3 papers
cs.IR2026
Lightweight Query Routing for Adaptive RAG: A Baseline Study on RAGRouter-Bench
Prakhar Bansal, Shivangi Agarwal
Retrieval-Augmented Generation pipelines span a wide range of retrieval strategies that differ substantially in token cost and capability. Selecting the right strategy per query is…
cs.CL2026
Beyond the Parameters: A Technical Survey of Contextual Enrichment in Large Language Models: From In-Context Prompting to Causal Retrieval-Augmented Generation
Prakhar Bansal, Shivangi Agarwal
Large language models (LLMs) encode vast world knowledge in their parameters, yet they remain fundamentally limited by static knowledge, finite context windows, and weakly structur…
cs.LG2025
Model Selection for Off-policy Evaluation: New Algorithms and Experimental Protocol
Pai Liu, Lingfeng Zhao, Shivangi Agarwal +4
Holdout validation and hyperparameter tuning from data is a long-standing problem in offline reinforcement learning (RL). A standard framework is to use off-policy evaluation (OPE)…