Search: “framework”

Closed-loop coupling of personalised and foundation models for real-time treatment guidance with MRI

arXiv:2607.00500v1 Announce Type: cross Abstract: Image-guided therapies, including radiotherapy, biopsy and deep brain stimulation, rely on real-time targeting of anatomical structures. However, in t

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Tutorials

CogTax: A Four-Level Cognitive Taxonomy for Command-Line Computing Education

DGX agent

arXiv:2607.00140v1 Announce Type: cross Abstract: As computing education expands beyond traditional programming into operational domains such as systems administration and command-line environments, e

tutorialsarxiv-cs-cl

2 Jul 2026

'consensus' can't just built by big tech! let's all be careful of regulatory capture and extreme concentration of power!

'consensus' can't just built by big tech! let's all be careful of regulatory capture and extreme concentration of power! NEW: Anthropic announces it is drafting a consensus framework with Amazon, Micr

safetygary-marcus--x

Agents

Deconfounded Lifelong Learning for Autonomous Driving via Dynamic Knowledge Spaces

arXiv:2603.14354v3 Announce Type: replace-cross Abstract: End-to-End autonomous driving (E2E-AD) systems face challenges in lifelong learning, including catastrophic forgetting, difficulty in knowledg

agentsarxiv-cs-ai

Detecting the Undetectable: Enhancing Unsupervised time series Anomaly Detection via Active Learning

arXiv:2607.00720v1 Announce Type: cross Abstract: Despite the increasing sophistication of industrial AI systems, the ability to reliably detect subtle and noisy anomalies in complex time series data

tutorialsarxiv-cs-ai

ECoSim: Data Efficient Fine-Tuning for Controllable Traffic Simulation

arXiv:2607.00545v1 Announce Type: new Abstract: Controllable traffic simulation is critical for testing autonomous driving systems, yet existing approaches often require retraining large generative mo

From 'Strings' to 'Things' for Personal Knowledge Graphs: Evaluating LLM Triple Extraction for Recommendation Systems

arXiv:2607.00003v1 Announce Type: cross Abstract: Personal Knowledge Graphs (PKGs) offer a privacy-preserving framework for modeling user preferences, yet constructing them from unstructured, decentra

From Structural Equation Modelling to Double Machine Learning: Robustness Analysis for Survey-Based Research

model-releasesarxiv-cs-lg

arXiv:2607.00512v1 Announce Type: new Abstract: Structural equation modelling (SEM) is widely used in survey-based business and information systems research to assess latent constructs and theory-driv

Generated Contents Enrichment

arXiv:2405.03650v4 Announce Type: replace Abstract: We study Generated Contents Enrichment (GCE), a conditional image-generation task in which a sparse scene description is first enriched through an e

GenSP: Consistent Spherical Parameterization via Learning Shape Generative Models

arXiv:2607.00492v1 Announce Type: new Abstract: We introduce GenSP, a data-driven framework that learns consistent spherical parameterizations across a collection of genus-0 shapes. Instead of optimiz

tutorialsarxiv-cs-cv

Homogenization of ell_2-Adversarial Training in High-Dimensions: Exact Dynamics under Stochastic Gradient Descent

model-releasesarxiv-cs-lg

arXiv:2607.00207v1 Announce Type: cross Abstract: We develop a framework for analyzing the learning dynamics of ell_2-adversarial training of single-index models on Gaussian mixtures in the high-dimen

Learning Expert Strategy for Autonomous Robotic Endovascular Intervention via Decoupled Procedural Execution

arXiv:2607.00066v1 Announce Type: new Abstract: Endovascular interventions are high-stakes procedures requiring precise device operation within complex and tortuous vascular anatomies. Autonomous endo

safetyarxiv-cs-ro

Learning from Demonstration via Spatiotemporal Tubes for Unknown Euler-Lagrange Systems

arXiv:2607.00534v1 Announce Type: new Abstract: We present STT-LfD, a unified Learning from Demonstration (LfD) framework that integrates motion learning with control for unknown Euler-Lagrange system

safetyarxiv-cs-ro

Local Ai

Learning to Watch: Active Video Anomaly Understanding via Interleaved Policy Optimization

arXiv:2607.00622v1 Announce Type: new Abstract: Video anomaly understanding (VAU) relies on sparse, context-dependent cues. However, existing passive paradigms suffer from observational aliasing, wher

local-aiarxiv-cs-cv

Linkify: Learning from Interface-Augmented Assembly Graphs

model-releasesarxiv-cs-cv

arXiv:2607.01205v1 Announce Type: new Abstract: We present Linkify, a framework for learning from interface-augmented assembly graphs to enable context-aware part retrieval in mechanical assemblies. W

