Software


No Metrics Are Perfect: Adversarial Reward Learning for Visual Storytelling

We propose an Adversarial REward Learning (AREL) framework to learn an implicit reward function from human demonstrations, and then optimize policy search with the learned reward function (ACL 2018).
[Code]   [Paper]  

KBGAN: Adversarial Learning for Knowledge Graph Embeddings

We introduce KBGAN, an adversarial learning framework to improve the performances of a wide range of existing knowledge graph embedding models (NAACL-HLT 2018).
[Code]   [Paper]  

DeepPath: Reinforcement Learning for Knowledge Graph Reasoning

We describe a novel reinforcement learning framework for learning multi-hop relational paths: we use a policy-based agent with continuous states based on knowledge graph embeddings, which reasons in a KG vector space by sampling the most promising relation to extend its path. (EMNLP 2017).
[Code]   [Paper]  

Deep Residual Learning for Weakly-Supervised Relation Extraction

We design a novel convolutional neural network (CNN) with residual learning, and investigate its impacts on the task of distantly supervised noisy relation extraction. (EMNLP 2017).
[Code]   [Paper]