Papers by Yantuan Xian

2 papers
Multilingual Generative Retrieval via Cross-lingual Semantic Compression (2025.findings-emnlp)

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Challenge: Existing methods for multilingual retrieval still face cross-lingual identifier misalignment and identifiere inflation.
Approach: They propose a framework that unifies semantically equivalent multilingual keywords into shared atoms to align semantics and compresses the identifier space.
Outcome: The proposed framework improves cross-lingual alignment and reduces redundancy.
Does Large Language Model Contain Task-Specific Neurons? (2024.emnlp-main)

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Challenge: Large language models (LLMs) have demonstrated remarkable capabilities in comprehensively handling various types of natural language processing (NLP) tasks.
Approach: They propose a method for task-specific neuron localization based on Causal Gradient Variation with Special Tokens (CGVST) this method identifies task- specific neurons by concentrating on the most significant tokens during task processing, eliminating redundant tokens and minimizing interference from non-essential neurons.
Outcome: The proposed method can locate task-specific neurons across eight public tasks.

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