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Ranjita Naik

3 accepted papers

2024

Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models

ICLR 2024poster

We investigate the internal behavior of Transformer-based Large Language Models (LLMs) when they generate factually incorrect text. We propose modeling factual queries as constraint satisfaction problems and use this framework to investigate how the LLM interacts internally with factual constraints.…

2024

GATE X-E : A Challenge Set for Gender-Fair Translations from Weakly-Gendered Languages

ACL 2024findings

Neural Machine Translation (NMT) continues to improve in quality and adoption, yet the in advertent perpetuation of gender bias remains a significant concern. Despite numerous studies on gender bias in translations into English from weakly gendered-languages, there are no benchmarks for evaluating t…

2024

KITAB: Evaluating LLMs on Constraint Satisfaction for Information Retrieval

ICLR 2024poster

We study the ability of state-of-the art models to answer constraint satisfaction queries for information retrieval (e.g., “a list of ice cream shops in San Diego”). In the past, such queries were considered as tasks that could only be solved via web-search or knowledge bases. More recently, large l…

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