Papers by Fabian Karl

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Challenge:	State-of-the-art approaches rely on complex components like graph encoders, label semantics, and autoregressive decoders.
Approach:	They propose a multi-head encoder-only architecture for hierarchical text classification that treats each level as a separate classification task with its own label space.
Outcome:	The proposed architecture matches or exceeds state-of-the-art methods on four benchmarks.