Search: “concepts”

arXiv:2606.21889v1 Announce Type: new Abstract: We study fixed-precision ranking-and-selection in structured settings where the answer may be non-unique and where noisy estimates may temporarily admit

arXiv:2606.21289v1 Announce Type: new Abstract: Nondestructive detection methods, based on vibrational spectroscopy, are vitally important in a wide range of applications including industrial chemistr

arXiv:2606.22443v1 Announce Type: new Abstract: Compliant mechanisms are important in robotics because they can improve adaptability, safety, and energy efficiency while reducing hardware complexity.

arXiv:2606.21705v1 Announce Type: new Abstract: Dataset distillation (DD) has proven to reduce training cost while preserving accuracy. While promising, the factors that make one distilled dataset mor

arXiv:2606.23548v1 Announce Type: cross Abstract: This paper presents SuperCond-GNN, a graph neural network-based surrogate model for predicting the voltage distribution in high-temperature supercondu

Want to get into Hermes Agent but don't know where to start? Perhaps you're not ready to invest multiple hours of listening to my voice (unthinkable!), so I made a quick 10 minute video to get you up

1/ Regardez cette courbe. C’est la fréquence du terme « white supremacy » dans la presse américaine (travaux de David Rozado). Explosion brutale après 2013. Pas une explosion du racisme réel. Une expl

arXiv:2606.11482v1 Announce Type: cross Abstract: Understanding and predicting how social beliefs evolve in response to events -- from policy changes to scientific breakthroughs -- remains a fundament

arXiv:2606.12016v1 Announce Type: cross Abstract: Model post-training, and in particular reinforcement learning (RL), is one of the primary mechanisms by which developers can shape models' values and

arXiv:2604.25018v2 Announce Type: replace-cross Abstract: The Internet of Everything (IoE) represents an evolution of the Internet of Things (IoT) by integrating people, data, processes, and things in

arXiv:2510.24515v2 Announce Type: replace Abstract: The Team Orienteering Problem (TOP) generalizes many real-world multi-agent scheduling and routing tasks that occur in autonomous mobility, aerial l

arXiv:2606.11860v1 Announce Type: new Abstract: In this paper, we introduce Representation Prediction via Autoencoding using Iterative Refinement (RePAIR) - a novel self-supervised representation lear

arXiv:2606.11320v1 Announce Type: new Abstract: In this paper, we present a novel set of related models for semantic segmentation of node-link diagrams. These diagrams are frequently used to represent

arXiv:2412.09023v3 Announce Type: replace Abstract: Channel and spatial attention mechanisms introduced in earlier work enhance the representational capabilities of deep convolutional neural networks

arXiv:2512.11393v2 Announce Type: replace Abstract: Humans can intuitively parallelise complex activities, but can a model predict this from observing a single person? Given one egocentric video, we i

arXiv:2606.12289v1 Announce Type: cross Abstract: As Artificial Intelligence models grow in complexity, interpretability has become an indispensable tool for understanding, debugging, and controlling

arXiv:2512.13765v2 Announce Type: replace-cross Abstract: The forward problem in electrocardiology, computing body surface potentials from cardiac electrical activity, is traditionally solved using ph

arXiv:2606.10044v1 Announce Type: new Abstract: Businesses are increasingly adopting AI-enabled tools to improve productivity, reduce costs, and enhance products and services. However, the transformat

arXiv:2606.10777v1 Announce Type: new Abstract: Uncertainty estimation is critical for deploying machine learning models in high-stakes settings. However, classical calibration only assesses the relia

arXiv:2606.10736v1 Announce Type: cross Abstract: Large online courses generate thousands of student questions directed at conversational AI teaching assistants, yet these interaction logs remain larg

arXiv:2606.10799v1 Announce Type: new Abstract: Large Language Models (LLMs) struggle to rigorously verify complex mathematical proofs. Standard global evaluation approaches suffer from 'context poiso

