Dr. Lilian Weng
VERIFIED TECHNICAL DOSSIERSources checked

Dr. Lilian Weng

AI Safety & Systems Researcher | Former VP of Research & Head of Safety Systems at OpenAI

2 Verified ArtifactsSource Checked & Attributed

Verified Proof of Work Artifacts

2 items cataloged

Each artifact below represents an authenticated research publication, production code repository, or technical architectural framework directly authored or co-created by Dr. Lilian Weng. Every entry undergoes editorial source verification.

#1
EXPLANATION Checked Sep 20, 2026

Prompt Engineering and In-Context Learning Technical Reference

A comprehensive, deeply cited technical survey on prompt engineering and in-context learning mechanics, reviewing chain-of-thought, self-consistency, directional stimulus prompting, and tree-of-thought search patterns across modern foundation models.

Model & Execution Context:Covers prompting taxonomies for GPT-3.5, GPT-4, PaLM, and LLaMA foundation models.
Scope & Limitations

Technical survey and architectural analysis; empirical performance varies significantly between parameter scales and post-training regimes.

#2
EXPLANATION Checked Sep 20, 2026

LLM-Powered Autonomous Agents: Comprehensive System Design & Architecture Analysis

Landmark reference architecture decomposing autonomous agents into planning (subgoal decomposition, reflection), memory (short-term in-context, long-term vector search), and tool execution loops.

Model & Execution Context:Large language models, vector memory systems, ReAct prompting, and agent loops.
Scope & Limitations

Identifies fundamental limits of finite context windows, reliability bottlenecks in long-term planning, and unreliability of open-ended natural language tool interfaces.