Primary computational corpus for the manuscript "Large language models that near-perfectly evaluate products systematically recommend a worse familiar brand" (Affonso, Spears School of Business, Oklahoma State University). Contains 627,491 controlled product-recommendation trials across 30 frontier language models from...
Large language models have improved chiefly by scaling one monolithic computation. We argue the binding constraint is no longer missing components—language, reasoning, and knowledge are all present—but a missing composition in which they form a closed loop. We propose the Core Ring, an architecture with no single core....
Anbang Hou· Zenodo (CERN European Organi...· 0 citations
AbstractUMOSU/UMOKWAI — Foundational Phenomena and Domains of Complexity: What an AI Needs to Answer Reliably**This deposit collects the first systematic, phenomenon-by-phenomenon analysis conducted within the UMOSU/UMOKWAI ontological and epistemic-operational model. The model classifies reality through six foundation...
Marco Falsetti· Zenodo (CERN European Organi...· 0 citations
Large language models (LLMs) are often memory-bandwidth bound during autoregressive decoding, so reducing weight storage does not automatically produce parallel speedup when the compressed representation is irregular. We present SSQT, a post-training framework that jointly applies hardware-aligned structured sparsifica...
Qian-Sheng Song, Guolin Tang· Proceedings of the Internati...· 0 citations
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Large language models have improved chiefly by scaling one monolithic computation. We argue the binding constraint is no longer missing components—language, reasoning, and knowledge are all present—but a missing composition in which they form a closed loop. We propose the Core Ring, an architecture with no single core....
Anbang Hou· Zenodo (CERN European Organi...· 0 citations
The performance of single-GPU LLM inference is characterized by strong cross-layer interactions spanning model architecture, runtime scheduling, operator execution, and GPU microarchitecture. Unfortunately, a unified understanding of single-GPU LLM inference bottlenecks is still lacking due to two limitations: the lack...
Zong-Xing Zhao, Xiaqing Li, Ze-Kai Meng et al.· Proceedings of the Internati...· 0 citations
AbstractUMOSU/UMOKWAI — Foundational Phenomena and Domains of Complexity: What an AI Needs to Answer Reliably**This deposit collects the first systematic, phenomenon-by-phenomenon analysis conducted within the UMOSU/UMOKWAI ontological and epistemic-operational model. The model classifies reality through six foundation...
Marco Falsetti· Zenodo (CERN European Organi...· 0 citations
As Large Language Models (LLMs) are increasingly used as a primary source of information and advice, understanding their alignment to humans in terms of values becomes a pressing concern. A growing literature has leveraged large scale surveys to investigate to what extent LLMs'and humans'stated values and opinions alig...
Maria-Louisa Wightman, Guillaume Bied, T. De Bie· Proceedings of the AAAI/ACM...· 0 citations
The state of the art in AI for requirements engineering research leading up to the transformation, before reviewing advances in LLMs, and two subsequent research areas: prompt programming and generalist SE agents, which combine multiple LLM advances to yield semi-autonomous processes that complete SE tasks.
Travis D. Breaux, Anmol Singhal· Requirements Engineering· 0 citations
The need for custom validation capabilities to ensure that models produced by both humans and LLMs are trustworthy enough to serve as the foundation of the MBSE ecosystem is addressed.
Á. Tóth, Levente Bajczi, Ármin Zavada et al.· Proceedings of the ACM/IEEE...· 0 citations
OntoSTL defines a bidirectional transformation between STL and OWL and applies equivalence-preserving canonicalization rules, including implication elimination, supported Negation Normal Form (NNF) conversion, Boolean simplification, associative flattening, and deterministic operand ordering.
Haitham Al-Shami, Riku Ala-Laurinaho, Xin-Yi Tu et al.· Proceedings of the ACM/IEEE...· 0 citations
Business Process Modeling (BPM) is a key and complex activity in Software and Systems Engineering. As a consequence, any relevant assistance integrated into the BPM tooling can be highly beneficial. Historically, Natural Language Processing (NLP) techniques have already been used in this context. However, the recent de...
Andrey Sadovykh, Loay Chlih, Bilal Said et al.· Proceedings of the ACM/IEEE...· 0 citations
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
Microsoft Research Blog· microsoft.comOct 12, 2026
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
