Salvato in:
| Autore principale: | |
|---|---|
| Natura: | Preprint |
| Pubblicazione: |
2025
|
| Soggetti: | |
| Accesso online: | https://arxiv.org/abs/2510.23650 |
| Tags: |
Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
|
| _version_ | 1866915580111486976 |
|---|---|
| author | Xia, Wei |
| author_facet | Xia, Wei |
| contents | We proposed Static and Dynamic -- two zero-shot logits-layer debiasing methods. Dynamic reduces bias by up to 70% with minimal fluency loss. Logits intervention outperforms hidden-layer approaches. We show semantic-aware logits intervention is stable and effective for debiasing aligned LLMs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_23650 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Beyond Hidden-Layer Manipulation: Semantically-Aware Logit Interventions for Debiasing LLMs Xia, Wei Machine Learning Artificial Intelligence We proposed Static and Dynamic -- two zero-shot logits-layer debiasing methods. Dynamic reduces bias by up to 70% with minimal fluency loss. Logits intervention outperforms hidden-layer approaches. We show semantic-aware logits intervention is stable and effective for debiasing aligned LLMs. |
| title | Beyond Hidden-Layer Manipulation: Semantically-Aware Logit Interventions for Debiasing LLMs |
| topic | Machine Learning Artificial Intelligence |
| url | https://arxiv.org/abs/2510.23650 |