Search: “models”

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

26 Jun 2026

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

DGX agent

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

model-releasesarxiv-cs-ai

26 Jun 2026

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

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

model-releasesarxiv-cs-ai

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

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

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

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

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

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

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

Robot Self-Improvement via Human-Video Dynamics Models

arXiv:2606.21406v1 Announce Type: cross Abstract: A central question in robot learning is how to acquire skills from the kinds of data that humans learn from: passive observation, embodied practice, a

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

SimAC: A Simple Anti-Customization Method for Protecting Face Privacy against Text-to-Image Synthesis of Diffusion Models

arXiv:2312.07865v4 Announce Type: replace Abstract: Despite the success of diffusion-based customization methods on visual content creation, increasing concerns have been raised about such techniques

Toward Non-Expert Customized Congestion Control: Large Language Model-Assisted CCA Code Generation with eBPF Deployment

arXiv:2601.22461v2 Announce Type: replace-cross Abstract: General-purpose congestion control algorithms (CCAs) are designed to achieve general congestion control goals, but they may not meet the speci

Verifiable, private AI: Google Cloud expands Confidential Computing frontiers

model-releasesgoogle-cloud-ai

Protecting sensitive data used with AI is a critical part of our commitment to providing advanced and secure cloud infrastructure. Confidential Computing cryptographically protects data in use in hard

Zero-order Parameter-free Optimization for LMO-based Methods: Novel Approach for Efficient Fine-tuning

model-releasesarxiv-cs-lg

arXiv:2606.14970v2 Announce Type: replace Abstract: Fine-tuning large language models (LLMs) has become a central application of modern optimization, enabling pretrained models to adapt to diverse dow

Here is the prompt method behind this AR try-on app. The trick is not a magic prompt. It is the architecture of the prompt, and it works acr…

model-releaseszhipu-ai--x

Here is the prompt method behind this AR try-on app. The trick is not a magic prompt. It is the architecture of the prompt, and it works across GLM-5.2 and other frontier models. Full prompt: http://c

22 Jun 2026

Use Case 1: Autonomous ML Research Can an AI autonomously improve another AI’s training recipe? We tasked Fugu Ultra with improving a small …

model-releasesdavid-ha--x

Use Case 1: Autonomous ML Research Can an AI autonomously improve another AI’s training recipe? We tasked Fugu Ultra with improving a small GPT model using AutoResearch. Over 14 hours on a single H100

22 Jun 2026

Over the last two weeks, both the U.S. Government and Anthropic took significant actions that demonstrated their power to control access to …

model-releasesandrew-ng--x

Over the last two weeks, both the U.S. Government and Anthropic took significant actions that demonstrated their power to control access to AI by restricting what others can do with frontier models. T

19 Jun 2026

DeceptionX: Explainable Deception Detection with Multimodal Large Language Models

arXiv:2606.11385v1 Announce Type: new Abstract: Deception detection is a critical and highly challenging task within affective computing and behavioral analysis. Existing deep learning methods typical

applicationsarxiv-cs-cv

From Prompts to Tokens: Internalizing Causal Supervision in Vision-Language Model for Multi-Image Causal Reasoning

arXiv:2606.11745v1 Announce Type: cross Abstract: Visual causal reasoning is essential for understanding and intervening in the physical world, requiring identification of causal variables from visual

researcharxiv-cs-ai

iPack: Intuitive Bin Packing with Large Language Models

arXiv:2503.08445v2 Announce Type: replace Abstract: Robotics and automation are increasingly influential in logistics but remain largely confined to traditional warehouses. In grocery retail, advancem

researcharxiv-cs-ro

LakeFM: Toward a Foundation Model for Aquatic Ecosystems Using Irregular Multivariate Multi-depth Time Series Data

arXiv:2606.11268v1 Announce Type: new Abstract: Understanding and forecasting lake dynamics is critical for monitoring water quality and ecosystem health across lakes and reservoirs. While machine lea