Papers by Hanyu Luo

2 papers
MAGRET: Machine-generated Text Detection with Rewritten Texts (2025.coling-main)

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Challenge: Existing studies focus on detecting machine-generated text in open-source models, but their performance on closed-source large models is limited.
Approach: They propose a method to detect rewritten text from large language models using a BERT encoder and propose to refine it to achieve semantic alignment.
Outcome: The proposed method outperforms baseline methods on three text-generated datasets.
Tandem: Riding Together with Large and Small Language Models for Efficient Reasoning (2026.findings-acl)

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Challenge: Recent advances in large language models (LLMs) have catalyzed the rise of reasoningintensive inference paradigms, where models perform explicit step-by-step reasoning before generating final answers.
Approach: They propose a large-small LLM collaboration framework that synergizes large and small language models to achieve high-quality reasoning with significantly reduced computational cost.
Outcome: The proposed framework outperforms the mentor LLM while preserving the benefits of the thinking paradigm of LLMs.

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