Author

Hermann Ney

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#machine learning Preprint Sep 2026

Fine-Tuning LLMs for Translation: General Forgetting Mitigation Does Not Preserve MT-Specific Instruction Following

Elastic Weight Consolidation preserves general capabilities best in both stages; on the 8B Spanish model the average score on general benchmarks drops 1.7 points versus 11.0 for standard fine-tuning, yet its scores for formality and grammatical gender control remain close to standard fine-tuning.

Niklas Scholz, David Thulke, Abdallah Nasir et al. · 0 citations

#artificial intelligence Preprint Aug 2026

Stick to What You Know: A Study of Knowledge-Aligned Supervised Fine-Tuning

Experiments show that knowledge-aligned SFT can reduce factual hallucinations on WildHalu and Biography while largely preserving general capabilities and confirm that SFT targets beyond the base model's knowledge drive hallucination behavior.

AR Becker, Jakob Kemmler, David Thulke et al. · 0 citations