activity
20182023
most citedWhen Ensembling Smaller Models is More Efficient than Single Large Models

24 citations · 104 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2023★ 22 cited

VideoPoet: A Large Language Model for Zero-Shot Video Generation

Dan Kondratyuk, Lijun Yu, Xiuye Gu +28

We present VideoPoet, a language model capable of synthesizing high-quality video, with matching audio, from a large variety of conditioning signals. VideoPoet employs a decoder-on…

cs.CV2023★ 6 cited

Alternating Gradient Descent and Mixture-of-Experts for Integrated Multimodal Perception

Hassan Akbari, Dan Kondratyuk, Yin Cui +3

We present Integrated Multimodal Perception (IMP), a simple and scalable multimodal multi-task training and modeling approach. IMP integrates multimodal inputs including image, vid…

cs.CV2021★ 9 cited

Towards a Unified Foundation Model: Jointly Pre-Training Transformers on Unpaired Images and Text

Qing Li, Boqing Gong, Yin Cui +4

In this paper, we explore the possibility of building a unified foundation model that can be adapted to both vision-only and text-only tasks. Starting from BERT and ViT, we design…

cs.CV2020★ 21 cited

Wisdom of Committees: An Overlooked Approach To Faster and More Accurate Models

Xiaofang Wang, Dan Kondratyuk, Eric Christiansen +3

Committee-based models (ensembles or cascades) construct models by combining existing pre-trained ones. While ensembles and cascades are well-known techniques that were proposed be…

cs.LG2020★ 24 cited

When Ensembling Smaller Models is More Efficient than Single Large Models

Dan Kondratyuk, Mingxing Tan, Matthew Brown +1

Ensembling is a simple and popular technique for boosting evaluation performance by training multiple models (e.g., with different initializations) and aggregating their prediction…

cs.CL2019★ 21 cited

75 Languages, 1 Model: Parsing Universal Dependencies Universally

Dan Kondratyuk, Milan Straka

We present UDify, a multilingual multi-task model capable of accurately predicting universal part-of-speech, morphological features, lemmas, and dependency trees simultaneously for…

cs.CL2018

LemmaTag: Jointly Tagging and Lemmatizing for Morphologically-Rich Languages with BRNNs

Daniel Kondratyuk, Tomáš Gavenčiak, Milan Straka +1

We present LemmaTag, a featureless neural network architecture that jointly generates part-of-speech tags and lemmas for sentences by using bidirectional RNNs with character-level…

cs.DB2018★ 1 cited

Integrity Coded Databases: An Evaluation of Performance, Efficiency, and Practicality

Dan Kondratyuk, Jake Rodden, Elmer Duran

In recent years, cloud database storage has become an inexpensive and convenient option for businesses and individuals to store information. While its positive aspects make the clo…