4 citations · 5 across the 16 of their papers we have counts for
15 papers · 1 filter
The Culture Within: Towards Mechanistic Understanding of Cultural Reasoning in LLMs
Samee Arif, Furkan Danisman, Angana Borah +6
Large Language Models (LLMs) increasingly operate across culturally diverse settings, yet existing evaluations largely measure cultural behavior at the output level. We introduce C…
AtlasNLP: A Country-Aware Atlas of Dataset Representation in NLP
Joan Nwatu, Tsedeniya Solomon Amare, Longju Bai +17
Understanding which countries are represented in NLP datasets is essential for identifying gaps, targeting data collection, measuring progress, and informing AI policy. However, ge…
SurakshaEval: An Indic Safety Benchmark for Multilingual LLMs
Debopriyo Banerjee, Kapil Rajesh Kavitha, Angana Borah +11
Existing safety evaluation datasets for large language models (LLMs) predominantly focus on English and Western contexts, often overlooking the linguistic diversity and culturally…
Whose Norms? Disentangling Cultural and Personal Alignment in Large Language Models
Angana Borah, Isabelle Augenstein, Rada Mihalcea
Large language models are increasingly used for social decision-making situations that require balancing cultural norms with personal preferences. For example, a user preferring ho…
The Age of Curiosity Meets the Age of AI: Benchmarking Child Safety in Large Language Models
Samee Arif, Angana Borah, Rada Mihalcea
Children increasingly have access to Large Language Models (LLMs), which may expose them to responses that are developmentally inappropriate or require age-sensitive safety, guidan…
Belief-Sim: Towards Belief-Driven Simulation of Demographic Misinformation Susceptibility
Angana Borah, Zohaib Khan, Rada Mihalcea +1
Misinformation is a growing societal threat, and susceptibility to misinformative claims varies across demographic groups due to differences in underlying beliefs. As Large Languag…
The Curious Case of Curiosity across Human Cultures and LLMs
Angana Borah, Zhijing Jin, Rada Mihalcea
Recent advances in Large Language Models (LLMs) have expanded their role in human interaction, yet curiosity -- a central driver of inquiry -- remains underexplored in these system…
NLP for Social Good: A Survey and Outlook of Challenges, Opportunities, and Responsible Deployment
Antonia Karamolegkou, Angana Borah, Eunjung Cho +30
Natural language processing (NLP) now shapes many aspects of our world, yet its potential for positive social impact is underexplored. This paper surveys work in ``NLP for Social G…
Persuasion at Play: Understanding Misinformation Dynamics in Demographic-Aware Human-LLM Interactions
Angana Borah, Rada Mihalcea, Verónica Pérez-Rosas
Existing challenges in misinformation exposure and susceptibility vary across demographic groups, as some populations are more vulnerable to misinformation than others. Large langu…
Mind the (Belief) Gap: Group Identity in the World of LLMs
Angana Borah, Marwa Houalla, Rada Mihalcea
Social biases and belief-driven behaviors can significantly impact Large Language Models (LLMs) decisions on several tasks. As LLMs are increasingly used in multi-agent systems for…
Towards Implicit Bias Detection and Mitigation in Multi-Agent LLM Interactions
Angana Borah, Rada Mihalcea
As Large Language Models (LLMs) continue to evolve, they are increasingly being employed in numerous studies to simulate societies and execute diverse social tasks. However, LLMs a…
Application Specific Compression of Deep Learning Models
Rohit Raj Rai, Angana Borah, Amit Awekar
Large Deep Learning models are compressed and deployed for specific applications. However, current Deep Learning model compression methods do not utilize the information about the…
Towards Region-aware Bias Evaluation Metrics
Angana Borah, Aparna Garimella, Rada Mihalcea
When exposed to human-generated data, language models are known to learn and amplify societal biases. While previous works introduced benchmarks that can be used to assess the bias…
Measuring Spurious Correlation in Classification: 'Clever Hans' in Translationese
Angana Borah, Daria Pylypenko, Cristina Espana-Bonet +1
Recent work has shown evidence of 'Clever Hans' behavior in high-performance neural translationese classifiers, where BERT-based classifiers capitalize on spurious correlations, in…
Are Word Embedding Methods Stable and Should We Care About It?
Angana Borah, Manash Pratim Barman, Amit Awekar
A representation learning method is considered stable if it consistently generates similar representation of the given data across multiple runs. Word Embedding Methods (WEMs) are…