Everyone Operating At The Frontier Satya Nadella, Chairman & CEO, Microsoft, interviewed by @saranormous & @eladgil (No Priors) and @swyx (Latent Space) Crossover special at Microsoft Build 2026. Summ

arXiv:2606.10450v1 Announce Type: new Abstract: DiffC provides a principled way to reuse pre-trained diffusion models for lossy compression, but its encoding and decoding procedures remain slow becaus

arXiv:2606.10861v1 Announce Type: cross Abstract: LLM-powered chatbots are increasingly embedded in everyday workflows, raising sustainability concerns due to their energy use. Most mitigation strateg

arXiv:2606.09944v1 Announce Type: cross Abstract: GDP per capita is the default lens through which governibng bodies track the economic prosperity and consequences of economic events , yet it is blind

Here is a thought that might sounds odd/wrong the first time you hear it: recorded media is a phase. A long one, but a phase. For most of human history, media was live. Stories were told around fires

arXiv:2606.10358v1 Announce Type: cross Abstract: Learning Bayesian network (BN) structure from sparse discrete data is hard: when each instance records only a few variables, most variable pairs lack

arXiv:2606.10975v1 Announce Type: new Abstract: Finding convenient spaces in which certain hypotheses regarding an assumed sparse structure of natural signals hold true has become a desirable result i

arXiv:2606.10458v1 Announce Type: cross Abstract: We derive the optimal quantizer of a real-valued random variable W with distribution P_W such that 1) the distribution of the quantization output X th

arXiv:2606.10806v1 Announce Type: new Abstract: Moonshine is an autonomous agent whose central objective is to generate mathematical conjectures. Its core capability is to extract structure from class

arXiv:2606.10250v1 Announce Type: cross Abstract: Class imbalance is a common problem in deep learning that severely degrades performance. In federated learning (FL), it is a critical factor contribut

arXiv:2507.13595v3 Announce Type: replace Abstract: Reconstructing accurate implicit surface representations from point clouds remains a challenging task, particularly when data is captured using low-

arXiv:2606.09901v1 Announce Type: cross Abstract: Diffusion-based generative models enable powerful image editing capabilities, but achieving precise control while maintaining fidelity and safety rema

arXiv:2406.08726v3 Announce Type: replace Abstract: Large language models (LLMs) generate text that reinforces standard language ideology: a bias towards certain language varieties that are granted mo

arXiv:2606.10106v1 Announce Type: cross Abstract: The term agent harness now circulates widely in software engineering with generative artificial intelligence. It names the layer that wraps a language

This post traces the historical lineage of machine learning techniques, suggesting that LatentMoE builds upon a chain of progressively developed methods including MLA, LoRA, and SVD, emphasizing how m

arXiv:2606.08369v1 Announce Type: cross Abstract: A growing body of work points to the great promise of AI systems that can continually expand their capabilities as they operate in an open-ended envir

arXiv:2606.08934v1 Announce Type: new Abstract: Recurrent neural networks maintain a hidden state h_t, but its probabilistic meaning is often unclear. We study hidden-state stability through backward

arXiv:2606.09638v1 Announce Type: new Abstract: Differential equations play a critical role in scientific discovery because they provide a mathematical framework to describe the behaviour of physical

arXiv:2606.08068v1 Announce Type: new Abstract: Multi-agent large language model (LLM) systems often fail to reliably outperform a single strong model equipped with best-of-N sampling. We argue that a

arXiv:2606.07548v1 Announce Type: cross Abstract: The MedHopQA challenge presents a critical test for Large Language Models (LLMs): complex, multi-hop reasoning in the high-stakes biomedical domain. T

arXiv:2606.07628v1 Announce Type: cross Abstract: While the eugenic roots of computer vision are well-documented in critical technology studies, less attention has been paid to the operational mechani

arXiv:2606.08806v1 Announce Type: cross Abstract: Artificial Intelligence (AI) and Large Language Models (LLMs) are increasingly used in autonomous software testing; however, AI-generated test artifac

arXiv:2606.07619v1 Announce Type: new Abstract: We present a Graph Neural Network (GNN) framework for the classification of finite groups according to their solvability. Using graph representations as

arXiv:2502.19049v3 Announce Type: replace Abstract: Stochastic differential equations (SDEs) describe dynamical systems where deterministic flows, governed by a drift function, are superimposed with r

This OpenAI publication likely discusses how governments and policymakers should approach industrial policy in an era dominated by artificial intelligence and computational intelligence capabilities.