2.3k citations · 6.5k across the 77 of their papers we have counts for
6 papers · 2 filters
Effective Approaches to Attention-based Neural Machine Translation
Minh-Thang Luong, Hieu Pham, Christopher D. Manning
An attentional mechanism has lately been used to improve neural machine translation (NMT) by selectively focusing on parts of the source sentence during translation. However, there…
A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts +1
Understanding entailment and contradiction is fundamental to understanding natural language, and inference about entailment and contradiction is a valuable testing ground for the d…
Robust Subgraph Generation Improves Abstract Meaning Representation Parsing
Keenon Werling, Gabor Angeli, Christopher Manning
The Abstract Meaning Representation (AMR) is a representation for open-domain rich semantics, with potential use in fields like event extraction and machine translation. Node gener…
Text to 3D Scene Generation with Rich Lexical Grounding
Angel Chang, Will Monroe, Manolis Savva +2
The ability to map descriptions of scenes to 3D geometric representations has many applications in areas such as art, education, and robotics. However, prior work on the text to 3D…
Tree-structured composition in neural networks without tree-structured architectures
Samuel R. Bowman, Christopher D. Manning, Christopher Potts
Tree-structured neural networks encode a particular tree geometry for a sentence in the network design. However, these models have at best only slightly outperformed simpler sequen…
Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks
Kai Sheng Tai, Richard Socher, Christopher D. Manning
Because of their superior ability to preserve sequence information over time, Long Short-Term Memory (LSTM) networks, a type of recurrent neural network with a more complex computa…