Search: “framework”

arXiv:2510.01569v3 Announce Type: replace Abstract: We present InvThink, a training and prompting framework that requires the model to enumerate, analyze, and constrain potential failures before gener

arXiv:2605.05949v2 Announce Type: replace Abstract: Algorithmic problem solving serves as a rigorous testbed for evaluating structured reasoning in AI coding systems, as it directly reflects a model's

arXiv:2605.06709v1 Announce Type: new Abstract: This paper addresses PDE-based control for flexible multibody robotic systems, presenting a subsystem-based framework for serial manipulators with arbit

arXiv:2512.12116v3 Announce Type: replace Abstract: Learned time-series models, whether continuous or discrete, are widely used for forecasting the states of dynamical systems but suffer from error ac

arXiv:2605.07267v1 Announce Type: new Abstract: Personalized healthcare decisions require reasoning about how physiological and behavioral variables influence an individual patient over time. Existing

arXiv:2605.06474v2 Announce Type: replace-cross Abstract: We present a novel theoretical framework, Q-MMR, for off-policy evaluation in finite-horizon MDPs. Q-MMR learns a set of scalar weights, one f

arXiv:2605.07096v1 Announce Type: cross Abstract: Evaluating a new model on an existing benchmark is often necessary to understand its behavior before deployment. For modern evaluation frameworks, gen

arXiv:2605.07413v1 Announce Type: new Abstract: Obtaining accurate class labels is often costly or unreliable, and may also be limited by privacy or other practical conditions. Compared with asking an

arXiv:2605.07634v1 Announce Type: cross Abstract: We consider a first order stochastic optimization framework where, at each iteration, K independent identically distributed (i.i.d.) data point sample

arXiv:2605.07102v1 Announce Type: new Abstract: Evaluating literary quality requires assessing interpretive dimensions such as cultural representation, emotional depth, and philosophical sophisticatio

arXiv:2509.25584v2 Announce Type: replace Abstract: Vision-language models achieve incredible performance across a wide range of tasks, but their large size makes inference costly. Recent work has sho

arXiv:2605.07908v1 Announce Type: cross Abstract: Belief functions are a powerful and popular framework for the mathematical characterisation of uncertainty, in particular in situations in which lack

arXiv:2605.06736v1 Announce Type: cross Abstract: Accurate sleep stage classification across datasets remains challenging due to variability in EEG channel montages, sampling rates, recording environm

arXiv:2605.07717v1 Announce Type: cross Abstract: Despite the widespread adoption of agile methods, achieving true agility at scale remains elusive. Large-scale agile frameworks remain largely human-c

This release fixes a macOS 26 target leakage issue in the v3 metallib component for the MLX framework. The fix addresses a problem where Metal library compilation was incorrectly targeting macOS 26, w

This release candidate addresses a macOS 26 target leakage issue in the v3 metallib component of Ollama, a machine learning framework. The fix prevents incorrect macOS version targeting that was affec

arXiv:2605.06761v1 Announce Type: new Abstract: The web is complex, open-ended, and constantly changing, making it challenging to scale training data for visual web agents. Existing data collection at

We introduce a framework for learning latent representations of 4D objects which are descriptive, faithfully capturing object geometry and appearance; compressive, aiding in downstream efficiency; and

arXiv:2605.04813v1 Announce Type: new Abstract: With the rapid development of cloud computing and Web services, Quality of Service (QoS) has become a key criterion for service selection and recommenda

B9055 is the latest version of llama.cpp, released on May 7, 2026. Llama.cpp is an LLM inference framework implemented in C/C++ that enables efficient large language model execution with broad hardwar

b9060 is a release build identifier for llama.cpp, an open-source LLM inference framework implemented in C/C++. This build represents a snapshot in the project's ongoing development, containing bug fi

arXiv:2603.20684v2 Announce Type: replace Abstract: Echo State Networks (ESNs) are a reservoir computing framework widely used for nonlinear time-series prediction. However, despite their effectivenes

