Philipp Krähenbühl

Domain Adaptation Through Task Distillation

2020 · arXiv (Cornell University)

Deep networks devour millions of precisely annotated images to build their complex and powerful representations. Unfortunately, tasks like autonomous driving have virtually no real-world training data. Repeatedly crashing a car into a tree is simply …

Reinforcement Learning for Long-Horizon Interactive LLM Agents

2025 · arXiv (Cornell University)

Interactive digital agents (IDAs) leverage APIs of stateful digital environments to perform tasks in response to user requests. While IDAs powered by instruction-tuned large language models (LLMs) can react to feedback from interface invocations in …