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Found 11 papers, 7 papers with code
HandyPriors: Physically Consistent Perception of Hand-Object Interactions with Differentiable Priors
We demonstrate that HandyPriors attains comparable or superior results in the pose estimation task, and that the differentiable physics module can predict contact information for pose refinement.
On the Equivalence of Graph Convolution and Mixup
We establish this equivalence mathematically by demonstrating that graph convolution networks (GCN) and simplified graph convolution (SGC) can be expressed as a form of Mixup.
Orbit: A Unified Simulation Framework for Interactive Robot Learning Environments
We present Orbit, a unified and modular framework for robot learning powered by NVIDIA Isaac Sim.
DeXtreme: Transfer of Agile In-hand Manipulation from Simulation to Reality
Our policies are trained to adapt to a wide range of conditions in simulation.
COFFEE: Counterfactual Fairness for Personalized Text Generation in Explainable Recommendation
However, the bias inherent in user written text, often used for PTG model training, can inadvertently associate different levels of linguistic quality with users' protected attributes.
A Heuristic Approach to Two Level Boolean Minimization Derived from Karnaugh Mapping
The following paper presents a heuristic method by which sum-of-product Boolean expressions can be simplified with a specific focus on the removal of redundant and selective prime implicants.
VIOLIN: A Large-Scale Dataset for Video-and-Language Inference
We introduce a new task, Video-and-Language Inference, for joint multimodal understanding of video and text.
Distilling Knowledge Learned in BERT for Text Generation
Experiments show that the proposed approach significantly outperforms strong Transformer baselines on multiple language generation tasks such as machine translation and text summarization.
Stack-Pointer Networks for Dependency Parsing
Combining pointer networks~\citep{vinyals2015pointer} with an internal stack, the proposed model first reads and encodes the whole sentence, then builds the dependency tree top-down (from root-to-leaf) in a depth-first fashion.
Ranked #14 on
Dependency Parsing
on Penn Treebank
Softmax Q-Distribution Estimation for Structured Prediction: A Theoretical Interpretation for RAML
Reward augmented maximum likelihood (RAML), a simple and effective learning framework to directly optimize towards the reward function in structured prediction tasks, has led to a number of impressive empirical successes.
Visualizing Large-scale and High-dimensional Data
We propose the LargeVis, a technique that first constructs an accurately approximated K-nearest neighbor graph from the data and then layouts the graph in the low-dimensional space.
