Papers by Huangzhao Zhang

2 papers
Generating Fluent Adversarial Examples for Natural Languages (P19-1)

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Challenge: Current methods for building adversarial attackers for NLP are inefficient as the gradient is discarded.
Approach: They propose an adversarial attacker which performs Metropolis-Hastings sampling with the guidance of gradients to solve these problems.
Outcome: The proposed algorithm outperforms the baseline model on attacking capability on IMDB and SNLI.
HiRoPE: Length Extrapolation for Code Models Using Hierarchical Position (2024.acl-long)

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Challenge: Existing LLMs are constrained by their pre-trained context lengths, leading to performance issues . elucidating this limitation, we propose a training-free solution to the context length limitation in LLM applications .
Approach: They propose a method that integrates hierarchical rotary position embedding into LLMs without extra training costs.
Outcome: The proposed method improves performance on language modeling and long code completion tasks.

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