57 citations · 109 across the 21 of their papers we have counts for
7 papers · 1 filter
Dialog2API: Task-Oriented Dialogue with API Description and Example Programs
Raphael Shu, Elman Mansimov, Tamer Alkhouli +6
Functionality and dialogue experience are two important factors of task-oriented dialogue systems. Conventional approaches with closed schema (e.g., conversational semantic parsing…
Injecting Domain Knowledge in Language Models for Task-Oriented Dialogue Systems
Denis Emelin, Daniele Bonadiman, Sawsan Alqahtani +2
Pre-trained language models (PLM) have advanced the state-of-the-art across NLP applications, but lack domain-specific knowledge that does not naturally occur in pre-training data.…
Unveiling Transformers with LEGO: a synthetic reasoning task
Yi Zhang, Arturs Backurs, Sébastien Bubeck +3
We propose a synthetic reasoning task, LEGO (Learning Equality and Group Operations), that encapsulates the problem of following a chain of reasoning, and we study how the Transfor…
Label Semantic Aware Pre-training for Few-shot Text Classification
Aaron Mueller, Jason Krone, Salvatore Romeo +4
In text classification tasks, useful information is encoded in the label names. Label semantic aware systems have leveraged this information for improved text classification perfor…
Clinical Prompt Learning with Frozen Language Models
Niall Taylor, Yi Zhang, Dan Joyce +2
Prompt learning is a new paradigm in the Natural Language Processing (NLP) field which has shown impressive performance on a number of natural language tasks with common benchmarki…
Dialogue Meaning Representation for Task-Oriented Dialogue Systems
Xiangkun Hu, Junqi Dai, Hang Yan +4
Dialogue meaning representation formulates natural language utterance semantics in their conversational context in an explicit and machine-readable form. Previous work typically fo…
Measuring and Reducing Model Update Regression in Structured Prediction for NLP
Deng Cai, Elman Mansimov, Yi-An Lai +3
Recent advance in deep learning has led to the rapid adoption of machine learning-based NLP models in a wide range of applications. Despite the continuous gain in accuracy, backwar…