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Adithya V. Ganesan

7 accepted papers

2026

Quantifying Error Disparities in Population Health Models

IJCAI 2026

Many high-stakes social applications of AI, such as public health surveillance and policy planning, operate at the community- rather than individual-level. However, most model fairness research evaluates disparities at the individual- or data-level (i.e. document or image) and rely on metrics define

Cited by 0Scholar
2025

Capturing Author Self Beliefs in Social Media Language

ACL 2025long

Measuring the prevalence and dimensions of self beliefs is essential for understanding human self-perception and various psychological outcomes. In this paper, we develop a novel task for classifying language that contains explicit or implicit mentions of the author’s self beliefs. We contribute a s…

Cited by 0SourcePDFScholar
2025

Idiosyncratic Versus Normative Modeling of Atypical Speech Recognition: Dysarthric Case Studies

EMNLP 2025

State-of-the-art automatic speech recognition (ASR) models like Whisper perform poorly on atypical speech, such as that produced by individuals with dysarthria. Past works for atypical speech have mostly investigated fully personalized (or idiosyncratic) models, but modeling strategies that can both

2025

Systematic Evaluation of Auto-Encoding and Large Language Model Representations for Capturing Author States and Traits

ACL 2025finding

Large Language Models (LLMs) are increasingly used in human-centered applications, yet their ability to model diverse psychological constructs is not well understood. In this study, we systematically evaluate a range of Transformer-LMs to predict psychological variables across five major dimensions:…

Cited by 0SourcePDFScholar
2025

WhiSPA: Semantically and Psychologically Aligned Whisper with Self-Supervised Contrastive and Student-Teacher Learning

ACL 2025long

Current speech encoding pipelines often rely on an additional text-based LM to get robust representations of human communication, even though SotA speech-to-text models often have a LM within. This work proposes an approach to improve the LM within an audio model such that the subsequent text-LM is…

2023

Discourse-Level Representations can Improve Prediction of Degree of Anxiety

ACL 2023short

Anxiety disorders are the most common of mental illnesses, but relatively little is known about how to detect them from language. The primary clinical manifestation of anxiety is worry associated cognitive distortions, which are likely expressed at the discourse-level of semantics. Here, we investig…

Cited by 11SourcePDFScholar
2021

Empirical Evaluation of Pre-trained Transformers for Human-Level NLP: The Role of Sample Size and Dimensionality

NAACL 2021long

In human-level NLP tasks, such as predicting mental health, personality, or demographics, the number of observations is often smaller than the standard 768+ hidden state sizes of each layer within modern transformer-based language models, limiting the ability to effectively leverage transformers. He…