Reproducibility artifact for the manuscript Evaluating LLM-Based Credit Rating Systems: A Pre-Registered Specification-Curve Analysis. A pre-registered specification-curve (multiverse) study of large-language-model credit-rating instability. From a frozen corpus of 8,640 elicitations (90-item firm-profile battery with...
Samir Chincholikar, Robin Chawla· Open MIND· 0 citations
The emergence of conspiracy theories in the wake of major events is a significant societal challenge. Here we test whether conversational dialogues with a large language model (LLM) can reduce belief in immediately unfolding conspiracies. In experiments conducted in the days following the July 2024 assassination attemp...
Thomas H. Costello, Nathaniel Rabb, Michael N. Stagnaro et al.· 0 citations
It is argued that the properties that make these models attractive - their generality, accessibility, and low deployment cost - undermine the conditions under which AI safety has historically been pursued, and safety assurance shifts from an intrinsic feature of building an AI tool to an optional add-on.
Large language models often generate confident but fabricated content, yet whether they maintain internal representations of their own epistemic states is unknown. To address this question, contrastive activation vectors were extracted for 15 epistemic states from five language models, using 100 matched present-neutral...
Jacob L. Steenwyk· Preprints.org· 0 citations
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Supplemental materials for a study benchmarking retrieval-augmented large language models for predicting green building project cost and duration. Forty-one configurations from Anthropic, Google and OpenAI, across their reasoning-effort settings, each predicted 20 held-out Hong Kong BEAM Plus projects three times (2,46...
Amos Darko, Emmanuel Boateng, Muhammad Abu Bakar Tariq et al.· Figshare· 0 citations
Whether analytic theology can supply a symbolic logical framework apt to encode moral safeguards inside LLM pipelines is investigated, which targets the engineering of moral computation: a formal language placed between metaphysical content and machine implementation.
Fernando Negrini· International Journal of Bio...· 0 citations
This dataset is an extension of the publication of the Database of Byzantine Book Epigrams (2023). The 2023 publication is a copy of the data used for the live application on dbbe.ugent.be. The present dataset aims to offer a simplified structure of the DBBE data, facilitating computational research and data analysis....
Kristoffel Demoen, Sofia Belioti, Gilbert Bentein et al.· Ghent University Academic Bi...· 0 citations
# Separating Secrets from Placeholders: A Hybrid CNN-CodeBERT Framework for Three-Class Credential Leakage Detection ## Overview This repository contains the code and dataset for our 3-class credential leakage detection framework, which distinguishes between: - **Class 0:** No Leak- **Class 1:** Genuine Leak- **Class 2...
Mst Maksuda Bilkis Baby, Khushika Shah, 梁乃跃 et al.· Zenodo (CERN European Organi...· 0 citations
The file attached is the replication package for the experiments presented in the paper “Generalizing Large Language Models’ Hyperparameters and Prompting for Code Generation: Removing the Blindspot”. This package contains the prompts, generated code for case study, and evaluation results.
Generative AI offers new opportunities for individualized and adaptive learning, e.g., through large language model (LLM)-based feedback systems. While LLMs can produce factually correct feedback for relatively straightforward conceptual tasks, delivering high-quality feedback for tasks that require advanced domain exp...
Holger Maus, Fabian Kieser, Stefan Petersen et al.· The Physics Educator· 0 citations
With the wide and cross-domain adoption of Large Language Models, it becomes crucial to assess the extent to which the statistical correlations in training data hide subtle and potentially troubling biases. Gender bias in LLMs has been widely investigated from the perspectives of work, hobbies, and emotions typically a...
Massimiliano Luca, Ciro Beneduce, Bruno Lepri et al.· ACM Transactions on Intellig...· 0 citations
Foundation models derive their value from broad general capability across domains, yet deployment usually rewards specialization - creating a fundamental question for general intelligence: when performance is pushed upward in one region of capability space, is competence elsewhere conserved, redistributed, or destroyed...
Sahir Maharaj· Zenodo (CERN European Organi...· 0 citations
