44 citations · 52 across the 12 of their papers we have counts for
14 papers
Doing Less with More: A First-Principles Exploration of the Suitability of Agentic Computing over Alternative Architectural Choices
Ritvik Garimella, Biplav Srivastava, Amit Sheth
There is growing interest in automating business activities with Agentic Artificial Intelligence (AI) due to latter's seeming ease of use. Never has it been easier, or costlier, to…
Output Language Confusion under Multilingual Prompt Contamination
Riju Marwah, Ritvik Garimella, Khusham Bansal +2
Standard factual benchmarks assume clean monolingual prompts and exact-match scoring, two assumptions that break simultaneously in real-world multilingual deployment, from retrieva…
Neuro-symbolic PRM: Enhancing Scientific Reasoning via Structured Traces and Symbolic Verification
Yuxin Zi, Cong Xu, Suparna Bhattacharya +2
While tool-augmented Large Language Models have significantly improved multi-step reasoning in quantitative STEM tasks, a critical residual failure mode remains: intermediate reaso…
SAAG: Structured Agent Assessment and Grounding
Ritvik Garimella, Vedant Khandelwal, Anvi Kohli +1
Exact-match evaluation of agent-calling obscures qualitatively different failure modes: a model may select the right function yet hallucinate argument values, or satisfy a schema w…
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.…
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…
Fast approximate Bayesian multidimensional scaling with consistency guarantees
Ami Sheth, Aaron Smith, Andrew J. Holbrook
Bayesian multidimensional scaling (BMDS) embeds objects in a low-dimensional space to approximately preserve an observed dissimilarity matrix. Compared to classic MDS, BMDS is…
Chatsparent: An Interactive System for Detecting and Mitigating Cognitive Fatigue in LLMs
Riju Marwah, Vishal Pallagani, Ritvik Garimella +1
LLMs are increasingly being deployed as chatbots, but today's interfaces offer little to no friction: users interact through seamless conversations that conceal when the model is d…
NeuroLit Navigator: A Neurosymbolic Approach to Scholarly Article Searches for Systematic Reviews
Vedant Khandelwal, Kaushik Roy, Valerie Lookingbill +4
The introduction of Large Language Models (LLMs) has significantly impacted various fields, including education, for example, by enabling the creation of personalized learning mate…
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…
On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS)
Vishal Pallagani, Kaushik Roy, Bharath Muppasani +7
Automated Planning and Scheduling is among the growing areas in Artificial Intelligence (AI) where mention of LLMs has gained popularity. Based on a comprehensive review of 126 pap…
GEAR-Up: Generative AI and External Knowledge-based Retrieval Upgrading Scholarly Article Searches for Systematic Reviews
Kaushik Roy, Vedant Khandelwal, Harshul Surana +3
Systematic reviews (SRs) - the librarian-assisted literature survey of scholarly articles takes time and requires significant human resources. Given the ever-increasing volume of p…
Neurosymbolic Value-Inspired AI (Why, What, and How)
Amit Sheth, Kaushik Roy
The rapid progression of Artificial Intelligence (AI) systems, facilitated by the advent of Large Language Models (LLMs), has resulted in their widespread application to provide hu…
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…