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large language models

2,160 papers

#large language models Open access Sep 2026

A Structural Interpretation of the 3D Poincaré Conjecture via the n=2 Uniqueness Theorem and Perelman's Ricci Flow ── Uniformization of Simply Connected Closed 3-Manifolds toward the Sphere, and a Structural Correspondence with Perelman's W-Entropy Functional ── [Paper 07]

For the three-dimensional Poincaré conjecture ── "every simply connected closed 3-manifold is homeomorphic to the 3-sphere S³" (Perelman's theorem) ── we present a structural interpretation based on the n=2 uniqueness theorem (dm/dr = 4π). The argument proceeds in three stages. Scope of this paper (scope note): This pa...

Yuuki Yamagishi · 0 citations
#large language models Open access Sep 2026

Physical Law as a Description Language of the Universe OS ── On the Solid Angle 4π Shared by Mechanics, Electromagnetism and Gravity ── [Paper 13]

The solid angle 4π appears again and again in the formulas of modern physics. This paper reads the universe as a single large informational rendering system, the "Universe OS," places the mass m as "a 4π spherical patch that specifies 3D space (the UI)," and surveys expressions for resistance, kinetic energy, volume re...

Yuuki Yamagishi · 0 citations
#large language models Open access Sep 2026

The 4π Mass Cancellation Theorem ── The Emergence of Pure Solid Angle in Inverse-Square Fields and the Mathematical Structure of Frictionless Equilibrium (Zero-Tension) ── [Paper 02]

In three-dimensional Euclidean space, when integrating over a ball whose density follows the inverse-square law ρ(r) = 1/r², the Jacobian r² of the volume element and the density 1/r² cancel. As a result, the total mass within the unit ball coincides with the total solid angle of 3D space, 4π (the full measure in stera...

Yuuki Yamagishi · 0 citations
#large language models Open access Sep 2026

A Structural Interpretation of the 4D Poincaré Conjecture and Exotic Structures via the n=3 Uniqueness Theorem and Hopf Fibration ── 2π² Hyperspherical Unit Mass Patch, 16π² Toroidal Cocoon, and the Information-Geometric Boundary of Exotic ℝ⁴ ── [Paper 08]

For the four-dimensional topological Poincaré conjecture (Freedman's theorem) and the exotic differentiable structures of four-dimensional Euclidean space (exotic ℝ⁴), we present a structural interpretation based on the n=3 uniqueness theorem and the Hopf fibration. The argument proceeds in three stages. Scope of this...

Yuuki Yamagishi · 0 citations
#large language models Open access Sep 2026

Enhancing Topic Modeling Through Adaptive Similarity Thresholding: The Case of Large-Scale Citizen Contributions

In this paper, we propose a topic modeling method aimed at identifying the most salient themes in a large-scale collection of citizen contributions. Our method explicitly distinguishes between different proposals expressed within the same theme by assigning them to separate clusters, rather than grouping all occurrence...

Sami Guembour, Catherine Dominguès, Sabine Ploux · 0 citations
#large language models Open access Sep 2026

Automating clinical information retrieval from Finnish electronic health records using large language models

Abstract Clinicians often need to search for patient-specific information within electronic health records (EHRs) containing years of heterogeneous longitudinal documentation, a task that can be time-consuming, cognitively demanding, and prone to oversight. We evaluated 14 locally deployable open-source large language...

Mikko Saukkoriipi, Nicole Hernández, Jaakko Sahlsten et al. · 0 citations
#large language models Book Open access Sep 2026

Language and Thought: The View from LLMs

Abstract Daniel Dennett speculated in Kinds of Minds (1996): “Perhaps the kind of mind you get when you add language to it is so different from the kind of mind you can have without language that calling them both minds is a mistake.” Recent work in AI can be seen as testing Dennett’s thesis by exploring the performanc...

Daniel Rothschild · 0 citations
#large language models Open access Sep 2026

The Continuity Anchoring Method: A Structured Methodology for Sustained Human-AI Interaction

SF0005: Continuity Anchoring Method (CAM) The Continuity Anchoring Method (CAM) defines a structured interaction protocol for stabilizing relational coherence across extended human-AI exchanges. It addresses the architectural constraint of statelessness in large language models by externalizing continuity functions to...

Thomas Gantz · 39 citations
#large language models Open access Sep 2026

From Assistance to Autonomy – A Researcher Study on the Potential of AI Support for Qualitative Data Analysis

The advent of AI technologies, such as Large Language Models, has introduced new possibilities for Qualitative Data Analysis (QDA), offering both opportunities and challenges. To help navigate the responsible integration of AI into QDA, we conducted semi-structured interviews with 15 Human-Computer Interaction (HCI) re...

Elisabeth Kirsten, Annalina Buckmann, Leona Lassak et al. · 2 citations
#large language models Review Aug 2026

From Values to Benchmarks: Evaluating Large Language Models for Governmental Use in Dutch

Large language models are increasingly being deployed in governmental settings, yet few existing evaluation frameworks jointly reflect the values of public administration and the linguistic requirements of non-English contexts. We present the"Grip on LLMs"framework, a systematic evaluation suite for Dutch governmental...

Laurens Samson, Iva Gornishka, Gossa Lô et al. · 0 citations

The Beginning of ChatGPT Ads

The first empirical study of advertising content being rolled out in the user-facing online interfaces of large language models (LLMs) finds that accounts begin receiving ads 14 days after account creation, and that lower-income accounts are more likely to receive ads.

Emma Lurie, Ro Encarnación, Sorelle A. Friedler et al. · 0 citations

From tech blogs

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Microsoft Research Blog Oct 12, 2026

Simulating student learning for better AI tutoring

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.

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