace Abstract: The empirical success of deep learning is often attributed to deep networks' ability to exploit hierarchical structure in data, constructing increas

tutorialsarxiv-cs-lg