GateKD is a confidence-gated closed-loop distillation framework that improves multi-step reasoning transfer from LLMs to smaller models by dynamically filtering supervision based on teacher reliability.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages=
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DuDi is a dual-signal distillation method with cross-lingual verbalizer that improves multilingual SLM performance on SEA languages and outperforms baselines on SEA-HELM.
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GateKD: Confidence-Gated Closed-Loop Distillation for Robust Reasoning
GateKD is a confidence-gated closed-loop distillation framework that improves multi-step reasoning transfer from LLMs to smaller models by dynamically filtering supervision based on teacher reliability.
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DuDi: Dual-Signal Distillation with Cross-Lingual Verbalizer
DuDi is a dual-signal distillation method with cross-lingual verbalizer that improves multilingual SLM performance on SEA languages and outperforms baselines on SEA-HELM.