Papers with conflict data

1 papers
KaFT: Knowledge-aware Fine-tuning for Boosting LLMs’ Domain-specific Question-Answering Performance (2025.findings-acl)

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Challenge: Recent literature reveals that supervised fine-tuning (SFT) is suboptimal for domain-specific question-answering tasks.
Approach: They propose a query diversification strategy for robust conflict detection and a knowledge-aware fine-tuning approach to effectively boost LLMs’ performance.
Outcome: The proposed approach improves the model generalization and alleviates the hallucination.

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