Papers by SeungYeop Baik

2 papers
TrapDoc: Deceiving LLM Users by Injecting Imperceptible Phantom Tokens into Documents (2025.findings-emnlp)

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Challenge: a growing number of LLMs have been used to provide reasoning, writing, text-editing capabilities.
Approach: They propose a method to inject imperceptible phantom tokens into LLMs to deceive users . the technique generates outputs that appear plausible to users but are in fact incorrect .
Outcome: a new method injects imperceptible tokens into documents to deceive users . the proposed framework is compared to baselines to show its effectiveness .
CodeComplex: Dataset for Worst-Case Time Complexity Prediction (2025.findings-emnlp)

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Challenge: Reasoning ability of large language models (LLMs) is crucial in complex decision-making tasks.
Approach: They propose to use code time complexity prediction to assess LLMs' reasoning ability.
Outcome: The proposed dataset comprises 4,900 Java codes and an equivalent number of Python codes.

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