Search Results for author: Alex Marin

Found 10 papers, 1 papers with code

Improving Zero-Shot Multilingual Text Generation via Iterative Distillation

no code implementations COLING 2022 Ernie Chang, Alex Marin, Vera Demberg

The demand for multilingual dialogue systems often requires a costly labeling process, where human translators derive utterances in low resource languages from resource rich language annotation.

Knowledge Distillation Text Generation

Programmable Annotation with Diversed Heuristics and Data Denoising

no code implementations COLING 2022 Ernie Chang, Alex Marin, Vera Demberg

To this end, we propose a novel data programming framework that can jointly construct labeled data for language generation and understanding tasks – by allowing the annotators to modify an automatically-inferred alignment rule set between sequence labels and text, instead of writing rules from scratch.

Denoising Text Generation

Bridging the Skills Gap: Evaluating an AI-Assisted Provider Platform to Support Care Providers with Empathetic Delivery of Protocolized Therapy

no code implementations8 Jan 2024 William R. Kearns, Jessica Bertram, Myra Divina, Lauren Kemp, Yinzhou Wang, Alex Marin, Trevor Cohen, Weichao Yuwen

We studied providers with and without expertise in mental health treatment delivering a therapy session using the platform with (intervention) and without (control) AI-assistance features.

Extracting and Inferring Personal Attributes from Dialogue

1 code implementation NLP4ConvAI (ACL) 2022 Zhilin Wang, Xuhui Zhou, Rik Koncel-Kedziorski, Alex Marin, Fei Xia

Personal attributes represent structured information about a person, such as their hobbies, pets, family, likes and dislikes.

Attribute Language Modelling

Jointly Improving Language Understanding and Generation with Quality-Weighted Weak Supervision of Automatic Labeling

no code implementations EACL 2021 Ernie Chang, Vera Demberg, Alex Marin

Neural natural language generation (NLG) and understanding (NLU) models are data-hungry and require massive amounts of annotated data to be competitive.

Text Generation

DART: A Lightweight Quality-Suggestive Data-to-Text Annotation Tool

no code implementations COLING 2020 Ernie Chang, Jeriah Caplinger, Alex Marin, Xiaoyu Shen, Vera Demberg

We present a lightweight annotation tool, the Data AnnotatoR Tool (DART), for the general task of labeling structured data with textual descriptions.

Active Learning text annotation

Bag of Experts Architectures for Model Reuse in Conversational Language Understanding

no code implementations NAACL 2018 Rahul Jha, Alex Marin, Suvamsh Shivaprasad, Imed Zitouni

Slot tagging, the task of detecting entities in input user utterances, is a key component of natural language understanding systems for personal digital assistants.

Domain Adaptation Natural Language Understanding

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