111 citations · 295 across the 63 of their papers we have counts for
52 papers · 1 filter
TRUST: An LLM-Based Dialogue System for Trauma Understanding and Structured Assessments
Sichang Tu, Abigail Powers, Stephen Doogan +1
Objectives: While Large Language Models (LLMs) have been widely used to assist clinicians and support patients, no existing work has explored dialogue systems for standard diagnost…
Automating PTSD Diagnostics in Clinical Interviews: Leveraging Large Language Models for Trauma Assessments
Sichang Tu, Abigail Powers, Natalie Merrill +4
The shortage of clinical workforce presents significant challenges in mental healthcare, limiting access to formal diagnostics and services. We aim to tackle this shortage by integ…
What is Your Favorite Gender, MLM? Gender Bias Evaluation in Multilingual Masked Language Models
Jeongrok Yu, Seong Ug Kim, Jacob Choi +1
Bias is a disproportionate prejudice in favor of one side against another. Due to the success of transformer-based Masked Language Models (MLMs) and their impact on many NLP tasks,…
Exploring the Impact of Human Evaluator Group on Chat-Oriented Dialogue Evaluation
Sarah E. Finch, James D. Finch, Jinho D. Choi
Human evaluation has been widely accepted as the standard for evaluating chat-oriented dialogue systems. However, there is a significant variation in previous work regarding who ge…
Aligning Speakers: Evaluating and Visualizing Text-based Diarization Using Efficient Multiple Sequence Alignment (Extended Version)
Chen Gong, Peilin Wu, Jinho D. Choi
This paper presents a novel evaluation approach to text-based speaker diarization (SD), tackling the limitations of traditional metrics that do not account for any contextual infor…
Leveraging Large Language Models for Automated Dialogue Analysis
Sarah E. Finch, Ellie S. Paek, Jinho D. Choi
Developing high-performing dialogue systems benefits from the automatic identification of undesirable behaviors in system responses. However, detecting such behaviors remains chall…
Widely Interpretable Semantic Representation: Frameless Meaning Representation for Broader Applicability
Lydia Feng, Gregor Williamson, Han He +1
This paper presents a novel semantic representation, WISeR, that overcomes challenges for Abstract Meaning Representation (AMR). Despite its strengths, AMR is not easily applied to…
FCC: Fusing Conversation History and Candidate Provenance for Contextual Response Ranking in Dialogue Systems
Zihao Wang, Eugene Agichtein, Jinho Choi
Response ranking in dialogues plays a crucial role in retrieval-based conversational systems. In a multi-turn dialogue, to capture the gist of a conversation, contextual informatio…
InterviewBot: Real-Time End-to-End Dialogue System to Interview Students for College Admission
Zihao Wang, Nathan Keyes, Terry Crawford +1
We present the InterviewBot that dynamically integrates conversation history and customized topics into a coherent embedding space to conduct 10 mins hybrid-domain (open and closed…
Unleashing the True Potential of Sequence-to-Sequence Models for Sequence Tagging and Structure Parsing
Han He, Jinho D. Choi
Sequence-to-Sequence (S2S) models have achieved remarkable success on various text generation tasks. However, learning complex structures with S2S models remains challenging as ext…
Don't Forget Your ABC's: Evaluating the State-of-the-Art in Chat-Oriented Dialogue Systems
Sarah E. Finch, James D. Finch, Jinho D. Choi
Despite tremendous advancements in dialogue systems, stable evaluation still requires human judgments producing notoriously high-variance metrics due to their inherent subjectivity…
Online Coreference Resolution for Dialogue Processing: Improving Mention-Linking on Real-Time Conversations
Liyan Xu, Jinho D. Choi
This paper suggests a direction of coreference resolution for online decoding on actively generated input such as dialogue, where the model accepts an utterance and its past contex…
Modeling Task Interactions in Document-Level Joint Entity and Relation Extraction
Liyan Xu, Jinho D. Choi
We target on the document-level relation extraction in an end-to-end setting, where the model needs to jointly perform mention extraction, coreference resolution (COREF) and relati…
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…
Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-sentence Dependency Graph
Liyan Xu, Xuchao Zhang, Bo Zong +6
We target the task of cross-lingual Machine Reading Comprehension (MRC) in the direct zero-shot setting, by incorporating syntactic features from Universal Dependencies (UD), and t…
What Went Wrong? Explaining Overall Dialogue Quality through Utterance-Level Impacts
James D. Finch, Sarah E. Finch, Jinho D. Choi
Improving user experience of a dialogue system often requires intensive developer effort to read conversation logs, run statistical analyses, and intuit the relative importance of…
An Approach to Inference-Driven Dialogue Management within a Social Chatbot
Sarah E. Finch, James D. Finch, Daniil Huryn +4
We present a chatbot implementing a novel dialogue management approach based on logical inference. Instead of framing conversation a sequence of response generation tasks, we model…
Boosting Cross-Lingual Transfer via Self-Learning with Uncertainty Estimation
Liyan Xu, Xuchao Zhang, Xujiang Zhao +3
Recent multilingual pre-trained language models have achieved remarkable zero-shot performance, where the model is only finetuned on one source language and directly evaluated on t…
Adapted End-to-End Coreference Resolution System for Anaphoric Identities in Dialogues
Liyan Xu, Jinho D. Choi
We present an effective system adapted from the end-to-end neural coreference resolution model, targeting on the task of anaphora resolution in dialogues. Three aspects are specifi…
Intensionalizing Abstract Meaning Representations: Non-Veridicality and Scope
Gregor Williamson, Patrick Elliott, Yuxin Ji +1
Abstract Meaning Representation (AMR) is a graphical meaning representation language designed to represent propositional information about argument structure. However, at present i…
StreamSide: A Fully-Customizable Open-Source Toolkit for Efficient Annotation of Meaning Representations
Jinho D. Choi, Gregor Williamson
This demonstration paper presents StreamSide, an open-source toolkit for annotating multiple kinds of meaning representations. StreamSide supports frame-based annotation schemes e.…
The Stem Cell Hypothesis: Dilemma behind Multi-Task Learning with Transformer Encoders
Han He, Jinho D. Choi
Multi-task learning with transformer encoders (MTL) has emerged as a powerful technique to improve performance on closely-related tasks for both accuracy and efficiency while a que…
ELIT: Emory Language and Information Toolkit
Han He, Liyan Xu, Jinho D. Choi
We introduce ELIT, the Emory Language and Information Toolkit, which is a comprehensive NLP framework providing transformer-based end-to-end models for core tasks with a special fo…
Levi Graph AMR Parser using Heterogeneous Attention
Han He, Jinho D. Choi
Coupled with biaffine decoders, transformers have been effectively adapted to text-to-graph transduction and achieved state-of-the-art performance on AMR parsing. Many prior works,…