LIST3R: Long-sequence Instance-aware 3D Reconstruction

arXiv:2607.00375v1 Announce Type: new Abstract: We present LIST3R, an instance-aware framework for long-sequence 3D reconstruction inspired by the way humans organize spatial memory around stable and

LiteParse runs anywhere, including inside agent runtimes. To prove it, we built an email processing assistant using @flueai (the agentic fra…

model-releasesjerry-liu--x

LiteParse runs anywhere, including inside agent runtimes. To prove it, we built an email processing assistant using @flueai (the agentic framework by @astrodotbuild), @resend webhooks, and @tursodatab

llm-coding-agent 0.1a0

model-releasessimon-willison

Release: llm-coding-agent 0.1a0 Another Fable 5 experiment. Now that my LLM library has evolved into more of an agent framework it's time to see what a simple coding agent would look like built on it.

MG-SpaIR: Multi-grade Sparse-guided Implicit Representation for Training-Data-Free Image Restoration

arXiv:2607.00138v1 Announce Type: new Abstract: MG-SpaIR is a training-data-free framework for restoring a clean image from a single observation corrupted by a mixture of blur, downsampling, noise, an

Applications

PedNStream: Scalable Network Flow Simulation for Pedestrian Traffic Management

arXiv:2607.01021v1 Announce Type: new Abstract: Large-scale crowd management requires pedestrian simulations that are both computationally efficient and compatible with feedback-based control. However

applicationsarxiv-cs-ai

PRISM-VO: Scale-Aware Visual Odometry Using Photometric Plenoptic Bundle Adjustment

arXiv:2607.00176v1 Announce Type: new Abstract: We introduce PRISM-VO, a novel pure optimization-based sparse photometric visual odometry framework for focused plenoptic cameras. The core of PRISM-VO

Applications

Sensorless Four-Channel Control Architecture Using Inverse Dynamics Modeling for Human-Scale Bilateral Teleoperation

arXiv:2607.01201v1 Announce Type: new Abstract: The four-channel teleoperation architecture is a well-established framework for achieving transparency in bilateral systems. However, its performance in

applicationsarxiv-cs-ro

SynLaD: Latent Diffusion for Generating Synthesizable Molecules Conditioned on 3D Pharmacophore Profiles

arXiv:2607.01105v1 Announce Type: new Abstract: We present SynLaD, a latent diffusion framework for small-molecule generation that unifies ligand-based drug design objectives (what to make) with synth

tutorialsarxiv-cs-lg

Vitality-Aware Compression for Efficient Image-to-Shape Diffusion Transformers

arXiv:2607.00382v1 Announce Type: new Abstract: We propose the first compression approach for image-to-shape Diffusion Transformers (DiTs) that substantially reduces model size while preserving geomet

Tools

5/ V1: Unifying Generation and Self-Verification for Parallel Reasoners Paper: https://arxiv.org/abs/2603.04304

This paper presents V1, a framework that unifies text generation with self-verification mechanisms to enable parallel reasoning processes in language models. The approach allows models to generate mul

toolstogether-ai--x

Hardware

9/ ParallelKernelBench: Benchmarking LLMs on Multi-GPU Kernel Generation Paper: https://www.alphaxiv.org/abs/2606.parallel-kernel-bench

ParallelKernelBench is a benchmarking framework designed to evaluate large language models' ability to generate optimized GPU kernels for multi-GPU computing environments. The benchmark assesses LLMs

hardwaretogether-ai--x

A Self-Evolving Agentic System for Automated Generation and Execution of Biological Protocols

arXiv:2606.31763v1 Announce Type: new Abstract: Autonomous wet-lab experimentation requires more than plausible protocol text: biological intent, quantitative procedures, device constraints and experi

A Tutorial on Autonomous Fault-Tolerant Control Using Knowledge-Grounded LLM Agents

arXiv:2606.31635v1 Announce Type: cross Abstract: Fault recovery in process plants still relies heavily on plant operators, especially when faults fall outside predefined supervisory logic. Operators

safetyarxiv-cs-ai

AC3S: Adaptive Conditioning for 3D-Aware Synthetic Data Generation

arXiv:2606.31204v1 Announce Type: new Abstract: Synthetic data generation has emerged as a powerful tool for improving data scalability in computer vision. Recent diffusion-based pipelines have demons

Accelerating Conformal Prediction via Approximate Leave-One-Out

arXiv:2606.31915v1 Announce Type: cross Abstract: While conformal prediction provides a general framework for uncertainty quantification in predictive inference, its application is often limited by co

researcharxiv-cs-lg

AgentBound: Verifiable Behavioral Governance for Autonomous AI Agents

arXiv:2606.30970v1 Announce Type: new Abstract: Autonomous AI agents increasingly perform consequential actions on behalf of human principals, including financial transactions, external communications

