4 papers
Choosing a Text Embedding Model: A Practical Benchmarking and Decision Framework
Madhav S Baidya
Choosing the right text embedding model is one of the most consequential -- and most frequently under-examined -- decisions in building a retrieval or search system, yet the model…
Selective-Advantage Entropy-Adaptive Horizon GRPO: Asymmetric Token-Level Discounting for Efficient Reinforcement Learning of Language Models
Chirag Chawla, Rohan Charudatt Salvi, Madhav S. Baidya
Group Relative Policy Optimisation (GRPO) has emerged as an effective reinforcement-learning algorithm for aligning language models on reasoning tasks, but it treats every token po…
PassiveQA: A Three-Action Framework for Epistemically Calibrated Question Answering via Supervised Finetuning
Madhav S Baidya
Large Language Models (LLMs) have achieved strong performance in question answering and retrieval-augmented generation (RAG), yet they implicitly assume that user queries are fully…
Detecting the Machine: A Comprehensive Benchmark of AI-Generated Text Detectors Across Architectures, Domains, and Adversarial Conditions
Madhav S. Baidya, S. S. Baidya, Chirag Chawla
The rapid proliferation of large language models (LLMs) has created an urgent need for robust and generalizable detectors of machine-generated text. Existing benchmarks typically e…