arXiv (All)
open access
AuthorMix: Modular Authorship Style Transfer via Layer-wise Adapter Mixing
The task of authorship style transfer involves rewriting text in the style of a target author while preserving the meaning of the original text. Existing style transfer methods train a single model on large corpora to model all target styles at once: this high-cost approach offers limited flexibilit
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Forging LLM Authorship Fingerprints with Targeted Rewriting#1143432
- CLeaR: A Unified Framework for Resolving the Leakage-Degradation Dilemma in Style Transfer#1142431
- Reason in Style: Discovering and Controlling Style in Language Models#1155659
- SongCraft: Unified Song Generation and Editing with Reconstructive Learning#1110680
- FAVoR: Measuring and Mitigating Author-Style Homogenization in Federated Personalized Generation#1105527
Record · ID 1012164
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive