24 citations · 28 across the 11 of their papers we have counts for
11 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…
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…
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…
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…
On Robustness of Finetuned Transformer-based NLP Models
Pavan Kalyan Reddy Neerudu, Subba Reddy Oota, Mounika Marreddy +2
Transformer-based pretrained models like BERT, GPT-2 and T5 have been finetuned for a large number of natural language processing (NLP) tasks, and have been shown to be very effect…
Syntactic Structure Processing in the Brain while Listening
Subba Reddy Oota, Mounika Marreddy, Manish Gupta +1
Syntactic parsing is the task of assigning a syntactic structure to a sentence. There are two popular syntactic parsing methods: constituency and dependency parsing. Recent works h…
GAE-ISumm: Unsupervised Graph-Based Summarization of Indian Languages
Lakshmi Sireesha Vakada, Anudeep Ch, Mounika Marreddy +2
Document summarization aims to create a precise and coherent summary of a text document. Many deep learning summarization models are developed mainly for English, often requiring a…
Neural Language Taskonomy: Which NLP Tasks are the most Predictive of fMRI Brain Activity?
Subba Reddy Oota, Jashn Arora, Veeral Agarwal +3
Several popular Transformer based language models have been found to be successful for text-driven brain encoding. However, existing literature leverages only pretrained text Trans…
Multi-Task Text Classification using Graph Convolutional Networks for Large-Scale Low Resource Language
Mounika Marreddy, Subba Reddy Oota, Lakshmi Sireesha Vakada +2
Graph Convolutional Networks (GCN) have achieved state-of-art results on single text classification tasks like sentiment analysis, emotion detection, etc. However, the performance…
Affect in Tweets Using Experts Model
Subba Reddy Oota, Adithya Avvaru, Mounika Marreddy +1
Estimating the intensity of emotion has gained significance as modern textual inputs in potential applications like social media, e-retail markets, psychology, advertisements etc.,…