large language models

Educators’ Discussion with a Generative Artificial Intelligence Trainer

It is learned that genAI was created to be people pleasing which can override its ability to find truth, and how it supports error analysis in Large Language Models, and how the public should view these tools.

Harmonized recommendation with large language model guidance and reinforcement learning

Reading and Steering Representations of Materials-Science Mechanisms in an Open-Weight Language Model

Large language models can answer scientific questions, yet a correct output does not reveal whether the model represents or uses the governing physics. Here, using three open-weight Gemma 4 models (google/gemma-4-E4B-it, google/gemma-4-12B-it, google/gemma-4-31B-it) we identify three experimentally separable signatures...

Can LLMs Extract Architectural Design Decisions from Source Code Commits? - A Preliminary Exploratory Study

A preliminary study using four LLMs with zeroshot and fewshot prompting on 30 developer-written ADDs from open-source projects finds that the generated ADDs are often too long, implementation-focused, and miss the rationale behind the decision.

A dual-layer bilevel optimization model to complete algorithm evolution in agile satellite task scheduling problem using Large Language Models

Prompt engineering for medical named entity recognition: A few-shot approach with large language models

Do large language models displace or complement investment advisors? Evidence from Chinese wealth management firms

Time‑Accumulated Vacuum Cosmology v3.6 Unified Proper‑Time Tracking Model for Evolving Dark Energy ρ₍vac₎(x) = ρ₀ [1 + k Φ(x)/c²]

Time‑Accumulated Vacuum Cosmology v3.6 FEU: Proper‑Time Modulated Vacuum with Early‑Time Suppression and Density‑Dependent Screening FEU v3.6 is the latest corrected and stabilized version of the Time‑Accumulated Vacuum Cosmology framework. The model extends ΛCDM by introducing a small, smooth modulation of vacuum ener...

Data and Supplementary Materials for "Quantifying Materiality Misalignment Risk in ESG Reporting Using Large Language Models"

Canonical Noncommutative Defects Beyond Parikh Projection: Magnus Towers and an Unbounded Static-Dynamic Boundary Gap

We develop an order-sensitive defect formalism for substitution prefixes using the classical Magnus expansion of words. A substitution morphism induces a filtered endomorphism of the completed noncommutative tensor algebra, and an anchored substitution cut produces a multiplicative residual whose finite truncations for...

Consciousness Is a Phase Transition: A Two-Channel Thermodynamic Criterion and an Exclusion Principle

We propose that consciousness is a phase transition of a non-equilibrium dissipative structure, characterised by two independently controlled channels that must both be driven past threshold. The central result is an exclusion criterion: a macroscopic dissipative structure cannot be conscious unless it satisfies three...

A Large Language Model Agent Framework for Token-Efficient Tabular Data Error Detection

Reproducibility materials for the PeerJ manuscript “A Large Language Model Agent Framework for Token-Efficient Tabular Data Error Detection”. This release contains the LAED source code, five aligned dirty/clean benchmark CSV pairs, the dependency specification, and documentation required to reproduce the supplied exper...