4 citations · 4 across the 1 of their papers we have counts for
7 papers
Few shot chain-of-thought driven reasoning to prompt LLMs for open ended medical question answering
Saeel Sandeep Nachane, Ojas Gramopadhye, Prateek Chanda +5
In this paper, we propose a modified version of the MedQA-USMLE dataset, named MEDQA-OPEN, which contains open-ended medical questions without options to mimic clinical scenarios,…
ToolWeave: Structured Synthesis of Complex Multi-Turn Tool-Calling Dialogues
Dinesh Khandelwal, Gnana Prakash Punnavajhala, GPS Bhargav +4
Multi-turn tool calling is essential for LLMs to function as autonomous agents, yet synthesizing the training data required for these capabilities remains a fundamental challenge.…
A Library of LLM Intrinsics for Retrieval-Augmented Generation
Marina Danilevsky, Kristjan Greenewald, Chulaka Gunasekara +13
In the developer community for large language models (LLMs), there is not yet a clean pattern analogous to a software library, to support very large scale collaboration. Even for t…
Systematic Knowledge Injection into Large Language Models via Diverse Augmentation for Domain-Specific RAG
Kushagra Bhushan, Yatin Nandwani, Dinesh Khandelwal +4
Retrieval-Augmented Generation (RAG) has emerged as a prominent method for incorporating domain knowledge into Large Language Models (LLMs). While RAG enhances response relevance b…
Selective Self-to-Supervised Fine-Tuning for Generalization in Large Language Models
Sonam Gupta, Yatin Nandwani, Asaf Yehudai +3
Fine-tuning Large Language Models (LLMs) on specific datasets is a common practice to improve performance on target tasks. However, this performance gain often leads to overfitting…
MediTOD: An English Dialogue Dataset for Medical History Taking with Comprehensive Annotations
Vishal Vivek Saley, Goonjan Saha, Rocktim Jyoti Das +2
Medical task-oriented dialogue systems can assist doctors by collecting patient medical history, aiding in diagnosis, or guiding treatment selection, thereby reducing doctor burnou…