activity
20222025
most citedA Comprehensive Survey of Regression Based Loss Functions for Time Series Forecasting

48 citations · 71 across the 12 of their papers we have counts for

collaborators
Showing 2025Show all

9 papers · 1 filter

cs.CL2025

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.SE2025

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.CL2025★ 1 cited

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…

cs.SE2025★ 1 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.SE2025★ 1 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Bug reports provide critical insights into software quality, yet existing datasets often suffer from limited scope, outdated content, or insufficient metadata for machine learning.…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.CL2025★ 1 cited

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.LG2025

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…

cs.CL2025

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…

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…