Please join us for the NLP Seminar this Monday (Oct 17) at 3:30pm in 202 South Hall.
Speaker: Jacob Andreas (Berkeley)
Title: Reasoning about pragmatics with neural listeners and speakers
We present a model for contrastively describing scenes, in which context-specific behavior results from a combination of inference-driven pragmatics and learned semantics. Like previous learned approaches to language generation, our model uses a simple feature-driven architecture (here a pair of neural “listener” and “speaker” models) to ground language in the world. Like inference-driven approaches to pragmatics, our model actively reasons about listener behavior when selecting utterances. For training, our approach requires only ordinary captions, annotated without demonstration of the pragmatic behavior the model ultimately exhibits. In human evaluations on a referring expression game, our approach succeeds 81% of the time, compared to 69% using existing techniques.
- Golland, Liang, and Klein. “A game-theoretic approach to generating spatial descriptions.” EMNLP, 2010.
- Mao, Junhua, et al. “Generation and comprehension of unambiguous object descriptions.” arxiv.org/pdf/1511.02283v3.pdf