Summary of Dataenvgym: Data Generation Agents in Teacher Environments with Student Feedback, by Zaid Khan et al.
DataEnvGym: Data Generation Agents in Teacher Environments with Student Feedback
by Zaid Khan, Elias Stengel-Eskin, Jaemin Cho, Mohit Bansal
First submitted to arxiv on: 8 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces DataEnvGym, a testbed for autonomous data generation agents, also known as teachers, which can create training data to improve student models. This medium-difficulty summary assumes some technical background in machine learning, particularly in the subfield of language models and their applications. The authors frame data generation as a sequential decision-making task involving an agent comprising a policy and engine, inside an environment that provides student feedback. They highlight the importance of automating the labor-intensive process of creating training data and introduce DataEnvGym to support rapid testing for agents and their modules across 4 domains (math, code, VQA, and tool-use). The paper demonstrates example agents improving students across tasks and settings, with implications for future work in improving data generation agents, engines, and feedback mechanisms. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper is about creating a way to make machines learn faster and better. Right now, humans have to think of ways to help machines improve, which takes a lot of time and effort. The authors want to automate this process by making “teachers” that can create the right data for machines to learn from. They created a special environment called DataEnvGym where these teachers can work and get feedback on how well they’re doing. |
Keywords
* Artificial intelligence * Machine learning
