The field of humanoid robotics is rapidly advancing with a focus on improving locomotion and manipulation capabilities. Recent developments have centered around creating more stable and adaptable controllers for diverse humanoid embodiments. This has involved the use of hierarchical control architectures, cross-humanoid locomotion pretraining, and sim-to-real policy transfer. Additionally, there has been a push towards enabling humanoid robots to interact with and manipulate various objects in their environment, with advancements in material generalization and physics-based character control. Notable papers in this area include: H-Zero, which introduces a cross-humanoid locomotion pretraining pipeline enabling zero-shot and few-shot transfer to novel humanoid robots. Modality-Augmented Fine-Tuning of Foundation Robot Policies, which demonstrates the effectiveness of modality augmentation in adapting foundation robot policies to diverse humanoid embodiments. Learning Sim-to-Real Humanoid Locomotion in 15 Minutes, which achieves rapid training of humanoid locomotion policies in just 15 minutes with a single RTX 4090 GPU.