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20212026
most citedWhen AI Benchmarks Plateau: A Systematic Study of Benchmark Saturation

2 citations · 6 across the 10 of their papers we have counts for

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8 papers · 1 filter

cs.CL2026

Investigating Multi-Cultural Value Selection Biases in LLMs

Siddhesh Pawar, Arnav Arora, Dustin Wright +2

Large language models (LLMs) serve users whose cultural identities are multi-layered, yet cultural evaluations commonly reduce identity to one label. In this work, we study LLMs un…

cs.CL2026

Not What, But How: A Framework for Auditing LLM Responses across Positioning, Generalization, Anthropomorphism, and Maxims

Siddhesh Milind Pawar, Sarah Masud, Haneul Yoo +2

Large language models (LLMs) are being increasingly used to answer subjective, information-seeking questions, where users are sensitive to how responses are communicated, not just…

cs.CL2025

CulTrace: Tracing Internal Cultural Reasoning in Large Language Models

Haeun Yu, Arnav Arora, Seogyeong Jeong +7

The growing deployment of large language models (LLMs) across diverse cultural contexts necessitates a deeper understanding of models' hidden representations of different cultures.…

cs.CL2025

BiasGym: A Simple and Generalizable Framework for Analyzing and Removing Biases through Injection

Sekh Mainul Islam, Nadav Borenstein, Siddhesh Milind Pawar +3

Understanding biases and stereotypes encoded in the weights of Large Language Models (LLMs) is crucial for developing effective mitigation strategies. However, biased behavior is o…

cs.CL2025★ 1 cited

Presumed Cultural Identity: How Names Shape LLM Responses

Siddhesh Pawar, Arnav Arora, Lucie-Aimée Kaffee +1

Names are deeply tied to human identity. They can serve as markers of individuality, cultural heritage, and personal history. However, using names as a core indicator of identity c…

cs.CL2024★ 2 cited

Survey of Cultural Awareness in Language Models: Text and Beyond

Siddhesh Pawar, Junyeong Park, Jiho Jin +7

Large-scale deployment of large language models (LLMs) in various applications, such as chatbots and virtual assistants, requires LLMs to be culturally sensitive to the user to ens…

cs.CL2023

Agree To Disagree

Abhinav Raghuvanshi, Siddhesh Pawar, Anirudh Mittal

How frequently do individuals thoroughly review terms and conditions before proceeding to register for a service, install software, or access a website? The majority of internet us…

cs.CL2021

Tapping BERT for Preposition Sense Disambiguation

Siddhesh Pawar, Shyam Thombre, Anirudh Mittal +2

Prepositions are frequently occurring polysemous words. Disambiguation of prepositions is crucial in tasks like semantic role labelling, question answering, text entailment, and no…