3 papers
cs.CL2026
Grounded Optimization: A Layered Engineering Framework for Reducing LLM Hallucination in Automated Personal Document Rewriting
Shashank Indukuri, Adarsh Agrawal
Large language models (LLMs) are increasingly applied to resume optimization for applicant tracking systems, introducing hallucination failures distinct from general text generatio…
cs.IR2026
Schema-First Retrieval: Embedding Catalogs for Natural Language Analytics
Adarsh Agrawal, Shashank Indukuri
Enterprise text-to-SQL systems often fail before SQL is generated: the model receives the wrong schema context. Modern warehouses contain thousands of tables, abbreviated columns,…
cs.AI2026
Self-Healing Agentic Orchestrators for Reliable Tool-Augmented Large Language Model Systems
Rahul Suresh Babu, Adarsh Agrawal
Tool-augmented large language model (LLM) agents rely on orchestration layers that coordinate planning, retrieval, tool invocation, validation, memory, and recovery. In these syste…