Papers by Zixuan Xia
MDR: Model-Specific Demonstration Retrieval at Inference Time for In-Context Learning (2024.naacl-long)
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| Challenge: | Existing methods for retrieval-based in-context learning ignore model biases and fail to retrieve the most appropriate demonstrations for different LLMs. |
| Approach: | They propose a model-specific demonstration retrieval method that considers the biases of different LLMs at inference time. |
| Outcome: | The proposed method improves performance on seen and unseen tasks with multi-scale inference LLMs by up to 41.2%. |
SSS: Editing Factual Knowledge in Language Models towards Semantic Sparse Space (2024.findings-acl)
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| Challenge: | Existing methods to modify LMs suffer from sub-optimal locality, where irrelevant neighborhood examples can be adversely influenced. |
| Approach: | They propose to use a model editing method to modify specific examples in LMs to improve locality and reasoning capability by directing the hidden state of edit example towards spaces where semantics are sparse. |
| Outcome: | The proposed method improves locality and reasoning capability on two datasets. |
The Threat of PROMPTS in Large Language Models: A System and User Prompt Perspective (2025.findings-acl)
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| Challenge: | Prompts are essential for guiding model output and influencing content generation. |
| Approach: | They propose to attack models with prompt leakage and prompt jailbreak attacks . they summarize the experimental setups of these methods and explore the relationship between prompt threats and prompt injection attacks. |
| Outcome: | The proposed methods summarize the experimental setups and examine the relationship between prompt threats and prompt injection attacks. |