5 papers
Large Language Models Decide Early and Explain Later
Ayan Datta, Zhixue Zhao, Bhuvanesh Verma +3
Large Language Models often achieve strong performance by generating long intermediate chain-of-thought reasoning. However, it remains unclear when a model's final answer is actual…
From Early Encoding to Late Suppression: Interpreting LLMs on Character Counting Tasks
Ayan Datta, Mounika Marreddy, Alexander Mehler +2
Large language models (LLMs) exhibit failures on elementary symbolic tasks such as character counting in a word, despite excelling on complex benchmarks. Although this limitation h…
IndicSentEval: How Effectively do Multilingual Transformer Models encode Linguistic Properties for Indic Languages?
Akhilesh Aravapalli, Mounika Marreddy, Radhika Mamidi +2
Transformer-based models have revolutionized the field of natural language processing. To understand why they perform so well and to assess their reliability, several studies have…
Multi-modal brain encoding models for multi-modal stimuli
Subba Reddy Oota, Khushbu Pahwa, Mounika Marreddy +3
Despite participants engaging in unimodal stimuli, such as watching images or silent videos, recent work has demonstrated that multi-modal Transformer models can predict visual bra…
USDC: A Dataset of ser tance and ogmatism in Long onversations
Mounika Marreddy, Subba Reddy Oota, Venkata Charan Chinni +2
Analyzing user opinion changes in long conversation threads is extremely critical for applications like enhanced personalization, market research, political campaigns, customer ser…