Papers by Dianqing Liu

2 papers
Exploring the Capability Boundaries of LLMs in Mastering of Chinese Chouxiang Language (2026.findings-acl)

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Challenge: Current state-of-the-art LLMs exhibit clear limitations on multiple tasks, while performing well on tasks that involve contextual semantic understanding.
Approach: They propose a mouse-based benchmark to evaluate LLMs' performance on NLP tasks involving Chouxiang Language.
Outcome: The proposed benchmark evaluates the performance of LLMs on six NLP tasks involving Chouxiang Language.
Mitigating Biases in Language Models via Bias Unlearning (2025.emnlp-main)

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Challenge: Recent debiasing approaches target different demographic groups, harming fairness and discrimination.
Approach: They propose a model debiasing framework which targets stereotypes by unlearning stereotype forgetting and anti-stereotype retention.
Outcome: The proposed framework outperforms existing methods in mitigating bias while retaining language modeling capabilities.

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