Papers by Junsheng Huang

1 papers
MAC-Tuning: LLM Multi-Compositional Problem Reasoning with Enhanced Knowledge Boundary Awareness (2025.emnlp-main)

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Challenge: Large language models produce non-existing facts when faced with questions outside their parametric knowledge, which undermines their reliability.
Approach: They propose a method that separates the learning of answer prediction and confidence estimation during fine-tuning on instruction data.
Outcome: Experiments on multiple models and different model sizes show that the proposed method outperforms baselines by up to 25% in average precision.

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