Search Results for author: Kuang-Huei Lee

Found 7 papers, 4 papers with code

Learning Task Sampling Policy for Multitask Learning

no code implementations Findings (EMNLP) 2021 Dhanasekar Sundararaman, Henry Tsai, Kuang-Huei Lee, Iulia Turc, Lawrence Carin

It has been shown that training multi-task models with auxiliary tasks can improve the target task quality through cross-task transfer.


Do As I Can, Not As I Say: Grounding Language in Robotic Affordances

no code implementations4 Apr 2022 Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Keerthana Gopalakrishnan, Karol Hausman, Alex Herzog, Daniel Ho, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Eric Jang, Rosario Jauregui Ruano, Kyle Jeffrey, Sally Jesmonth, Nikhil J Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Kuang-Huei Lee, Sergey Levine, Yao Lu, Linda Luu, Carolina Parada, Peter Pastor, Jornell Quiambao, Kanishka Rao, Jarek Rettinghouse, Diego Reyes, Pierre Sermanet, Nicolas Sievers, Clayton Tan, Alexander Toshev, Vincent Vanhoucke, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Mengyuan Yan

We show how low-level skills can be combined with large language models so that the language model provides high-level knowledge about the procedures for performing complex and temporally-extended instructions, while value functions associated with these skills provide the grounding necessary to connect this knowledge to a particular physical environment.

Decision Making Language Modelling

Compressive Visual Representations

1 code implementation NeurIPS 2021 Kuang-Huei Lee, Anurag Arnab, Sergio Guadarrama, John Canny, Ian Fischer

We verify this by developing SimCLR and BYOL formulations compatible with the Conditional Entropy Bottleneck (CEB) objective, allowing us to both measure and control the amount of compression in the learned representation, and observe their impact on downstream tasks.

Contrastive Learning Self-Supervised Image Classification

Learning Visual Relation Priors for Image-Text Matching and Image Captioning with Neural Scene Graph Generators

no code implementations22 Sep 2019 Kuang-Huei Lee, Hamid Palangi, Xi Chen, Houdong Hu, Jianfeng Gao

In this work, we tackle two fundamental language-and-vision tasks: image-text matching and image captioning, and demonstrate that neural scene graph generators can learn effective visual relation features to facilitate grounding language to visual relations and subsequently improve the two end applications.

Image Captioning Text Matching

Stacked Cross Attention for Image-Text Matching

3 code implementations ECCV 2018 Kuang-Huei Lee, Xi Chen, Gang Hua, Houdong Hu, Xiaodong He

Prior work either simply aggregates the similarity of all possible pairs of regions and words without attending differentially to more and less important words or regions, or uses a multi-step attentional process to capture limited number of semantic alignments which is less interpretable.

Cross-Modal Retrieval Image Retrieval +2

CleanNet: Transfer Learning for Scalable Image Classifier Training with Label Noise

1 code implementation CVPR 2018 Kuang-Huei Lee, Xiaodong He, Lei Zhang, Linjun Yang

We demonstrate the effectiveness of the proposed algorithm on both of the label noise detection task and the image classification on noisy data task on several large-scale datasets.

 Ranked #1 on Image Classification on Food-101N (using extra training data)

Classification General Classification +2

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