Papers by Songzhu Mei

2 papers
LLM-based Rumor Detection via Influence Guided Sample Selection and Game-based Perspective Analysis (2025.acl-long)

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Challenge: Existing methods for rumor detection on social media are limited by limited modeling capacity and insufficient training corpora.
Approach: They propose an SFT-based rumor detection model with Influence guided Sample selection and Game-based multi-perspective analysis to address these issues.
Outcome: The proposed model outperforms existing SOTA on three datasets.
Dovetail: A CPU/GPU Heterogeneous Speculative Decoding for LLM inference (2025.emnlp-main)

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Challenge: Large language models (LLMs) are demanding more memory and computational resources . however, these devices typically feature weaker GPUs and stronger CPUs .
Approach: They propose a lossless inference acceleration method that leverages the characteristics of heterogeneous devices and the advantages of speculative decoding.
Outcome: The proposed method achieves speedups ranging from 1.79 to 10.1 across different devices . it uses a draft model on the GPU to perform preliminary predictions, while a target model on CPU validates these outputs .

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