A reinforcement learning model is ethically fine-tuned using aggregated feedback from LLMs embodying five moral principles via Belief Jensen-Shannon Divergence and Dempster-Shafer Theory.
AI and Science: What 1,600 Researchers Think
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
verdicts
UNVERDICTED 3roles
background 1polarities
background 1representative citing papers
AI tools deliver useful overviews for research exploration but prove unreliable for precise information extraction and systematic reviews due to low explainability, reproducibility, and transparency.
The paper reduces a broad set of prompt engineering techniques to six core approaches and applies them to life sciences use cases while addressing common LLM pitfalls.
citing papers explorer
-
Addressing Moral Uncertainty using Large Language Models for Ethical Decision-Making
A reinforcement learning model is ethically fine-tuned using aggregated feedback from LLMs embodying five moral principles via Belief Jensen-Shannon Divergence and Dempster-Shafer Theory.
-
Useful for Exploration, Risky for Precision: Evaluating AI Tools in Academic Research
AI tools deliver useful overviews for research exploration but prove unreliable for precise information extraction and systematic reviews due to low explainability, reproducibility, and transparency.
-
The Prompt Engineering Report Distilled: Quick Start Guide for Life Sciences
The paper reduces a broad set of prompt engineering techniques to six core approaches and applies them to life sciences use cases while addressing common LLM pitfalls.