Our latest work demonstrates how industry-scale Flywheel systems can iteratively drive model improvements even when the objectives are not easily tractable!
Lin Guan
@GuanSuns
Research Scientist at Meta GenAI | PhD@ASU, BS@UT Austin | RL and planning for conversational models and agents.
Joined February 2017
- Our latest work sheds light on what to "scale" when building generalizable agents: 👉 Prefer training envs with 📚 high state information richness (high perception load & info volume) + 🧠high planning complexity (long task horizon & branching factors) 👉 The *complexity
- 📢 Our #ICLR2023 paper on learning and leveraging relative behavioral attributes to tame the sample complexity of #RLHF (joint with @karthikv792 & @rao2z ) is now featured on @mtlaiethics ! 1/ 👉
