Search: “framework”

PGUDA: Pressure-Guided Unsupervised Domain Adaptation with Cross-Modal Knowledge Distillation for sEMG-Based Gesture Recognition

arXiv:2606.31349v1 Announce Type: cross Abstract: Surface electromyography (sEMG)-based gesture recognition has emerged as a promising technology for natural human-computer interaction. However, its p

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Physics-Constrained Fine-Tuning of Flow-Matching Models for Generation and Inverse Problems

DGX agent

arXiv:2508.09156v3 Announce Type: replace-cross Abstract: We present a framework for fine-tuning flow-matching generative models to enforce physical constraints and solve inverse problems in scientifi

model-releasesarxiv-cs-ai

1 Jul 2026

Quantum Bayesian Networks Can Speed up Reinforcement Learning in Partially Observable Environments

arXiv:2507.18606v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) provides a principled framework for decision-making in partially observable environments, which can be modeled as

SimpleSearch-VL: A Simple Recipe for Multimodal Agentic Deep Search

model-releasesarxiv-cs-cv

arXiv:2606.31504v1 Announce Type: new Abstract: We present SimpleSearch-VL, an efficient, reliable, and practical framework for multimodal agentic search. Its core idea is to improve the agent's own s

SpheRoPE: Zero-Shot Optimization-Free 360 Panorama Generation with Spherical RoPE

arXiv:2606.32033v1 Announce Type: new Abstract: We present a zero-shot, training-free and optimization-free framework for generating 360 panoramic images and videos by directly injecting spherical pri

Stabilization Learning: A Paradigm Transition Bridging Control Theory and Machine Learning

arXiv:2606.31562v1 Announce Type: new Abstract: Stabilization learning is an interdisciplinary paradigm that bridges control theory and machine learning. Its core idea is to enable systems to adjust t

Stealthy Multi-Task Adversarial Attacks

arXiv:2411.17936v2 Announce Type: replace-cross Abstract: Deep neural networks are highly vulnerable to adversarial perturbations, raising serious safety concerns in the real-world systems. While prio

safetyarxiv-cs-cv

Tutorials

Toward AI-Resilient Assessment in Computer Science Courses in an AI-Native World

arXiv:2606.30655v1 Announce Type: cross Abstract: AI-native course assessments in senior computer science courses and related fields should grade students by AI-resilient skill: the ability to achieve

tutorialsarxiv-cs-ai

Unified Structural-Hydrodynamic Modeling of Underwater Underactuated Mechanisms and Soft Robots

model-releasesarxiv-cs-ro

arXiv:2603.07939v2 Announce Type: replace Abstract: Underwater robots are widely deployed for ocean exploration and manipulation. Underactuated mechanisms are advantageous in aquatic environments beca

UniSAE: Unified Speech Attribute Editing on Speaker, Emotion and Low-Level Content via Discrete Phonetic Posteriorgram Modelling

arXiv:2606.31128v1 Announce Type: cross Abstract: Speech editing aims to modify specific portions of an utterance while preserving the remaining speech. Existing approaches primarily focus on word-lev

Tools

“Valued work per watt is the score” @rolandgvc with the real details of self improving agents at @aiDotEngineer!

This post discusses a framework for evaluating self-improving AI agents where 'value per watt' serves as a key metric, likely examining how efficiently these agents generate useful output relative to

toolsswyx--x

Verification-Gated Agentic Mission-State Governance for Intelligent Industrial Multi-Robot Systems

arXiv:2606.31339v1 Announce Type: new Abstract: Agentic artificial intelligence is increasingly used to decompose industrial tasks, propose robot actions, and adapt execution plans in dynamic cyber-ph

A Linear Matching Bandit Approach to Online Multi-Human Multi-Robot Teaming

arXiv:2606.29221v1 Announce Type: new Abstract: We address the problem of online multi-human multi-robot teaming through the lens of a linear matching bandit framework, where a learner assigns robots

A Posteriori Error Analysis for Decoupled Neural Approximations of Fully Coupled FBSDEs with Control Mismatch

arXiv:2606.29474v1 Announce Type: cross Abstract: This paper develops an a posteriori error analysis framework for decoupled neural approximations of fully coupled forward--backward stochastic differe

AERMANI-VLM: Structured Prompting and Reasoning for Aerial Manipulation with Vision Language Models

arXiv:2511.01472v2 Announce Type: replace Abstract: The rapid progress of vision--language models (VLMs) has sparked growing interest in robotic control, where natural language can express the operati

