most citedINCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge

4 citations · 5 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CL2025

Application of CARE-SD text classifier tools to assess distribution of stigmatizing and doubt-marking language features in EHR

Drew Walker, Jennifer Love, Swati Rajwal +4

Introduction: Electronic health records (EHR) are a critical medium through which patient stigmatization is perpetuated among healthcare teams. Methods: We identified linguistic fe…

cs.CL2025

Identifying social isolation themes in NVDRS text narratives using topic modeling and text-classification methods

Drew Walker, Swati Rajwal, Sudeshna Das +2

Social isolation and loneliness, which have been increasing in recent years strongly contribute toward suicide rates. Although social isolation and loneliness are not currently rec…

cs.CL2025

Kaleidoscope: In-language Exams for Massively Multilingual Vision Evaluation

Israfel Salazar, Manuel Fernández Burda, Shayekh Bin Islam +42

The evaluation of vision-language models (VLMs) has mainly relied on English-language benchmarks, leaving significant gaps in both multilingual and multicultural coverage. While mu…

cs.CL2025

HILGEN: Hierarchically-Informed Data Generation for Biomedical NER Using Knowledgebases and Large Language Models

Yao Ge, Yuting Guo, Sudeshna Das +3

We present HILGEN, a Hierarchically-Informed Data Generation approach that combines domain knowledge from the Unified Medical Language System (UMLS) with synthetic data generated b…

cs.CL20241 cited

Decade of Natural Language Processing in Chronic Pain: A Systematic Review

Swati Rajwal

In recent years, the intersection of Natural Language Processing (NLP) and public health has opened innovative pathways for investigating various domains, including chronic pain in…

cs.CL20244 cited

INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge

Angelika Romanou, Negar Foroutan, Anna Sotnikova +56

The performance differential of large language models (LLM) between languages hinders their effective deployment in many regions, inhibiting the potential economic and societal val…