activity
20242026
most citedUtilizing Large Language Models for Named Entity Recognition in Traditional Chinese Medicine against COVID-19 Literature: Comparative Study

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Rewrite the News: Tracing Editorial Reuse Across News Agencies

Soveatin Kuntur, Nina Smirnova, Anna Wroblewska +2

This paper investigates sentence-level text reuse in multilingual journalism, analyzing where reused content occurs within articles. We present a weakly supervised method for detec…

cs.CL2026

Analysing Calls to Order in German Parliamentary Debates

Nina Smirnova, Daniel Dan, Philipp Mayr

Parliamentary debate constitutes a central arena of political power, shaping legislative outcomes and public discourse. Incivility within this arena signals political polarization…

cs.DL2025

Open Political Corpora: Structuring, Searching, and Analyzing Political Text Collections with PoliCorp

Nina Smirnova, Muhammad Ahsan Shahid, Philipp Mayr

In this work, we present PoliCorp (https://demo-pollux.gesis.org/), a web portal designed to facilitate the search and analysis of political text corpora. PoliCorp provides researc…

cs.CL2025

Annotating Scientific Uncertainty: A comprehensive model using linguistic patterns and comparison with existing approaches

Panggih Kusuma Ningrum, Philipp Mayr, Nina Smirnova +1

UnScientify, a system designed to detect scientific uncertainty in scholarly full text. The system utilizes a weakly supervised technique to identify verbally expressed uncertainty…

cs.CL20241 cited

Utilizing Large Language Models for Named Entity Recognition in Traditional Chinese Medicine against COVID-19 Literature: Comparative Study

Xu Tong, Nina Smirnova, Sharmila Upadhyaya +5

Objective: To explore and compare the performance of ChatGPT and other state-of-the-art LLMs on domain-specific NER tasks covering different entity types and domains in TCM against…