Dr. Percy Liang
VERIFIED TECHNICAL DOSSIERSources checked

Dr. Percy Liang

Associate Professor, Stanford University | Director, Center for Research on Foundation Models

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. Percy Liang. Every entry undergoes editorial source verification.

#1
RESEARCH Checked Sep 20, 2026

Stanford CRFM Alpaca: A Strong, Replicable Instruction-Following Model

The landmark research project that demonstrated high-quality instruction tuning of open foundation models using self-instruct data synthesis at a compute cost under $600, catalyzing the open-source LLM revolution.

Model & Execution Context:Fine-tuned on LLaMA 7B using standard PyTorch FSDP on 8 80GB A100 GPUs.
Scope & Limitations

Trained on 52k synthetic instructions; subject to hallucination and inherits safety limitations of the underlying foundation model.

#2
RESEARCH Checked Sep 20, 2026

Holistic Evaluation of Language Models (HELM)

A multi-dimensional benchmark evaluating foundational LLMs across 42 real-world scenarios and 7 evaluation metrics to eliminate selective benchmark reporting.

Model & Execution Context:Empirical evaluation suite covering all major commercial and open foundation models.
Scope & Limitations

Continuous maintenance required as frontier model providers iterate closed alignment weights.