Papers by Zheyu Lin

3 papers
mPLM-Sim: Better Cross-Lingual Similarity and Transfer in Multilingual Pretrained Language Models (2024.findings-eacl)

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Challenge: Recent multilingual pretrained language models encode strong language-specific signals, which are not explicitly provided during pretraining.
Approach: They propose a language similarity measure that induces similarities across languages from mPLMs using multi-parallel corpora.
Outcome: The proposed measure exhibits moderately high correlations with linguistic similarity measures, and more accurate similarity results on low correlation languages.
DetectBench: Can Large Language Model Detect and Piece Together Implicit Evidence? (2024.findings-emnlp)

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Challenge: Existing LLMs' abilities to detect evidence in long contexts are far inferior to humans.
Approach: They propose a benchmark to assess LLMs' abilities in evidence and multi-step commonsense reasoning within a long context.
Outcome: The proposed method improves the performance of LLMs in evidence detection and commonsense reasoning.
N-GLARE: An Non-Generative Latent Representation-Efficient LLM Safety Evaluator (2026.acl-long)

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Challenge: Evaluating the safety robustness of LLMs is critical for their deployment.
Approach: They propose to use latent representations to characterize hidden layer dynamics by analyzing the APT of latent models and introducing the JSS metric.
Outcome: The proposed method exploits the APT (Angular-Probabilistic Trajectory) of latent representations and introduces the JSS (Jensen-Shannon Separability) metric.

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