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Mina Lee

Stanford University

10 papers hereh-index 97.9k citations11 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author4
  • middle author5

Across the 9 of 10 papers where every author was matched, so the position is known.

fields
  • cs.CL6
  • cs.LG2
  • cs.HC1
  • cs.RO1
affiliations
  • Stanford University
Homepage
same name
  • Mina Lee — 13 papers, h 8

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20192023
most citedOn the Opportunities and Risks of Foundation Models

2.3k citations · 2.7k across the 10 of their papers we have counts for

collaborators
Showing 2022Show all

4 papers · 1 filter

cs.CL2022★ 57 cited

Evaluating Human-Language Model Interaction

Mina Lee, Megha Srivastava, Amelia Hardy +15

Many real-world applications of language models (LMs), such as writing assistance and code autocomplete, involve human-LM interaction. However, most benchmarks are non-interactive…

cs.RO2022★ 5 cited

Leveraging Large (Visual) Language Models for Robot 3D Scene Understanding

William Chen, Siyi Hu, Rajat Talak +1

Abstract semantic 3D scene understanding is a problem of critical importance in robotics. As robots still lack the common-sense knowledge about household objects and locations of a…

cs.CL2022

TempLM: Distilling Language Models into Template-Based Generators

Tianyi Zhang, Mina Lee, Lisa Li +2

While pretrained language models (PLMs) have greatly improved text generation, they have also been known to produce unfaithful or inappropriate content. In contrast, classic templa…

cs.HC2022★ 337 cited

CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities

Mina Lee, Percy Liang, Qian Yang

Large language models (LMs) offer unprecedented language generation capabilities and exciting opportunities for interaction design. However, their highly context-dependent capabili…

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