Papers by Ronnie Rajan

2 papers
Cross-Examination Framework: A Task-Agnostic Diagnostic for Information Fidelity in Text-to-Text Generation (2026.acl-long)

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Challenge: Traditional metrics like BLEU and BERTScore fail to capture semantic fidelity in generative text-to-text tasks.
Approach: They propose a cross-examination framework that generates verifiable questions from each text and performs a Cross-exam to derive three interpretable scores: Coverage, Conformity, and Consistency.
Outcome: The proposed framework detects critical errors across translation, summarization and clinical note-generation and human expert validation shows it is reliable without gold references.
Building Trust in Clinical LLMs: Bias Analysis and Dataset Transparency (2025.emnlp-main)

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Challenge: Current dataset curation and bias assessment practices lack transparency . current approaches lack a thorough understanding of how data characteristics influence model behavior .
Approach: They propose a comprehensive bias evaluation framework that integrates general benchmarks with a healthcare-specific methodology to probe for biases in a sensitive healthcare context.
Outcome: The proposed approach to bias evaluation leverages established benchmarks and a healthcare-specific methodology.

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