1 citations · 2 across the 3 of their papers we have counts for
4 papers
Towards End-to-End Model-Agnostic Explanations for RAG Systems
Viju Sudhi, Sinchana Ramakanth Bhat, Max Rudat +2
Retrieval Augmented Generation (RAG) systems, despite their growing popularity for enhancing model response reliability, often struggle with trustworthiness and explainability. In…
Rethinking Chunk Size For Long-Document Retrieval: A Multi-Dataset Analysis
Sinchana Ramakanth Bhat, Max Rudat, Jannis Spiekermann +1
Chunking is a crucial preprocessing step in retrieval-augmented generation (RAG) systems, significantly impacting retrieval effectiveness across diverse datasets. In this study, we…
ILLUMINER: Instruction-tuned Large Language Models as Few-shot Intent Classifier and Slot Filler
Paramita Mirza, Viju Sudhi, Soumya Ranjan Sahoo +1
State-of-the-art intent classification (IC) and slot filling (SF) methods often rely on data-intensive deep learning models, limiting their practicality for industry applications.…
CarExpert: Leveraging Large Language Models for In-Car Conversational Question Answering
Md Rashad Al Hasan Rony, Christian Suess, Sinchana Ramakanth Bhat +6
Large language models (LLMs) have demonstrated remarkable performance by following natural language instructions without fine-tuning them on domain-specific tasks and data. However…