Behavior Cloning is Not All You Need: The Optimality of On-Policy Distillation for Noisy Expert Feedback

arXiv:2606.30923v1 Announce Type: cross Abstract: Imitation Learning is a natural framework for learning in sequential decision-making systems and has emerged as the dominant paradigm through which we

safetyarxiv-cs-ai

Can Physician Expertise Improve Machine Learning Identification of Delirium?

arXiv:2606.30651v1 Announce Type: cross Abstract: Delirium is common in hospitalized patients and is often missed in routine care. We present a user-centered interactive machine learning (UC-iML) fram

Agents

Contrastive Reflection for Iterative Prompt Optimization

arXiv:2606.30840v1 Announce Type: new Abstract: LLM agents are becoming central to information retrieval: they issue retrieval queries, synthesize answers, and increasingly serve as judges for IR eval

agentsarxiv-cs-ai

Diffusion Crossover: Defining Evolutionary Recombination in Diffusion Models via Noise Sequence Interpolation

arXiv:2604.14790v2 Announce Type: replace Abstract: Interactive Evolutionary Computation (IEC) provides a powerful framework for optimizing subjective criteria such as human preferences and aesthetics

researcharxiv-cs-ai

DynFly: Dynamic-Aware Continuous Trajectory Generation for UAV Vision-Language Navigation in Urban Environments

model-releasesarxiv-cs-cv

arXiv:2606.31654v1 Announce Type: cross Abstract: Recent advances in multimodal large models have significantly improved UAV vision-language navigation (UAV-VLN) by enhancing high-level perception and

Fable is back! @trq212 now giving us a Field Guide to Fable at @aiDotEngineer World’s Fair.

Trq212 is presenting a Field Guide to Fable at AI.Engineer World's Fair, indicating renewed interest or development in the Fable project or framework. This presentation likely covers Fable's features,

tutorialsswyx--x

Tools

/goal ?

The post likely discusses the '/goal' command or feature, possibly in the context of a development tool, framework, or platform. Without access to the specific content, it appears to relate to functio

toolsswyx--x

Agents

Investigating Multi-Agent Deliberation in Law

arXiv:2606.30906v1 Announce Type: new Abstract: Artificial Intelligence is increasingly applied to the field of law, and has the potential to increase access to justice. One particular movement that i

agentsarxiv-cs-ai

Applications

Joint discovery of governing partial differential equations from multi-source datasets by competitive optimization

arXiv:2606.30699v1 Announce Type: new Abstract: Discovering governing equations directly from observational data is a key step towards interpretable scientific machine learning. Current data-driven ap

applicationsarxiv-cs-lg

LaMP: Learning Vision-Language-Action Policy with 3D Scene Flow as Latent Motion Prior

arXiv:2603.25399v2 Announce Type: replace Abstract: We introduce extbf{LaMP}, a dual-expert Vision-Language-Action framework that embeds dense 3D scene flow as a latent motion prior for robotic manipu

Learning a Sampling-Free Variational DNN Plugin from Tiny Training Sets to Refine OOD Segmentation With Uncertainty Estimation

arXiv:2606.15837v2 Announce Type: replace Abstract: Deep neural networks (DNNs) frequently fail to generalize to out-of-distribution (OOD) medical images because of variations in scanners and acquisit

LLM-Empowered Agentic MAC Protocols: A Dynamic Stackelberg Game Approach

arXiv:2510.10895v2 Announce Type: replace Abstract: Medium Access Control (MAC) protocols, essential for wireless networks, are typically manually configured. While deep reinforcement learning (DRL)-b

safetyarxiv-cs-ai

Local Ai

MetricHMSR:Metric Human Mesh and Scene Recovery from Monocular Images

arXiv:2506.09919v4 Announce Type: replace Abstract: We introduce MetricHMSR, a novel framework for recovering metric human meshes and 3D scenes from a single monocular image. Existing methods struggle

local-aiarxiv-cs-cv

OopsieVerse: A Safety Benchmark with Damage-Aware Simulation for Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.31993v1 Announce Type: new Abstract: While robotic manipulation capabilities have advanced rapidly, physical safety remains a major barrier to deploying household robots: task success is in

Local Ai

Partition-Guided Distance Saliency: Bridging Decision and Objective Spaces in Many-Objective Optimization

arXiv:2606.30836v1 Announce Type: new Abstract: Explainability in Many-Objective Optimization (MaO) is currently hindered by the escalating complexity of the Pareto front, which renders the relationsh

local-aiarxiv-cs-lg

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

researcharxiv-cs-ai

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

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