4 citations · 4 across the 6 of their papers we have counts for
7 papers
MLE-Smith: Scaling MLE Tasks with Automated Multi-Agent Pipeline
Rushi Qiang, Yuchen Zhuang, Anikait Singh +4
While Language Models (LMs) have made significant progress in automating machine learning engineering (MLE), the acquisition of high-quality MLE training data is significantly cons…
Reinforcement Learning for Machine Learning Engineering Agents
Sherry Yang, Joy He-Yueya, Percy Liang
Existing agents for solving tasks such as ML engineering rely on prompting powerful language models. As a result, these agents do not improve with more experience. In this paper, w…
WorldGym: World Model as An Environment for Policy Evaluation
Julian Quevedo, Ansh Kumar Sharma, Yixiang Sun +3
Evaluating robot control policies is difficult: real-world testing is costly, and handcrafted simulators require manual effort to improve in realism and generality. We propose a wo…
MLE-Dojo: Interactive Environments for Empowering LLM Agents in Machine Learning Engineering
Rushi Qiang, Yuchen Zhuang, Yinghao Li +8
We introduce MLE-Dojo, a Gym-style framework for systematically reinforcement learning, evaluating, and improving autonomous large language model (LLM) agents in iterative machine…
Improving Dynamic Object Interactions in Text-to-Video Generation with AI Feedback
Hiroki Furuta, Heiga Zen, Dale Schuurmans +4
Large text-to-video models hold immense potential for a wide range of downstream applications. However, they struggle to accurately depict dynamic object interactions, often result…
VideoAgent: Self-Improving Video Generation
Achint Soni, Sreyas Venkataraman, Abhranil Chandra +4
Video generation has been used to generate visual plans for controlling robotic systems. Given an image observation and a language instruction, previous work has generated video pl…
Learning Fast-Mixing Models for Structured Prediction
Jacob Steinhardt, Percy Liang
Markov Chain Monte Carlo (MCMC) algorithms are often used for approximate inference inside learning, but their slow mixing can be difficult to diagnose and the approximations can s…