ComfyUI-Lora-FindingLora is a specialized loader extension for the ComfyUI image generation framework that streamlines LoRA (Low-Rank Adaptation) model management through fuzzy search functionality, e

arXiv:2602.10043v2 Announce Type: replace Abstract: Head magnetic resonance imaging (MRI) data are routinely collected and shared for research under strict regulatory frameworks that require the remov

arXiv:2408.09929v2 Announce Type: replace-cross Abstract: Inspired by the idea of Positive-incentive Noise (Pi-Noise or pi-Noise) that aims at learning the reliable noise beneficial to tasks, we scien

arXiv:2605.04708v1 Announce Type: new Abstract: From neural ODEs to continuous-time machine learning, differentiable solvers allow physics, optimization, and simulation to become trainable components

arXiv:2605.03986v1 Announce Type: new Abstract: Multi-Agent Systems (MAS) built using AI agents fulfill a variety of user intents that may be used to design and build a family of related applications.

arXiv:2603.26178v2 Announce Type: replace Abstract: We introduce the Geometric Evolution Graph Convolutional Network (GEGCN), a novel framework that enhances graph representation learning through expl

arXiv:2605.04853v1 Announce Type: new Abstract: We propose HIN-LRI, a hybrid framework that augments a classical numerical solver with a neural operator trained to correct the solver's structured trun

arXiv:2605.04425v1 Announce Type: new Abstract: Vision-language models such as CLIP achieve strong visual-textual alignment, but often suffer from overfitting and limited interpretability when adapted

Grok Imagine is an image quality model that has been discussed on the ComfyUI blog, likely covering its capabilities for evaluating or enhancing image generation quality within the ComfyUI framework.

arXiv:2505.00835v2 Announce Type: replace-cross Abstract: Appropriate modelling of extreme skew surges is crucial, particularly for coastal risk management. Our study focuses on modelling extreme skew

A security update for Next.js released in May 2026 by Vercel addressing identified vulnerabilities in the framework. The release likely includes patches for security issues affecting Next.js applicati

Nous Research has developed a ComfyUI skill integration for their Hermes agent framework that enables creative workflows through ComfyUI's node-based image generation system. This skill allows the Her

arXiv:2605.05118v1 Announce Type: new Abstract: Recently, Deng et al. (2026) proposed Generative Modeling via Drifting (GMD), a novel framework for generative tasks. This note presents an analysis of

arXiv:2605.04809v1 Announce Type: new Abstract: This article proposes a general optimization framework for solving hand-eye calibration problem. Unlike traditional methods, an iterative algorithm base

arXiv:2605.03491v1 Announce Type: new Abstract: Most evaluations of autonomous driving policies under adversarial conditions are conducted in simulation, due to cost efficiency and the absence of phys

arXiv:2605.04965v1 Announce Type: new Abstract: Optimal transport (OT) is a central framework for modeling distribution shifts. Because OT compares distributions directly in input space, a well-design

arXiv:2605.04305v1 Announce Type: new Abstract: We introduce SWAN (Semantic Watermarking with Abstract Meaning Representation), a novel framework that embeds watermark signatures into the semantic str

Theories are proven by accurate predictions. I first read @GaryMarcus in the late ’90s, and his ideas helped shape my deterministic ML frameworks, GAIuS & KATO. He’s been proven right repeatedly, yet

arXiv:2605.04201v1 Announce Type: new Abstract: We propose a topology-constrained quantized nnUNet framework for efficient and anatomically accurate 3D tooth segmentation, addressing the challenges of

arXiv:2605.04107v1 Announce Type: cross Abstract: Production agent frameworks (OpenAI Function Calling, Anthropic Tool Use, MCP) transmit tool schemas as JSON, a format designed for machine parsing, n

arXiv:2605.04527v1 Announce Type: new Abstract: We introduce a framework for learning latent representations of 4D objects which are descriptive, faithfully capturing object geometry and appearance; c

arXiv:2602.10094v2 Announce Type: replace Abstract: We present 4RC, a unified feed-forward framework for 4D reconstruction from monocular videos. Unlike existing approaches that typically decouple mot

arXiv:2605.03212v1 Announce Type: cross Abstract: Modeling latent clinical constructs from unconstrained clinical interactions is a unique challenge in affective computing. We present ADAPTS (Agentic

arXiv:2605.01401v1 Announce Type: cross Abstract: Tacit knowledge embedded in expert practice remains difficult to capture, formalise, and scale. While AI-driven educational systems have advanced pers