1 citations · 1 across the 3 of their papers we have counts for
9 papers
FlexiFlow: Bandit-based Model Switching in ML Workflows
Abhilash Jindal, Todd Nief, Bhanu Prakash Vangala +6
Model optimizations help improve inference performance and accuracy of ML workflows. However, relying on a single model to perform inference across all data batches often fails to…
Code That Works, Environments That Don't: Measuring Environment Reproducibility in AI-Generated Software
Bhanu Prakash Vangala, Tanu Malik
Code generation has emerged as a central capability of large language models, with coding agents now able to produce functionally correct software projects from natural language pr…
Scores That Hold, Benchmarks That Leak: Measuring Dataset Contamination in Public Brain-Tumor MRI Classification
Bhanu Prakash Vangala, Sowmya Guda, Latha Peddi +1
Automated classification of brain tumors from MRI is a heavily published application of deep learning in medical imaging, with reported accuracies on public benchmarks routinely ex…
How Many Labels Does a Language Need? Annotation Budgets and Cross-Lingual Pooling for African-Language Text Classification
Bhanu Prakash Vangala, Sowmya Guda, Navya Vangala
Every text classifier for an African language begins with a budgeting question: how many labelled examples are needed, and can labels from other African languages stand in for them…
One Threshold Does Not Fit All Languages: Language-Conditional Deferral for Reliable and Efficient Low-Resource Text Classification
Bhanu Prakash Vangala, Vangala Navya
In the Global South, the lower-income countries of Africa, Asia, and Latin America where most of the world's languages are spoken, a deployed text classifier usually runs on ordina…
Evaluation Choices Shape Biomedical ML Claims: A Pediatric Pneumonia Benchmark Case Study
Bhanu Prakash Vangala, Sowmya Guda, Latha Peddi +1
Biomedical machine learning papers often compress model performance into one headline number. That number can look like a property of the model even when it depends strongly on how…
Efficient Multi-Model Orchestration for Self-Hosted Large Language Models
Bhanu Prakash Vangala, Tanu Malik
Self-hosting large language models (LLMs) is increasingly appealing for organizations seeking privacy, cost control, and customization. Yet deploying and maintaining in-house model…
HalluMat: Detecting Hallucinations in LLM-Generated Materials Science Content Through Multi-Stage Verification
Bhanu Prakash Vangala, Sajid Mahmud, Pawan Neupane +2
Artificial Intelligence (AI), particularly Large Language Models (LLMs), is transforming scientific discovery, enabling rapid knowledge generation and hypothesis formulation. Howev…
AI-Generated Code Is Not Reproducible (Yet): An Empirical Study of Dependency Gaps in LLM-Based Coding Agents
Bhanu Prakash Vangala, Ali Adibifar, Ashish Gehani +1
The rise of Large Language Models (LLMs) as coding agents promises to accelerate software development, but their impact on generated code reproducibility remains largely unexplored…