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Rishabh Adiga

2 accepted papers

2025

Attention Speaks Volumes: Localizing and Mitigating Bias in Language Models

ACL 2025long

We believe that analyzing attention is crucial for understanding bias in large language models (LLMs); in ambiguous comparative prompting frameworks, it provides insight into how the LLM distributes its focus across different entities, and how this contributes to biased decisions. To this end, we fi…

Cited by 0SourcePDFScholar
2024

Designing Informative Metrics for Few-Shot Example Selection

ACL 2024findings

Pretrained language models (PLMs) have shown remarkable few-shot learning capabilities when provided with properly formatted examples. However, selecting the “best” examples remains an open challenge. We propose a complexity-based prompt selection approach for sequence tagging tasks. This approach a…

Cited by 1SourcePDFScholar