Papers by Zihui Xu

3 papers
SPIDE: Serial and Parallel Intertwined Speculative Decoding (2026.findings-acl)

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Challenge: Speculative decoding (SD) is a training-free SD framework that orchestrates dynamic alternation combining serial dynamic drafting with parallel draft verification.
Approach: They propose a serial and parallel intertwined speculative DEcoding framework that orchestrates dynamic alternation combining serial dynamic drafting and parallel draft verification.
Outcome: The proposed framework accelerates inference while reducing the LLM usage costs.
SCCD: A Session-based Dataset for Chinese Cyberbullying Detection (2025.coling-main)

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Challenge: Existing work on cyberbullying detection in Chinese is underdeveloped due to the lack of comprehensive and reliable datasets.
Approach: They propose to use Chinese social media sessions to analyze Chinese cyberbullying content to improve the quality of annotations.
Outcome: The proposed dataset shows that it performs better than existing methods on Weibo and a major social media platform.
LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment (2025.emnlp-main)

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Challenge: Recent advances in large language models (LLMs) show promise in simulating complex scenarios.
Approach: They examine multiple LLMs to proactively estimate perceived earthquake impacts using multimodal datasets and multimodal imagery.
Outcome: The framework generates Modified Mercalli Intensity (MMI) predictions at zip code and county scales using multimodal datasets.

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