Papers by Gao Zuchen

2 papers
OASIS: Order-Augmented Strategy for Improved Code Search (2025.acl-long)

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Challenge: Code embeddings capture the semantic representations of code and are crucial for various code-related large language model (LLM) applications.
Approach: They propose an order-augmented strategy for improved code search that leverages order-based similarity labels to capture subtle differences in similarity among negative pairs.
Outcome: The proposed model outperforms state-of-the-art models focusing on major positive-negative differences.
CoSafe: Evaluating Large Language Model Safety in Multi-Turn Dialogue Coreference (2024.emnlp-main)

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Challenge: Existing studies have not noticed the safety risks of large language models . authors evaluated 1,400 questions in multi-turn dialogue coreference .
Approach: They are the first to evaluate LLM safety in multi-turn dialogue coreference . they created a dataset of 1,400 questions and tested five open-source models .
Outcome: The study shows that model safety decreases in multi-turn dialogue coreference scenarios . the highest success rate was with the LLaMA2-Chat-7b model, while the lowest was with mistral-7B-Instruct model .

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