activity
20182026
most citedshs-nlp at RadSum23: Domain-Adaptive Pre-training of Instruction-tuned LLMs for Radiology Report Impression Generation

5 citations · 12 across the 7 of their papers we have counts for

collaborators

9 papers

cs.CL2026

FinRT: Distilling Adaptive Red-Teaming Strategies into Reusable Adversarial Generators in Consumer Finance

Rikhiya Ghosh, Himanshu Kumar, Sriram Venkatapathy +3

In regulated industries like consumer finance, seemingly harmless user queries can exploit large language model vulnerabilities, triggering safety failures and pushing responses da…

cs.CR2026

Workspace Topology as an Attack Vector in Agentic Coding Assistants

Alexandre G. R. Day, Pradeep Yadlapalli, Sriram Venkatapathy +9

Agentic coding assistants are finding widespread use, not just in new code development but in quickly ingesting and leveraging third-party code. This opens up a risk of malicious c…

cs.CL2025

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…

cs.CL2024★ 1 cited

CVE-LLM : Automatic vulnerability evaluation in medical device industry using large language models

Rikhiya Ghosh, Oladimeji Farri, Hans-Martin von Stockhausen +2

The healthcare industry is currently experiencing an unprecedented wave of cybersecurity attacks, impacting millions of individuals. With the discovery of thousands of vulnerabilit…

cs.CL2023★ 3 cited

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…

cs.CL2023★ 5 cited

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…

cs.CL2023

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…

cs.AI2018

Toward the Engineering of Virtuous Machines

Naveen Sundar Govindarajulu, Selmer Bringsjord, Rikhiya Ghosh

While various traditions under the 'virtue ethics' umbrella have been studied extensively and advocated by ethicists, it has not been clear that there exists a version of virtue et…

cs.AI2018★ 3 cited

One Formalization of Virtue Ethics via Learning

Naveen Sundar Govindarajulu, Selmer Bringjsord, Rikhiya Ghosh

Given that there exist many different formal and precise treatments of deontologi- cal and consequentialist ethics, we turn to virtue ethics and consider what could be a formalizat…