Vilnis, Luke

Generating Sentences from a Continuous Space

Bowman, S. R., Vilnis, L., Vinyals, O., Dai, A., Jozefowicz, R., & Bengio, S. (2016) · Proceedings of The 20th SIGNLL Conference on Computational Natural Language Learning

Topic ModelingSpeech Recognition and Synthesis

Cited by 2,061

Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

Gemini Team, Georgiev, P., Lei, V. I., Burnell, R., Bai, L., Gulati, A., Tanzer, G., Vincent, D., Pan, Z., Wang, S., et al. (2024) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 306

Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures

Vilnis, L., Li, X., Murty, S., & McCallum, A. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Advanced Graph Neural NetworksTopic Modeling

Cited by 111

Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Comanici, G., Bieber, E., Schaekermann, M., Pasupat, I., Sachdeva, N., Dhillon, I., Blistein, M., Ram, O., Zhang, D., Rosen, E., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 69

Improving Local Identifiability in Probabilistic Box Embeddings

Dasgupta, S. S., Boratko, M., Zhang, D., Vilnis, L., Li, X. L., & McCallum, A. (2020) · arXiv

Bayesian Modeling and Causal InferenceMachine Learning and Data Classification

Cited by 33