46 citations · 120 across the 7 of their papers we have counts for
7 papers
Neural Logic Machines
Honghua Dong, Jiayuan Mao, Tian Lin +3
We propose the Neural Logic Machine (NLM), a neural-symbolic architecture for both inductive learning and logic reasoning. NLMs exploit the power of both neural networks---as funct…
Doubly Sparse: Sparse Mixture of Sparse Experts for Efficient Softmax Inference
Shun Liao, Ting Chen, Tian Lin +2
Computations for the softmax function are significantly expensive when the number of output classes is large. In this paper, we present a novel softmax inference speedup method, Do…
Neural Phrase-to-Phrase Machine Translation
Jiangtao Feng, Lingpeng Kong, Po-Sen Huang +5
In this paper, we propose Neural Phrase-to-Phrase Machine Translation (NPMT). Our model uses a phrase attention mechanism to discover relevant input (source) segments that are…
Subgoal Discovery for Hierarchical Dialogue Policy Learning
Da Tang, Xiujun Li, Jianfeng Gao +3
Developing agents to engage in complex goal-oriented dialogues is challenging partly because the main learning signals are very sparse in long conversations. In this paper, we prop…
Towards Neural Phrase-based Machine Translation
Po-Sen Huang, Chong Wang, Sitao Huang +2
In this paper, we present Neural Phrase-based Machine Translation (NPMT). Our method explicitly models the phrase structures in output sequences using Sleep-WAke Networks (SWAN), a…
Scaffolding Networks: Incremental Learning and Teaching Through Questioning
Asli Celikyilmaz, Li Deng, Lihong Li +1
We introduce a new paradigm of learning for reasoning, understanding, and prediction, as well as the scaffolding network to implement this paradigm. The scaffolding network embodie…