Dancing in Chains: Reconciling Instruction Following and Faithfulness in Language Models (2024.emnlp-main)
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Zhengxuan Wu, Yuhao Zhang, Peng Qi, Yumo Xu, Rujun Han, Yian Zhang, Jifan Chen, Bonan Min, Zhiheng Huang
| Challenge: | Modern language models fail to follow human instructions while being faithful . a trade-off exists between instruction following and faithfulness when training LMs . |
| Approach: | They propose a method that relies on Reject-sampling by Self-instruct with Continued Fine-tuning to train LMs to follow human instructions while being faithful. |
| Outcome: | The proposed method outperforms vanilla MTL with high-quality data, but with significantly smaller data. |
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| Challenge: | et al., 2023) proposes a method to improve instruction-tuning data . e.g., we generate synthetic instructions using the backtranslation approach . |
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ReasonIF: Large Reasoning Models Fail to Follow Instructions During Reasoning (2026.findings-acl)
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| Challenge: | Prior studies assess instruction adherence in the model’s main responses, but it is also critical for large reasoning models to follow user instructions throughout their reasoning process. |
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