Papers by Prajvi Saxena

2 papers
Newspaper Signaling for Crisis Prediction (2024.naacl-demo)

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Challenge: Existing systems for detecting crisis-related signals are limited due to unstructured data, media, and cultural bias, and multiple languages.
Approach: They propose a model for multi-lingual and open-domain newspaper signaling for detecting crisis-related indicators in newspaper articles.
Outcome: The proposed model can detect crisis-related indicators in multiple languages and can be used in open crisis domains in real-time.
Streamlining LLMs: Adaptive Knowledge Distillation for Tailored Language Models (2025.naacl-srw)

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Challenge: Large language models (LLMs) have transformative potential across industries, e.g., enhancing customer service, revolutionizing medical diagnostics, or identifying crises in news articles.
Approach: They propose to distill compact, parameter-efficient tailored language models from LLMs for domain-specific tasks with comparable performance.
Outcome: The proposed framework outperforms knowledge distillation frameworks in the crisis domain, where labeled data is scarce.

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