most citedGitBugs: Bug Reports for Duplicate Detection, Retrieval Augmented Generation, Triage, and More

1 citations · 2 across the 2 of their papers we have counts for

collaborators

9 papers

cs.SE20261 cited

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…

cs.SE20261 cited

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Bug reports provide critical insights into software quality, yet existing datasets often suffer from limited scope, outdated content, or insufficient metadata for machine learning.…

cs.CL2026

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…

cs.SE2026

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…

cs.CL2026

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…

cs.CL2025

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…