4 papers · 1 filter
Cognitive Fatigue in Autoregressive Transformers: Formalization and Measurement
Riju Marwah, Ritvik Garimella, Vishal Pallagani +3
Autoregressive language models frequently degrade during long-horizon generation, producing repetitive text, losing instruction adherence, and exhibiting unstable entropy. Despite…
CANDI: Contextual Alignment for Niche Domains Question Answering
Megha Chakraborty, Darssan L. Eswaramoorthi, Het Riteshkumar Shah +5
The deployment of large language models (LLMs) in specialized domains like medical diagnostics and financial advisory necessitates evaluating capabilities beyond general knowledge.…
Large Language Models for Mental Health Diagnostic Assessments: Exploring The Potential of Large Language Models for Assisting with Mental Health Diagnostic Assessments -- The Depression and Anxiety Case
Kaushik Roy, Harshul Surana, Darssan Eswaramoorthi +4
Large language models (LLMs) are increasingly attracting the attention of healthcare professionals for their potential to assist in diagnostic assessments, which could alleviate th…
RDR: the Recap, Deliberate, and Respond Method for Enhanced Language Understanding
Yuxin Zi, Hariram Veeramani, Kaushik Roy +1
Natural language understanding (NLU) using neural network pipelines often requires additional context that is not solely present in the input data. Through Prior research, it has b…