Papers by Jens Albrecht
Transition-Matrix Regularization for Next Dialogue Act Prediction in Counselling Conversations (2026.findings-acl)
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| Challenge: | Evaluated on a 60-class German counselling taxonomy, this improves macro-F1 by 9–42% relative depending on encoder and corpus-derived transition patterns. |
| Approach: | They propose to use a KL regularization term to align next dialogue act distributions with corpus-derived transition patterns to improve macro-F1 by 9–42% relative to encoders. |
| Outcome: | The proposed term improves macro-F1 by 9–42% relative to encoders and significantly improves dialogue-flow alignment. |