activity
20212026
most citedOn the Opportunities and Risks of Foundation Models

2.3k citations · 2.4k across the 10 of their papers we have counts for

collaborators

10 papers

cs.AI2026

Discovering High-Quality Chess Puzzles with Offline Reinforcement Learning

Allen Nie, Anirudhan Badrinath, Nicholas Tomlin +5

Learning and skill mastery require extensive and deliberate practice. In many learning settings, producing high-quality pedagogical materials can require a high level of domain exp…

cs.CL2023★ 1 cited

SIGHT: A Large Annotated Dataset on Student Insights Gathered from Higher Education Transcripts

Rose E. Wang, Pawan Wirawarn, Noah Goodman +1

Lectures are a learning experience for both students and teachers. Students learn from teachers about the subject material, while teachers learn from students about how to refine t…

cs.CL2023★ 4 cited

Is ChatGPT a Good Teacher Coach? Measuring Zero-Shot Performance For Scoring and Providing Actionable Insights on Classroom Instruction

Rose E. Wang, Dorottya Demszky

Coaching, which involves classroom observation and expert feedback, is a widespread and fundamental part of teacher training. However, the majority of teachers do not have access t…

cs.CL2023★ 13 cited

Solving Math Word Problems by Combining Language Models With Symbolic Solvers

Joy He-Yueya, Gabriel Poesia, Rose E. Wang +1

Automatically generating high-quality step-by-step solutions to math word problems has many applications in education. Recently, combining large language models (LLMs) with externa…

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.LG2022★ 1 cited

Know Thy Student: Interactive Learning with Gaussian Processes

Rose E. Wang, Mike Wu, Noah Goodman

Learning often involves interaction between multiple agents. Human teacher-student settings best illustrate how interactions result in efficient knowledge passing where the teacher…

cs.CL2022★ 9 cited

Language modeling via stochastic processes

Rose E Wang, Esin Durmus, Noah Goodman +1

Modern language models can generate high-quality short texts. However, they often meander or are incoherent when generating longer texts. These issues arise from the next-token-onl…

cs.CL2021

Calibrate your listeners! Robust communication-based training for pragmatic speakers

Rose E. Wang, Julia White, Jesse Mu +1

To be good conversational partners, natural language processing (NLP) systems should be trained to produce contextually useful utterances. Prior work has investigated training NLP…

cs.LG2021★ 2.3k cited

On the Opportunities and Risks of Foundation Models

Rishi Bommasani, Drew A. Hudson, Ehsan Adeli +111

AI is undergoing a paradigm shift with the rise of models (e.g., BERT, DALL-E, GPT-3) that are trained on broad data at scale and are adaptable to a wide range of downstream tasks.…