Papers by Kaike Zhang

2 papers
RubricHub: A Comprehensive and Highly Discriminative Rubric Dataset via Automated Coarse-to-Fine Generation (2026.acl-long)

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Challenge: Existing methods for generating open-ended rubrics suffer from scalability bottlenecks and coarse criteria resulting in a supervision ceiling effect.
Approach: They propose a framework for automated Coarse-to-Fine Rubric Generation . their framework uses principle-guided synthesis, multi-model aggregation, difficulty evolution .
Outcome: The proposed framework produces comprehensive and highly discriminative criteria capable of capturing the subtle nuances.
PKAD: Pretrained Knowledge is All You Need to Detect and Mitigate Textual Backdoor Attacks (2024.findings-emnlp)

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Challenge: Current defense methods can be classified into inference-time and training-time ones based on their execution phase.
Approach: They propose a two-stage poison detection strategy using pre-trained language models to detect poisoned samples before model training.
Outcome: The proposed method achieves better performance than current methods more quickly and with fewer training costs.

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