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Found 3 papers, 2 papers with code
A Survey of Confidence Estimation and Calibration in Large Language Models
Assessing their confidence and calibrating them across different tasks can help mitigate risks and enable LLMs to produce better generations.
Self-training Improves Pre-training for Few-shot Learning in Task-oriented Dialog Systems
In this paper, we devise a self-training approach to utilize the abundant unlabeled dialog data to further improve state-of-the-art pre-trained models in few-shot learning scenarios for ToD systems.
SLIM: Explicit Slot-Intent Mapping with BERT for Joint Multi-Intent Detection and Slot Filling
Utterance-level intent detection and token-level slot filling are two key tasks for natural language understanding (NLU) in task-oriented systems.
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