Skip to content

Acknowledgments

Default: include all awards below. Ask the PI for a final pass; some papers should highlight only the directly-relevant funders.

Friends and colleagues

Acknowledge friends and colleagues who helped (typically below the authorship bar). Place these before the funding paragraph in the paper.

Active funding sources

When an award expires, move it to Past funding sources and drop it from the boilerplate.

  • Visko Platform (2026–2027): general; especially relevant for video generation
  • Pionex (2026–2028): general; especially news forecasting, agentic RL
  • Toyota Research Institute, R2I program (2026–2027): world models, egocentric videos, personal assistant, aging, etc.
  • NSF BCS Award 2545541 (2026–2029): human and machine intuitive physics, JEPA, etc.
  • Google TPU Award (2026–2027): on-device continual learning
  • NYU-KAIST Award A25-0081-002 (2024–2027): embodied video learning, object-centric learning
  • IITP grant RS-2024-00469482 (2024–2028): general fundamental AI; funded by the Ministry of Science and ICT (MSIT) of the Republic of Korea in connection with the Global AI Frontier Lab International Collaborative Research

Compute is supported by NYU High Performance Computing resources, services, and staff expertise: always include this line.

Past funding sources

Kept for reference. Don't include in the boilerplate.

(none yet)

Boilerplate paragraph

This research was supported by Visko Platform, Pionex, Toyota Research Institute R2I program, NSF BCS Award 2545541, a Google TPU Award, the NYU-KAIST Award A25-0081-002, and the Institute of Information & Communications Technology Planning Evaluation (IITP) under grant RS-2024-00469482, funded by the Ministry of Science and ICT (MSIT) of the Republic of Korea in connection with the Global AI Frontier Lab International Collaborative Research. The compute is supported by the NYU High Performance Computing resources, services, and staff expertise.

When to include

  • papers (camera-ready), tech reports, arXiv
  • Never: under-review submissions

Per-paper additions

Dataset licenses, collaborator gifts: in the paper's .tex, not here.