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Found 8 papers, 4 papers with code
Toward Deconfounding the Effect of Entity Demographics for Question Answering Accuracy
The goal of question answering (QA) is to answer _any_ question.
MetaDIP: Accelerating Deep Image Prior with Meta Learning
Deep image prior (DIP) is a recently proposed technique for solving imaging inverse problems by fitting the reconstructed images to the output of an untrained convolutional neural network.
Investigating Information Inconsistency in Multilingual Open-Domain Question Answering
Retrieval based open-domain QA systems use retrieved documents and answer-span selection over retrieved documents to find best-answer candidates.
MATE: Multi-view Attention for Table Transformer Efficiency
However, more than 20% of relational tables on the web have 20 or more rows (Cafarella et al., 2008), and these large tables present a challenge for current Transformer models, which are typically limited to 512 tokens.
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Question Answering
on HybridQA
Toward Deconfounding the Influence of Entity Demographics for Question Answering Accuracy
The goal of question answering (QA) is to answer any question.
GAN-Tree: An Incrementally Learned Hierarchical Generative Framework for Multi-Modal Data Distributions
Despite the remarkable success of generative adversarial networks, their performance seems less impressive for diverse training sets, requiring learning of discontinuous mapping functions.
BiHMP-GAN: Bidirectional 3D Human Motion Prediction GAN
The discriminator is trained also to regress this extrinsic factor r, which is used alongside with the intrinsic factor (encoded starting pose sequence) to generate a particular pose sequence.
Unsupervised Feature Learning of Human Actions as Trajectories in Pose Embedding Manifold
In this work we propose a novel temporal pose-sequence modeling framework, which can embed the dynamics of 3D human-skeleton joints to a continuous latent space in an efficient manner.
