Search: “models”

Blackknife: Hard-Label Query-Limited Black-Box Attacks on Heterogeneous Graph Neural Networks

model-releasesarxiv-cs-lg

arXiv:2606.29240v1 Announce Type: new Abstract: Heterogeneous graph neural networks (HGNNs) have achieved strong performance in modeling complex graph-structured data with multiple node and relation t

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Bricker to BRACE: A Bracket Exposure RAW Dataset and Restoration Model for Flicker-Banding

DGX agent

arXiv:2606.29845v1 Announce Type: new Abstract: Flicker-banding (FB), arises from temporal aliasing between a camera's rolling shutter and a display's brightness modulation, degrading screen-captured

researcharxiv-cs-cv

30 Jun 2026

Can LLMs Hire Fairly? Racial Bias in Resume Screening

arXiv:2606.28978v1 Announce Type: new Abstract: We audit fourteen mainstream large language models (LLMs) for hiring discrimination using the paired-resume methodology of Kline, Rose, and Walters (202

Causality for Tabular Data Synthesis: A High-Order Structure Causal Benchmark Framework

arXiv:2406.08311v3 Announce Type: replace-cross Abstract: Existing evaluations of tabular synthesis models rely primarily on low-order statistics and downstream task performance, leaving multivariate

DrivenMorph: Bridging Attention Mechanism and Variational Image Registration via Difference Modeling

arXiv:2606.30183v1 Announce Type: new Abstract: Medical image registration benefits significantly from deep learning, yet existing approaches often lack physical explainability and fine-grained deform

Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting

arXiv:2507.06764v5 Announce Type: replace-cross Abstract: In this work, we propose Fast Equivariant Imaging (FEI), a novel unsupervised learning framework to rapidly and efficiently train deep imaging

How LLMs See Creativity: Zero-Shot Scoring of Visual Creativity with Interpretable Reasoning

arXiv:2606.29672v1 Announce Type: new Abstract: Evaluating the originality of visual images poses enduring challenges for creativity assessment. Automated scoring using AI models has proven effective

Local Ai

KernelSight-LM: A Kernel-Level LLM Inference Simulator

arXiv:2606.28565v1 Announce Type: cross Abstract: As large language models (LLMs) move into production serving, practitioners must rapidly evaluate inference performance across diverse hardware, model

local-aiarxiv-cs-ai

LETT-NeXt: A Lightweight RECIST-Guided Model for 3D CT Lesion Segmentation

arXiv:2606.30108v1 Announce Type: new Abstract: RECIST diameter measurements are widely used for tumor response assessment, but they provide only a limited 2D description of lesion extent. We present

Multimodal Large Language Model driven Radiology Report Generation with Clinical Knowledge Enhancement

arXiv:2403.06728v2 Announce Type: replace Abstract: Radiology report generation (RRG) has attracted significant attention due to its potential to reduce the workload of radiologists. The performance o

Scaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B Agent

arXiv:2606.30616v1 Announce Type: new Abstract: We introduce Agents-A1, a 35B Mixture-of-Experts Agentic Model that reaches trillion-parameter-level performance by scaling the agent horizon. We invest

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

Agents

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

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

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

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

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

safetyarxiv-cs-ai

Embarrassingly Simple Self-Distillation Improves Code Generation

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

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

OpenAI unveils GPT-5.6 amid US AI regulatory drama

model-releasesthe-verge-ai

Less than 24 hours after news broke that OpenAI would stagger its next model release at the request of the Trump administration, that model, GPT-5.6, is here. On Friday, the company unveiled the limit

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

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

researcharxiv-cs-lg

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

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

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

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

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

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

safetyarxiv-cs-ai

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

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

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

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

researcharxiv-cs-lg

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

RARM: Confidence-Gated Progress Reward Modeling for RL in Manipulation

arXiv:2606.22027v1 Announce Type: new Abstract: Reinforcement learning for robot manipulation is often bottlenecked by reward design, especially in long-horizon tasks: sparse success rewards provide w

applicationsarxiv-cs-ro

Self-Curriculum Model-based Reinforcement Learning for Shape Control of Deformable Linear Objects

arXiv:2602.21816v2 Announce Type: replace Abstract: Precise shape control of Deformable Linear Objects (DLOs) is crucial in robotic applications such as industrial and medical fields. However, existin