Papers by ChanJoo Jung
Personalized LLM Decoding via Contrasting Personal Preference (2025.emnlp-main)
Copied to clipboard
| Challenge: | Personalization of large language models (LLMs) is becoming increasingly important as they are increasingly deployed in real-world applications. |
| Approach: | They propose a decoding-time approach that leverages the user's implicit reward signal by performing parameter-efficient fine-tuning on user-specific data. |
| Outcome: | The proposed approach improves personalization by an average of 10.57% in ROUGE-L without external reward models or additional training procedures. |