Search Results for author:
Found 9 papers, 3 papers with code
CAISA at WASSA 2022: Adapter-Tuning for Empathy Prediction
We build a system that leverages adapters, a light weight and efficient method for leveraging large language models to perform the task Em- pathy and Distress prediction tasks for WASSA 2022.
Challenges of GPT-3-based Conversational Agents for Healthcare
The potential to provide patients with faster information access while allowing medical specialists to concentrate on critical tasks makes medical domain dialog agents appealing.
A Critical Reflection and Forward Perspective on Empathy and Natural Language Processing
We review the state of research on empathy in natural language processing and identify the following issues: (1) empathy definitions are absent or abstract, which (2) leads to low construct validity and reproducibility.
Mitigating Toxic Degeneration with Empathetic Data: Exploring the Relationship Between Toxicity and Empathy
Large pre-trained neural language models have supported the effectiveness of many NLP tasks, yet are still prone to generating toxic language hindering the safety of their use.
Investigating User Radicalization: A Novel Dataset for Identifying Fine-Grained Temporal Shifts in Opinion
The dataset includes a sufficient amount of stance polarity and intensity labels per user over time and within entire conversational threads, thus making subtle opinion fluctuations detectable both in long term and in short term.
Modeling Proficiency with Implicit User Representations
We introduce the problem of proficiency modeling: Given a user's posts on a social media platform, the task is to identify the subset of posts or topics for which the user has some level of proficiency.
Exploring Self-Identified Counseling Expertise in Online Support Forums
A growing number of people engage in online health forums, making it important to understand the quality of the advice they receive.
Chord Embeddings: Analyzing What They Capture and Their Role for Next Chord Prediction and Artist Attribute Prediction
In the first case study, we demonstrate that using chord embeddings in a next chord prediction task yields predictions that more closely match those by experienced musicians.
Expressive Interviewing: A Conversational System for Coping with COVID-19
The ongoing COVID-19 pandemic has raised concerns for many regarding personal and public health implications, financial security and economic stability.
