60 citations · 83 across the 12 of their papers we have counts for
13 papers
The Future of Open Human Feedback
Shachar Don-Yehiya, Ben Burtenshaw, Ramon Fernandez Astudillo +17
Human feedback on conversations with language language models (LLMs) is central to how these systems learn about the world, improve their capabilities, and are steered toward desir…
From Text to Emotion: Unveiling the Emotion Annotation Capabilities of LLMs
Minxue Niu, Mimansa Jaiswal, Emily Mower Provost
Training emotion recognition models has relied heavily on human annotated data, which present diversity, quality, and cost challenges. In this paper, we explore the potential of La…
Lessons from the Trenches on Reproducible Evaluation of Language Models
Stella Biderman, Hailey Schoelkopf, Lintang Sutawika +27
Reliable evaluation of language models (LMs) remains an open challenge. Re- searchers and engineers face methodological issues such as the sensitivity of models to evaluation setup…
Implicit Design Choices and Their Impact on Emotion Recognition Model Development and Evaluation
Mimansa Jaiswal
Emotion recognition is a complex task due to the inherent subjectivity in both the perception and production of emotions. The subjectivity of emotions poses significant challenges…
Best Practices for Noise-Based Augmentation to Improve the Performance of Deployable Speech-Based Emotion Recognition Systems
Mimansa Jaiswal, Emily Mower Provost
Speech emotion recognition is an important component of any human centered system. But speech characteristics produced and perceived by a person can be influenced by a multitude of…
Human-Imitating Metrics for Training and Evaluating Privacy Preserving Emotion Recognition Models Using Sociolinguistic Knowledge
Mimansa Jaiswal, Emily Mower Provost
Privacy preservation is a crucial component of any real-world application. But, in applications relying on machine learning backends, privacy is challenging because models often ca…
Privacy Enhanced Multimodal Neural Representations for Emotion Recognition
Mimansa Jaiswal, Emily Mower Provost
Many mobile applications and virtual conversational agents now aim to recognize and adapt to emotions. To enable this, data are transmitted from users' devices and stored on centra…
Identifying Mood Episodes Using Dialogue Features from Clinical Interviews
Zakaria Aldeneh, Mimansa Jaiswal, Michael Picheny +2
Bipolar disorder, a severe chronic mental illness characterized by pathological mood swings from depression to mania, requires ongoing symptom severity tracking to both guide and m…
Controlling for Confounders in Multimodal Emotion Classification via Adversarial Learning
Mimansa Jaiswal, Zakaria Aldeneh, Emily Mower Provost
Various psychological factors affect how individuals express emotions. Yet, when we collect data intended for use in building emotion recognition systems, we often try to do so by…
MuSE-ing on the Impact of Utterance Ordering On Crowdsourced Emotion Annotations
Mimansa Jaiswal, Zakaria Aldeneh, Cristian-Paul Bara +4
Emotion recognition algorithms rely on data annotated with high quality labels. However, emotion expression and perception are inherently subjective. There is generally not a singl…
"Hang in There": Lexical and Visual Analysis to Identify Posts Warranting Empathetic Responses
Mimansa Jaiswal, Sairam Tabibu, Erik Cambria
In the past few years, social media has risen as a platform where people express and share personal incidences about abuse, violence and mental health issues. There is a need to pi…
The Truth and Nothing but the Truth: Multimodal Analysis for Deception Detection
Mimansa Jaiswal, Sairam Tabibu, Rajiv Bajpai
We propose a data-driven method for automatic deception detection in real-life trial data using visual and verbal cues. Using OpenFace with facial action unit recognition, we analy…
The PRIORI Emotion Dataset: Linking Mood to Emotion Detected In-the-Wild
Soheil Khorram, Mimansa Jaiswal, John Gideon +2
Bipolar Disorder is a chronic psychiatric illness characterized by pathological mood swings associated with severe disruptions in emotion regulation. Clinical monitoring of mood is…