activity
20212026
most citedOn the Opportunities and Risks of Foundation Models

2.3k citations · 3.1k across the 9 of their papers we have counts for

collaborators

9 papers

cs.RO2026

Traffic Scenario Orchestration from Language via Constraint Satisfaction

Frieda Rong, Chris Zhang, Kelvin Wong +1

Autonomous vehicles (AVs) require extensive testing in simulation, but test case generation for driving scenarios is laborious. The desired scenarios are often out-of-distribution…

cs.LG2024

Value Internalization: Learning and Generalizing from Social Reward

Frieda Rong, Max Kleiman-Weiner

Social rewards shape human behavior. During development, a caregiver guides a learner's behavior towards culturally aligned goals and values. How do these behaviors persist and gen…

cs.CL2024★ 2 cited

When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards

Norah Alzahrani, Hisham Abdullah Alyahya, Yazeed Alnumay +9

Large Language Model (LLM) leaderboards based on benchmark rankings are regularly used to guide practitioners in model selection. Often, the published leaderboard rankings are take…

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.CL2022★ 128 cited

Holistic Evaluation of Language Models

Percy Liang, Rishi Bommasani, Tony Lee +47

Language models (LMs) are becoming the foundation for almost all major language technologies, but their capabilities, limitations, and risks are not well understood. We present Hol…

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★ 565 cited

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao +448

Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabil…

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.…

cs.CV2021★ 4 cited

GeoSim: Realistic Video Simulation via Geometry-Aware Composition for Self-Driving

Yun Chen, Frieda Rong, Shivam Duggal +6

Scalable sensor simulation is an important yet challenging open problem for safety-critical domains such as self-driving. Current works in image simulation either fail to be photor…