wangkevin02
/

USP

@@ -13,12 +13,11 @@ base_model:
 Our User Simulator with Implicit Profiles (USP) replicates human-like conversational behavior in interactions with large language models (LLMs). By emulating diverse user dynamics based on predefined profiles, it reconstructs realistic user-LLM dialogues, leveraging the LLaMA-3-base-8B architecture with **Conditional Supervised Fine-Tuning (SFT)** and **Reinforcement Learning with Cycle Consistency (RLCC)**.  For a detailed methodology and insights, refer to [Our Paper](#).
-## Constraints
-1. **Maximum Context Length**: Supports up to **4,096 tokens**. Exceeding this may degrade performance; keep inputs within this limit for best results.
-1. **Language Limitation**: Optimized for English. Non-English performance may vary due to limited training data.
 ## Sample Implementation

 Our User Simulator with Implicit Profiles (USP) replicates human-like conversational behavior in interactions with large language models (LLMs). By emulating diverse user dynamics based on predefined profiles, it reconstructs realistic user-LLM dialogues, leveraging the LLaMA-3-base-8B architecture with **Conditional Supervised Fine-Tuning (SFT)** and **Reinforcement Learning with Cycle Consistency (RLCC)**.  For a detailed methodology and insights, refer to [Our Paper](#).
+> *Note*: Our model is subject to the following constraints:
+>
+> 1. **Maximum Context Length**: Supports up to **4,096 tokens**. Exceeding this may degrade performance; keep inputs within this limit for best results.
+>
+> 1. **Language Limitation**: Optimized for English. Non-English performance may vary due to limited training data.
 ## Sample Implementation