Papers by Gil Pasternak

2 papers
Measuring Risk of Bias in Biomedical Reports: The RoBBR Benchmark (2025.emnlp-main)

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Challenge: Systematic reviews should take into account the quality of available evidence, placing more weight on studies that use a valid methodology.
Approach: They propose to use a risk-of-bias framework to assess the methodological strength of biomedical papers by combining expert reviewers' judgments with research paper sentences.
Outcome: The proposed system measures the methodological strength of biomedical papers using the risk-of-bias framework used for systematic reviews.
GLiNER2: Schema-Driven Multi-Task Learning for Structured Information Extraction (2025.emnlp-demos)

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Challenge: Existing solutions for information extraction (IE) require specialized models for different tasks or require expensive large language models.
Approach: They propose a framework that enhances the original GLiNER architecture to support named entity recognition, text classification, and hierarchical structured data extraction within a single efficient model.
Outcome: The proposed framework improves performance across diverse IE tasks and accessibility compared to LLM-based alternatives.

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