Applications

Attention Enhanced Entity Recommendation for Intelligent Monitoring in Cloud Systems

arXiv:2510.20640v2 Announce Type: replace Abstract: In this paper, we present DiRecGNN, an attention-enhanced entity recommendation framework for monitoring cloud services at Microsoft. We provide ins

applicationsarxiv-cs-lg

Agents

AutoB2G: Agentic Simulation and Reinforcement Learning for Spatio-Temporal Grid-Interactive Building Control

arXiv:2603.26005v2 Announce Type: replace Abstract: Grid-interactive building control has emerged as a promising approach for improving demand-side flexibility in modern power systems. Realistic studi

agentsarxiv-cs-ai

Build agents even faster with Gemini Enterprise Agent Platform’s fully-managed, remote MCP server

model-releasesgoogle-cloud-ai

A couple of months ago, we announced that over 50 Google-managed MCP servers are available. Today, we’ll dive into how to use the Gemini Enterprise Agent Platform remote MCP server to securely connect

CAN We Trust Your Results? A Cross-Dataset Study of Automotive IDS Evaluation

arXiv:2606.30430v1 Announce Type: cross Abstract: The increasing connectivity of modern vehicles has made securing in-vehicle communication networks a critical challenge. Intrusion Detection Systems (

Data-Driven Energy-Based Learning via Gibbs Measures on Hierarchical Structures

model-releasesarxiv-cs-lg

arXiv:2606.30064v1 Announce Type: new Abstract: We introduce a data-driven probabilistic framework for learning systems based on Gibbs measures on hierarchical structures. Unlike standard empirical ri

Enhancing Layer Interaction Using Key-Correlated Layer Attention

arXiv:2606.28405v1 Announce Type: new Abstract: Recent advances in network architecture design have introduced layer attention to enhance inter-layer interactions. In such frameworks, each layer queri

Evaluating LLMs on Chinese Topic Constructions: A Research Proposal Inspired by Tian et al. (2024)

arXiv:2504.14969v2 Announce Type: replace Abstract: This paper proposes a framework for evaluating large language models (LLMs) on Chinese topic constructions, focusing on their sensitivity to island

Exploration and Online Transfer with Behavioral Foundation Models

arXiv:2606.29980v1 Announce Type: new Abstract: Zero-shot Transfer in Reinforcement Learning (RL) aims to train an agent that can generate optimal policies for any reward function, without additional

safetyarxiv-cs-ai

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

FFAvatar: Feed-Forward 4D Head Avatar Reconstruction from Sparse Portrait Images

arXiv:2606.30347v1 Announce Type: cross Abstract: We present FFAvatar, a Transformer-based 3D Gaussian framework for fast construction of high-quality and animatable 4D head avatars from one or more r

From Phase to Phenomenon: Self-Supervised Learning of Subsurface Scattering with Minimal Phase-shift Inputs

arXiv:2606.29461v1 Announce Type: new Abstract: We propose a self-supervised pretraining framework for learning sub-surface scattering (SSS) light transport representations from minimal input. Our met

Generalization Analysis of Transformers in Distribution Regression

model-releasesarxiv-cs-lg

arXiv:2606.29256v1 Announce Type: cross Abstract: In recent years, models based on the Transformer architecture have seen widespread applications and have become one of the core tools in the field of

Applications

Gradient Boosted Mixed Models: Flexible Estimation of Mean and Variance Components for Clustered Data

arXiv:2511.00217v2 Announce Type: replace-cross Abstract: We introduce Gradient Boosted Mixed Models (GBMixed), a framework which extends boosting to clustered data by jointly modeling the mean and va

applicationsarxiv-cs-lg

HSAP: A Hierachical Sequence-aware Parallelism for Hybrid-Context Generative Models

arXiv:2606.30460v1 Announce Type: new Abstract: In this paper, we aim to combine the advantages of existing sequence parallelism paradigms and overcomes their drawbacks, the most serious of which is t

Applications

HyPER-GAN: Hybrid Patch-Based Image-to-Image Translation for Real-Time Photorealism Enhancement in Game Engines

arXiv:2603.10604v3 Announce Type: replace Abstract: Generative models are increasingly used in video game engines to enhance the photorealism of rendered images for visual synthetic data generation an

applicationsarxiv-cs-cv

Agents

HyphaeDB: A Living Knowledge Topology for Agent-First Memory

arXiv:2606.28781v1 Announce Type: new Abstract: Every existing vector database and agent memory framework treats memory as passive storage that agents query explicitly. No system propagates knowledge

agentsarxiv-cs-ai

Improved Predictive Performance and Interpretability for Mesomorphic Neural Networks Using Local Fidelity Regularization

model-releasesarxiv-cs-lg

arXiv:2606.29951v1 Announce Type: new Abstract: Interpretable Mesomorphic Neural Networks (IMNs) offer a promising framework that combines the predictive power of deep neural networks with the interpr

