Compositional Attention Networks for Machine Reasoning. - Drew A. Hudson; Christopher D. Manning (ICLR (Poster), 2018)

GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering. - Drew A. Hudson; Christopher D. Manning (CVPR, 2019)

Learning by Abstraction: The Neural State Machine. - Drew A. Hudson; Christopher D. Manning (NeurIPS, 2019)

GQA: a new dataset for compositional question answering over real-world images. - Drew A. Hudson; Christopher D. Manning (CoRR, 2019)

SLM: Learning a Discourse Language Representation with Sentence Unshuffling. - Haejun Lee; Drew A. Hudson; Kangwook Lee 004; Christopher D. Manning (EMNLP (1), 2020)

Generative Adversarial Transformers. - Drew A. Hudson; Larry Zitnick (ICML, 2021)

On the Opportunities and Risks of Foundation Models. - Rishi Bommasani; Drew A. Hudson; Ehsan Adeli 001; Russ B. Altman; Simran Arora; Sydney von Arx; Michael S. Bernstein; Jeannette Bohg; Antoine Bosselut; Emma Brunskill; Erik Brynjolfsson; Shyamal Buch; et al. (CoRR, 2021)

Compositional Transformers for Scene Generation. - Drew A. Hudson; C. Lawrence Zitnick (CoRR, 2021)

Holistic Evaluation of Language Models. - Percy Liang; Rishi Bommasani; Tony Lee; Dimitris Tsipras; Dilara Soylu; Michihiro Yasunaga; Yian Zhang; Deepak Narayanan; Yuhuai Wu; Ananya Kumar; Benjamin Newman; Binhang Yuan; et al. (Trans. Mach. Learn. Res., 2023)

SODA: Bottleneck Diffusion Models for Representation Learning. - Drew A. Hudson; Daniel Zoran; Mateusz Malinowski; Andrew K. Lampinen; Andrew Jaegle; James L. McClelland; Loic Matthey; Felix Hill; Alexander Lerchner (CVPR, 2024)

Moving Off-the-Grid: Scene-Grounded Video Representations. - Sjoerd van Steenkiste; Daniel Zoran; Yi Yang 007; Yulia Rubanova; Rishabh Kabra; Carl Doersch; Dilara Gokay; Joseph Heyward; Etienne Pot; Klaus Greff; Drew A. Hudson; Thomas Keck; et al. (NeurIPS, 2024)

Neural Assets: 3D-Aware Multi-Object Scene Synthesis with Image Diffusion Models. - Ziyi Wu; Yulia Rubanova; Rishabh Kabra; Drew A. Hudson; Igor Gilitschenski; Yusuf Aytar; Sjoerd van Steenkiste; Kelsey R. Allen; Thomas Kipf (NeurIPS, 2024)

Scaling Instructable Agents Across Many Simulated Worlds. - SIMA Team; Maria Abi Raad; Arun Ahuja; Catarina Barros; Frederic Besse; Andrew Bolt; Adrian Bolton; Bethanie Brownfield; Gavin Buttimore; Max Cant; Sarah Chakera; Stephanie C. Y. Chan; et al. (CoRR, 2024)

Can foundation models actively gather information in interactive environments to test hypotheses? - Nan Rosemary Ke; Danny P. Sawyer; Hubert Soyer; Martin Engelcke; David P. Reichert; Drew A. Hudson; John Reid; Alexander Lerchner; Danilo Jimenez Rezende; Timothy P. Lillicrap; Michael Mozer; Jane X. Wang (CoRR, 2024)

Probabilistic Inverse Cameras: Image to 3D via Multiview Geometry. - Rishabh Kabra; Drew A. Hudson; Sjoerd van Steenkiste; João Carreira 001; Niloy J. Mitra (CoRR, 2024)

Scaling 4D Representations. - João Carreira 001; Dilara Gokay; Michael King; Chuhan Zhang; Ignacio Rocco; Aravindh Mahendran; Thomas Keck; Joseph Heyward; Skanda Koppula; Etienne Pot; Goker Erdogan; Yana Hasson; et al. (CoRR, 2024)