Denoising Bodies to Titles: Retrieving Similar Questions with Recurrent Convolutional Models

By Tao Lei, Hrishikesh Joshi, Regina Barzilay, Tommi S. Jaakkola, Kateryna Tymoshenko, Alessandro Moschitti, Lluís Màrquez i Villodre. 2015

14 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Regina Barzilay
2. Wengong Jin
3. Tommi S. Jaakkola
4. Tao Lei
5. Percy Liang
6. Yoshua Bengio
7. Mohit Bansal
8. Mirella Lapata

Citations in the corpus

• Deriving Neural Architectures from Sequence and Graph Kernels (2017, background): “This includes recurrent modules with the ability to carry persistent memories such as LSTM (Hochreiter & Schmid-huber, 1997) and GRU (Chung et al., 2014), as well as non-consecutive convolutional modules (RCNNs, Lei et al. (2015)), and others.”
• Rationalizing Neural Predictions (2016, methodology): “We use the “one-versus-all” hinge loss (i.e. positive versus other negatives) for the encoder, similar to (Lei et al., 2015b).”