Papers by Hanzi Xu

2 papers
Robustness of Learning from Task Instructions (2023.findings-acl)

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Challenge: traditional supervised learning mostly works on individual tasks and requires training on a large set of task-specific examples.
Approach: a new study investigates the system robustness when instructions are manipulated and paraphrased . task instructions give the model the definition of the task and allow it to output the appropriate answer .
Outcome: a new study shows that supervised learning is robust when instructions are manipulated, paraphrased or iii from different levels of conciseness.
X-Shot: A Unified System to Handle Frequent, Few-shot and Zero-shot Learning Simultaneously in Classification (2024.findings-acl)

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Challenge: Recent studies have focused on few-shot and zero-shot learning, but label occurrences vary widely . authors propose a new classification challenge that can be used to manage labels across the full frequency spectrum .
Approach: They propose a new classification challenge that allows for label co-occurrences without predefined limits.
Outcome: The proposed system can handle freq-shot, few-shot and zero-shot labels without limits.

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