48 citations · 71 across the 12 of their papers we have counts for
13 papers
Support-Contra Asymmetry in LLM Explanations
Avinash Patil
Large Language Models (LLMs) increasingly produce natural language explanations alongside their predictions, yet it remains unclear whether these explanations reference predictive…
When Bugs Linger: A Study of Anomalous Resolution Time Outliers and Their Themes
Avinash Patil
Efficient bug resolution is critical for maintaining software quality and user satisfaction. However, specific bug reports experience unusually long resolution times, which may ind…
Evaluating Reasoning LLMs for Suicide Screening with the Columbia-Suicide Severity Rating Scale
Avinash Patil, Siru Tao, Amardeep Gedhu
Suicide prevention remains a critical public health challenge. While online platforms such as Reddit's r/SuicideWatch have historically provided spaces for individuals to express s…
A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards
Avinash Patil
Software Quality Assurance (SQA) is critical for delivering reliable, secure, and efficient software products. The Software Quality Assurance Process aims to provide assurance that…
GitBugs: Bug Reports for Duplicate Detection, Retrieval Augmented Generation, Triage, and More
Avinash Patil, Siru Tao, Aryan Jadon
Bug reports provide critical insights into software quality, yet existing datasets often suffer from limited scope, outdated content, or insufficient metadata for machine learning.…
Cognitive-Mental-LLM: Evaluating Reasoning in Large Language Models for Mental Health Prediction via Online Text
Avinash Patil, Amardeep Kour Gedhu
Large Language Models (LLMs) have demonstrated potential in predicting mental health outcomes from online text, yet traditional classification methods often lack interpretability a…
Enhancing Domain-Specific Retrieval-Augmented Generation: Synthetic Data Generation and Evaluation using Reasoning Models
Aryan Jadon, Avinash Patil, Shashank Kumar
Retrieval-Augmented Generation (RAG) systems face significant performance gaps when applied to technical domains requiring precise information extraction from complex documents. Cu…
English Please: Evaluating Machine Translation with Large Language Models for Multilingual Bug Reports
Avinash Patil, Siru Tao, Aryan Jadon
Accurate translation of bug reports is critical for efficient collaboration in global software development. In this study, we conduct the first comprehensive evaluation of machine…
Advancing Reasoning in Large Language Models: Promising Methods and Approaches
Avinash Patil, Aryan Jadon
Large Language Models (LLMs) have succeeded remarkably in various natural language processing (NLP) tasks, yet their reasoning capabilities remain a fundamental challenge. While LL…
A Comprehensive Survey of Evaluation Techniques for Recommendation Systems
Aryan Jadon, Avinash Patil
The effectiveness of recommendation systems is pivotal to user engagement and satisfaction in online platforms. As these recommendation systems increasingly influence user choices,…
A Comparative Study of Text Embedding Models for Semantic Text Similarity in Bug Reports
Avinash Patil, Kihwan Han, Aryan Jadon
Bug reports are an essential aspect of software development, and it is crucial to identify and resolve them quickly to ensure the consistent functioning of software systems. Retrie…
Auto-labelling of Bug Report using Natural Language Processing
Avinash Patil, Aryan Jadon
The exercise of detecting similar bug reports in bug tracking systems is known as duplicate bug report detection. Having prior knowledge of a bug report's existence reduces efforts…
A Comprehensive Survey of Regression Based Loss Functions for Time Series Forecasting
Aryan Jadon, Avinash Patil, Shruti Jadon
Time Series Forecasting has been an active area of research due to its many applications ranging from network usage prediction, resource allocation, anomaly detection, and predicti…