Author

Sachindra Joshi

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#artificial intelligence Preprint Sep 2026

STAIR (STructure Aware Information Retriever): A novel dataset and LLM based retriever for document structure augmentation

Retrieval Augmented Generation (RAG) is a key component for generating accurate and hallucination free answers using Large Language Models (LLMs). LLMs are improving at handling long context, but still suffer from"lost in the middle"problem. Thus, precise and accurate retrieval is important. Current retrievers chunk lo...

Vineet Kumar, Meghanadh Pulivarthi, Vishwajeet Kumar et al. · 1 citation

#artificial intelligence Preprint Sep 2026

DKL: Decoupled Knowledge Learning for Instruction-Tuned Language Models

RAG has become the de facto method for incorporating new, corpus-specific knowledge into an instruction following LLM (Instruct LLM). Although RAG-based prompting improves factual grounding, it fails when retrieval is incorrect or incomplete, leading to hallucinations. Finetuning methods such as RAFT and PA-RAG enhance...

Kushagra Bhushan, Meghanadh Pulivarthi, Sai Krishna Reddy Sathi et al. · 1 citation

#artificial intelligence Preprint Aug 2026

KItCAT: Knowledge Injection via Input Corruption for Auto-regressive Training

This work introduces KItCAT: Knowledge Injection via Corrupted Auto-regressive Training, a lightweight training strategy that reduces the need for paraphrasing in decoder-only LLMs and shows that KItCAT consistently improves over CPT across multiple datasets and model families.

Meghanadh Pulivarthi, Kushagra Bhushan, Vineet Kumar et al. · 0 citations