most citedThe Troubling Emergence of Hallucination in Large Language Models -- An Extensive Definition, Quantification, and Prescriptive Remediations

11 citations · 19 across the 11 of their papers we have counts for

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cs.AI2024

RoundTable: Leveraging Dynamic Schema and Contextual Autocomplete for Enhanced Query Precision in Tabular Question Answering

Pratyush Kumar, Kuber Vijaykumar Bellad, Bharat Vadlamudi +1

With advancements in Large Language Models (LLMs), a major use case that has emerged is querying databases in plain English, translating user questions into executable database que…

cs.AI2024

Out-of-Distribution Detection with Attention Head Masking for Multimodal Document Classification

Christos Constantinou, Georgios Ioannides, Aman Chadha +2

Detecting out-of-distribution (OOD) data is crucial in machine learning applications to mitigate the risk of model overconfidence, thereby enhancing the reliability and safety of d…

cs.AI2024

MedSumm: A Multimodal Approach to Summarizing Code-Mixed Hindi-English Clinical Queries

Akash Ghosh, Arkadeep Acharya, Prince Jha +7

In the healthcare domain, summarizing medical questions posed by patients is critical for improving doctor-patient interactions and medical decision-making. Although medical data h…

cs.AI202311 cited

The Troubling Emergence of Hallucination in Large Language Models -- An Extensive Definition, Quantification, and Prescriptive Remediations

Vipula Rawte, Swagata Chakraborty, Agnibh Pathak +5

The recent advancements in Large Language Models (LLMs) have garnered widespread acclaim for their remarkable emerging capabilities. However, the issue of hallucination has paralle…

cs.AI20232 cited

Artificial Intelligence in Career Counseling: A Test Case with ResumAI

Muhammad Rahman, Sachi Figliolini, Joyce Kim +4

The rise of artificial intelligence (AI) has led to various means of integration of AI aimed to provide efficiency in tasks, one of which is career counseling. A key part of gettin…