5 citations · 16 across the 11 of their papers we have counts for
11 papers
CVE-LLM : Ontology-Assisted Automatic Vulnerability Evaluation Using Large Language Models
Rikhiya Ghosh, Hans-Martin von Stockhausen, Martin Schmitt +3
The National Vulnerability Database (NVD) publishes over a thousand new vulnerabilities monthly, with a projected 25 percent increase in 2024, highlighting the crucial need for rap…
Fusion of Domain-Adapted Vision and Language Models for Medical Visual Question Answering
Cuong Nhat Ha, Shima Asaadi, Sanjeev Kumar Karn +3
Vision-language models, while effective in general domains and showing strong performance in diverse multi-modal applications like visual question-answering (VQA), struggle to main…
General-Purpose vs. Domain-Adapted Large Language Models for Extraction of Structured Data from Chest Radiology Reports
Ali H. Dhanaliwala, Rikhiya Ghosh, Sanjeev Kumar Karn +4
Radiologists produce unstructured data that can be valuable for clinical care when consumed by information systems. However, variability in style limits usage. Study compares syste…
Generation of Radiology Findings in Chest X-Ray by Leveraging Collaborative Knowledge
Manuela Daniela Danu, George Marica, Sanjeev Kumar Karn +8
Among all the sub-sections in a typical radiology report, the Clinical Indications, Findings, and Impression often reflect important details about the health status of a patient. T…
shs-nlp at RadSum23: Domain-Adaptive Pre-training of Instruction-tuned LLMs for Radiology Report Impression Generation
Sanjeev Kumar Karn, Rikhiya Ghosh, Kusuma P +1
Instruction-tuned generative Large language models (LLMs) like ChatGPT and Bloomz possess excellent generalization abilities, but they face limitations in understanding radiology r…
RadLing: Towards Efficient Radiology Report Understanding
Rikhiya Ghosh, Sanjeev Kumar Karn, Manuela Daniela Danu +3
Most natural language tasks in the radiology domain use language models pre-trained on biomedical corpus. There are few pretrained language models trained specifically for radiolog…
Differentiable Multi-Agent Actor-Critic for Multi-Step Radiology Report Summarization
Sanjeev Kumar Karn, Ning Liu, Hinrich Schuetze +1
The IMPRESSIONS section of a radiology report about an imaging study is a summary of the radiologist's reasoning and conclusions, and it also aids the referring physician in confir…
Few-Shot Learning of an Interleaved Text Summarization Model by Pretraining with Synthetic Data
Sanjeev Kumar Karn, Francine Chen, Yan-Ying Chen +2
Interleaved texts, where posts belonging to different threads occur in a sequence, commonly occur in online chat posts, so that it can be time-consuming to quickly obtain an overvi…
A Hierarchical Decoder with Three-level Hierarchical Attention to Generate Abstractive Summaries of Interleaved Texts
Sanjeev Kumar Karn, Francine Chen, Yan-Ying Chen +2
Interleaved texts, where posts belonging to different threads occur in one sequence, are a common occurrence, e.g., online chat conversations. To quickly obtain an overview of such…
News Article Teaser Tweets and How to Generate Them
Sanjeev Kumar Karn, Mark Buckley, Ulli Waltinger +1
In this work, we define the task of teaser generation and provide an evaluation benchmark and baseline systems for the process of generating teasers. A teaser is a short reading su…
Neural Architectures for Open-Type Relation Argument Extraction
Benjamin Roth, Costanza Conforti, Nina Poerner +2
In this work, we introduce the task of Open-Type Relation Argument Extraction (ORAE): Given a corpus, a query entity Q and a knowledge base relation (e.g.,"Q authored notable work…