Information Dynamics of Language Communication

arXiv:2606.30096v1 Announce Type: new Abstract: Quantifying how meaning propagates through communicative exchanges remains underdeveloped in computational linguistics. Here we introduce an information

Tutorials

Investigating ECG Diagnosis with Ambiguous Labels using Partial Label Learning

arXiv:2512.11095v2 Announce Type: replace Abstract: Label ambiguity is an inherent and largely unaddressed challenge in real-world electrocardiogram (ECG) diagnosis, arising from overlapping condition

tutorialsarxiv-cs-lg

Agents

joined @LangChain almost three months ago and have spent a ton of time thinking about evals! i think that harbor is the future of eval frame…

joined @LangChain almost three months ago and have spent a ton of time thinking about evals! i think that harbor is the future of eval frameworks so really enjoyed being able to bring it into tighter

agentsharrison-chase--x

Learning as Observable Matrix Dynamics: Diffusive Relaxations versus Phase Transitions

arXiv:2606.29679v1 Announce Type: new Abstract: Observable Matrix Dynamics (OMD) is a diagnostic framework that probes the dynamics of high-dimensional internal representations of inputs by a neural n

LLMs and their Limited Theory of Mind: Evaluating Mental State Annotations in Situated Dialogue

arXiv:2509.02292v2 Announce Type: replace Abstract: What if large language models could not only infer human mindsets but also expose every blind spot in team dialogue such as discrepancies in the tea

Longitudinal Lesion Inpainting in Brain MRI via 3D Region Aware Diffusion

model-releasesarxiv-cs-ai

arXiv:2603.05693v2 Announce Type: replace-cross Abstract: Accurate longitudinal analysis of brain MRI is often hindered by evolving lesions, which bias automated neuroimaging pipelines. While deep gen

ML-Powered LDAP Reconnaissance Detection using Weak Supervision

arXiv:2606.28917v1 Announce Type: new Abstract: Lightweight Directory Access Protocol (LDAP) is a protocol that allows users to query and modify Active Directory (AD) data. By default, all users have

Momentum Guidance: Plug-and-Play Guidance for Flow Models

arXiv:2602.20360v2 Announce Type: replace-cross Abstract: Flow-based generative methods offer a simple and effective framework for high-fidelity generation, yet pretrained flow models are rarely used

Neural Galerkin Normalizing Flow for Transition Probability Density Functions of Diffusion Models

arXiv:2603.18907v2 Announce Type: replace Abstract: We propose a new Neural Galerkin Normalizing Flow framework to approximate the transition probability density function of a diffusion process by sol

NVIDIA BioNeMo Agent Toolkit Brings Accelerated AI to Life Sciences Researchers in Claude Science

model-releasesnvidia-genai-blog

Life sciences has entered an era of computational scale, and for more than a decade, NVIDIA has built the full GPU-accelerated computing stack — spanning hardware, frameworks, libraries, models, micro

OGM-CBF: Occupancy Grid Map-based Control Barrier Function for Safe Mobile Robot Control with Memory of out of View Obstacles

arXiv:2405.10703v4 Announce Type: replace Abstract: Safe control in unknown environments is a key challenge in mobile robotics. Control Barrier Functions (CBFs) provide a principled framework for guar

OLIVE: View-Augmented Latent Prediction with Waveform Reconstruction for Speech SSL

arXiv:2606.30356v1 Announce Type: new Abstract: We propose Online Latent prediction with Invariant Views and rEconstruction (OLIVE), a self-supervised speech representation learning framework that joi

Proteus: Automated Adversarial Robustness Testing for Audio Deepfake Detectors

model-releasesarxiv-cs-ai

arXiv:2606.29544v1 Announce Type: cross Abstract: We present Proteus, a framework developed at Resemble AI for automated robustness testing of our audio deepfake detection system. Given a detector, Pr

Rectifying Mask via Entropy for Distractor-Free 3DGS in Ambiguous Scenarios

arXiv:2606.29496v1 Announce Type: new Abstract: We present RefineSplat, a systematic framework that effectively constructs transient masks to identify diverse ambiguous distractors. To do this, we qua

RenderFormer++: Scalable and Physically Grounded Feed-Forward Neural Rendering

arXiv:2606.30380v1 Announce Type: cross Abstract: We present RenderFormer++, a scalable and physically grounded feed-forward neural rendering framework for global illumination in mesh scenes. Existing