Month: September 2015

Speaker: Jacob Andreas (UC Berkeley)

Title: Alignment-based compositional semantics for instruction following (EMNLP 2015)

Abstract:

This paper describes an alignment-based model for interpreting natural language instructions in context. We approach instruction following as a search over plans, scoring sequences of actions conditioned on structured observations of text and the environment. By explicitly modeling both the low-level compositional structure of individual actions and the high-level structure of full plans, we are able to learn both grounded representations of sentence meaning and pragmatic constraints on interpretation. To demonstrate the model’s flexibility, we apply it to a diverse set of benchmark tasks. On every task, we outperform strong task-specific baselines, and achieve several new state-of-the-art results.

Slides: (pdf)  (keynote)

Speaker: Long Duong (U Melbourne, visiting ICSI)

Title: A Neural Network Model for Low-Resource Universal Dependency Parsing (EMNLP 2015)

Abstract:

Accurate dependency parsing requires large treebanks, which are only available for a few languages. We propose a method that takes advantage of shared structure across languages to build a mature parser using less training data. We propose a model for learning a shared “universal” parser that operates over an interlingual continuous representation of language, along with language-specific mapping components. Compared with supervised learning, our methods give a consistent 8-10% improvement across several treebanks in low-resource simulations.

Welcome to a new semester and a new seminar!  We’ll do quick introductions this week.