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Found 5 papers, 2 papers with code
Language-Guided World Models: A Model-Based Approach to AI Control
Installing probabilistic world models into artificial agents opens an efficient channel for humans to communicate with and control these agents.
Appearance Codes using Joint Embedding Learning of Multiple Modalities
The use of appearance codes in recent work on generative modeling has enabled novel view renders with variable appearance and illumination, such as day-time and night-time renders of a scene.
Building Scalable Video Understanding Benchmarks through Sports
Our human studies indicate that ASAP can align videos and annotations with high fidelity, precision, and speed.
$FM^2$: Field-matrixed Factorization Machines for Recommender Systems
The FmFM model's performance is also comparable to DNN models which require much more FLOPs in runtime.
UMD at SemEval-2018 Task 10: Can Word Embeddings Capture Discriminative Attributes?
We describe the University of Maryland{'}s submission to SemEval-018 Task 10, {``}Capturing Discriminative Attributes{''}: given word triples (w1, w2, d), the goal is to determine whether d is a discriminating attribute belonging to w1 but not w2.
