BASALITH · XYZ
RESEARCH INDEX

Cited Research

Nine outside papers underpin the Basalith architecture, and one entry is our own. Each citation in the white paper links to its full entry here.

10
ENTRIES
8
RESEARCH AREAS
1966-2026
PUBLICATION RANGE
1
PREREGISTERED
 
[1]
THEORETICAL FOUNDATION1966§01§13

The Tacit Dimension

Polanyi, M. · University of Chicago Press

Tacit knowledge exists only in practice. It cannot be fully articulated in words.

[2]
KNOWLEDGE TRANSFER2024§01§12§13

Procedures for transferring organizational knowledge during generational change: A systematic review

Igoa-Iraola, E., & Diez, F. · Heliyon, 10(4)

68% of organizations attempt tacit knowledge transfer, but effective methods remain elusive.

[3]
KNOWLEDGE TRANSFER2021§01§13

The High Cost of Poor Succession Planning

Fernandez-Araoz, C., Nagel, G., & Green, C. · Harvard Business Review, May-June 2021

Badly managed CEO and C suite transitions destroy close to $1 trillion a year in market value among S&P 1500 companies.

[4]
USER RESEARCH2025§01§13

AI Afterlife as Digital Legacy: Perceptions, Expectations, and Concerns

Lei, Y. et al. · Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems

Intentional participation distinguishes authentic digital legacy from reactive reconstruction.

[5]
COGNITIVE FINGERPRINTING2021§02§13

A cognitive fingerprint in human random number generation

Schulz, M-A., Baier, S., Timmermann, B., Bzdok, D., & Witt, K. · Scientific Reports, 11

Individual behavioral patterns in random number generation are measurably distinctive at 96.5% AUC, establishing that cognitive signatures differ between individuals.

[6]
LLM RESEARCH2025§13

Large Language Models for Psychological Assessment: A Comprehensive Overview

Brickman, J., Gupta, M., & Oltmanns, J.R. · Advances in Methods and Practices in Psychological Science

Fine tuned LLMs can predict personality traits from social media posts with meaningful accuracy.

[7]
PRIVACY RISK2025§11§13

Unintended Memorization of Sensitive Information in Fine-Tuned Language Models

Anonymous · arXiv:2601.17480

LLMs memorize training samples even when seen once, requiring quality screened training pipelines.

[8]
PLLM TAXONOMY2025§13§14

A Survey of Personalized Large Language Models: Progress and Future Directions

Au, S. et al. · arXiv:2502.11528

Per user PEFT provides a viable paradigm for personalized behavioral fine tuning at scale.

[9]
ORAL HISTORY2025§13

Large Language Models for Oral History Understanding with Text Classification and Sentiment Analysis

Anonymous · arXiv:2508.06729

LLMs effectively annotate 92,191 sentences from 1,002 oral history interviews.

[10]
PREREGISTERED2026§05§13

Template Contamination in Honesty Instructions

Ha, D. · Stage 1 Preregistration, Open Science Framework

Registered, not resolved. An instruction to be honest, made concrete, may produce more confident fabrication than no instruction at all.