1 citations · 1 across the 4 of their papers we have counts for
4 papers
AgentSLABench: Evaluating and Benchmarking Agentic Systems Under Resource Constraints
Meher Bhaskar Madiraju, Meher Sai Preetam Madiraju
We present AgentSLABench, a resource-aware evaluation framework for autonomous AI agents that measures correctness alongside latency, cost, compute, memory, and network usage under…
RigorBench: Benchmarking Engineering Process Discipline in Autonomous AI Coding Agents
Meher Bhaskar Madiraju, Meher Sai Preetam Madiraju
Agentic coding harnesses - such as Agent-Skills, Superpowers, and Agent-Rigor - are increasingly deployed to augment underlying LLMs for real-world software engineering tasks. Exis…
Simplex-Constrained Sparse Bagging: Transitioning from Uniform Priors to Sparse Posteriors in Ensemble Learning
Meher Sai Preetam Madiraju, Meher Bhaskar Madiraju
We present Simplex-Constrained Sparse Bagging (SCSB), a mathematically rigorous framework for post-training compression and probability calibration of bootstrap-based bagging ensem…
OptiMindTune: A Multi-Agent Framework for Intelligent Hyperparameter Optimization
Meher Bhaskar Madiraju, Meher Sai Preetam Madiraju
Hyperparameter optimization (HPO) is a critical yet challenging aspect of machine learning model development, significantly impacting model performance and generalization. Traditio…