Search Results for author:
Found 14 papers, 3 papers with code
Improving Text-to-Text Pre-trained Models for the Graph-to-Text Task
Converting a knowledge graph or sub-graph to natural text is useful when answering questions based on a knowledge base.
Getting to Production with Few-shot Natural Language Generation Models
In this paper, we study the utilization of pre-trained language models to enable few-shotNatural Language Generation (NLG) in task-oriented dialog systems.
EASE: Extractive-Abstractive Summarization End-to-End using the Information Bottleneck Principle
To achieve the best of both worlds, we propose EASE, an extractive-abstractive framework that generates concise abstractive summaries that can be traced back to an extractive summary.
Small But Funny: A Feedback-Driven Approach to Humor Distillation
The emergence of Large Language Models (LLMs) has brought to light promising language generation capabilities, particularly in performing tasks like complex reasoning and creative writing.
Improving Faithfulness of Abstractive Summarization by Controlling Confounding Effect of Irrelevant Sentences
Lack of factual correctness is an issue that still plagues state-of-the-art summarization systems despite their impressive progress on generating seemingly fluent summaries.
A Study on the Efficiency and Generalization of Light Hybrid Retrievers
Driven by this question, we leverage an indexing-efficient dense retriever (i. e. DrBoost) and introduce a LITE retriever that further reduces the memory of DrBoost.
EASE: Extractive-Abstractive Summarization with Explanations
Current abstractive summarization systems outperform their extractive counterparts, but their widespread adoption is inhibited by the inherent lack of interpretability.
El Volumen Louder Por Favor: Code-switching in Task-oriented Semantic Parsing
Being able to parse code-switched (CS) utterances, such as Spanish+English or Hindi+English, is essential to democratize task-oriented semantic parsing systems for certain locales.
Sound Natural: Content Rephrasing in Dialog Systems
We introduce a new task of rephrasing for a more natural virtual assistant.
Likelihood Ratios and Generative Classifiers for Unsupervised Out-of-Domain Detection In Task Oriented Dialog
We are hitherto the first to investigate the use of generative classifiers for OOD detection at test-time.
Improving Robustness of Task Oriented Dialog Systems
However, evaluating a model's robustness to these changes is harder for language since words are discrete and an automated change (e. g. adding `noise') to a query sometimes changes the meaning and thus labels of a query.
Improving Semantic Parsing for Task Oriented Dialog
Semantic parsing using hierarchical representations has recently been proposed for task oriented dialog with promising results [Gupta et al 2018].
CERES: Distantly Supervised Relation Extraction from the Semi-Structured Web
In this paper we present a new method for automatic extraction from semi-structured websites based on distant supervision.
soc2seq: Social Embedding meets Conversation Model
While liking or upvoting a post on a mobile app is easy to do, replying with a written note is much more difficult, due to both the cognitive load of coming up with a meaningful response as well as the mechanics of entering the text.
