Vilnis, Luke

7 publications

ICML 2023 Arithmetic Sampling: Parallel Diverse Decoding for Large Language Models Luke Vilnis, Yury Zemlyanskiy, Patrick Murray, Alexandre Tachard Passos, Sumit Sanghai

NeurIPS 2021 Capacity and Bias of Learned Geometric Embeddings for Directed Graphs Michael Boratko, Dongxu Zhang, Nicholas Monath, Luke Vilnis, Kenneth L Clarkson, Andrew McCallum

NeurIPS 2020 Improving Local Identifiability in Probabilistic Box Embeddings Shib Dasgupta, Michael Boratko, Dongxu Zhang, Luke Vilnis, Xiang Li, Andrew McCallum

ICLR 2019 Smoothing the Geometry of Probabilistic Box Embeddings Xiang Li, Luke Vilnis, Dongxu Zhang, Michael Boratko, Andrew McCallum

ICLR 2018 Go for a Walk and Arrive at the Answer: Reasoning over Paths in Knowledge Bases Using Reinforcement Learning Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Akshay Krishnamurthy, Alex Smola, Andrew McCallum

UAI 2015 Bethe Projections for Non-Local Inference Luke Vilnis, David Belanger, Daniel Sheldon, Andrew McCallum

ICLR 2015 Word Representations via Gaussian Embedding Luke Vilnis, Andrew McCallum