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2,572 papers
Author's note. This monograph consolidates the program corpus listed at the foot of this description. As the program has grown, each new result was propagated across an expanding set of documents, and the set became unmanageable. Consolidation also surfaced inconsistencies between documents written at different stages...
A gate-aware pruning strategy is developed to evaluate hidden-unit importance by jointly considering gate weights and gradient sensitivity, enabling structural compression while preserving critical temporal information and substantially improving computational efficiency.
QuantNature Technical White Paper (Document ID: QN-UARI-2026-V2.0) Title Universal Acoustic Resonance Imaging (UARI v2.0): Real-Time Multi-Target Soliton Discrimination and In-Situ Near-Field Ego-Noise Nulling across Sub-Wavelength Arrays Author: QuantNature Global (https://www.quantnature.com)Release Date: September 9...
The sudden structural transformations experienced by cognitive systems duringevolution are difficult to characterise with traditional continuous dynamics frameworks. This paper constructs a mathematical framework that maps cognitive statespaces to sequences of filtered simplicial complexes, and employs persistent homol...
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The quantification of causal emergence faces a fundamental difficulty: how canmacroscopic causal power be identified in microscopic dynamics without falling intoa circular reliance on a presupposed coarse-graining strategy? In this paper, theconstraint network of a cognitive system is modelled as a simplicial complex,...
QuantNature Technical White Paper (Document ID: QN-UARI-2026-V2.0) Title Universal Acoustic Resonance Imaging (UARI v2.0): Real-Time Multi-Target Soliton Discrimination and In-Situ Near-Field Ego-Noise Nulling across Sub-Wavelength Arrays Author: QuantNature Global (https://www.quantnature.com)Release Date: September 9...
We present a discrete theory of gravity whose microscopic primitive is a conserved ledger whose dynamical step is a single one-coordinate, one-bit posting, and we prove exactly where such a theory must import geometry and how much of general relativity it recovers once it does. Three unconditional theorems carry the ne...
A near-universal test of independence: the three-pole calibrated envelope, its joint null law, and dependent-null higher-criticism attainment William J. Dwyer, MD, MPH, FAAP — Department of Mathematics and Statistics, University of Massachusetts Lowell. ORCID 0009-0004-0855-7222. Concept DOI (always resolves to the lat...
Artificial intelligence (AI) models are a widespread tool employed across a broad range of applications, made possible by advanced architectures, learning algorithms and hardware. A growing consensus in the field holds that the development of highly efficient models can no longer be decoupled from the underlying hardwa...
This study is intended to serve as a structured reference for the development of scalable, trustworthy, and intelligent IoV systems by highlighting state-of-the-art techniques, open research gaps, and future directions.
This work builds on Wang et al.'s taxonomy of Continuum Orchestration Systems employing DRL techniques and extends it with two further dimensions, measuring how LLMs are exploited and bridging the incommensurable per-tier signals and the LLM Orchestrator.
The intersection of Big Data Analytics and Industrial Internet of Things (IIoT) introduces a transformative potential to improve operational efficiency, predictive maintenance, and decision-making in smart industrial systems. But such methods rarely deployed in practice, are not interoperable, and are not scalable. Thi...
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
Associate Professor Cathy Wu uses reinforcement learning to help map out improvements to transportation and other multifaceted systems.
Announcing Gemini 4 Argon, our frontier model for real-world coding, enterprise knowledge work and cyber defense, rolling out soon.
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