Papers with Multi-label Learning
ICXML: An In-Context Learning Framework for Zero-Shot Extreme Multi-Label Classification (2024.findings-naacl)
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| Challenge: | Existing research has focused on fully supervised XMC, but real-world scenarios often lack supervision signals, highlighting the importance of zero-shot settings. |
| Approach: | They propose a framework that generates a set of candidate labels through in-context learning and then reranks them. |
| Outcome: | The proposed framework advances state-of-the-art on two diverse public benchmarks. |