Preconditioned Test-Time Adaptation for Out-of-Distribution Debiasing in Narrative Generation (2026.acl-long)
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| Challenge: | Debiased large language models excel at handling known or low-bias prompts, but fail on unfamiliar and high-biased prompts. |
| Approach: | They propose a debiasing framework that detects high-bias prompts and triggers context-aware LoRA updates only when a bias-risk score exceeds a threshold. |
| Outcome: | The proposed framework reduces toxicity/bias score with significantly lower latency than standard optimization methods. |
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