Papers by Anyi Wang
Improving LLM Reasoning through Interpretable Role-Playing Steering (2025.findings-emnlp)
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| Challenge: | Existing methods for role-playing rely on prompt engineering, which lacks stability and interpretability. |
| Approach: | They propose a framework that extracts latent representations from role-play prompts and constructs a steering vector that can be injected into the model's residual stream with controllable intensity. |
| Outcome: | The proposed framework extracts latent representations from role-play prompts, selects the most relevant features based on activation patterns, and constructs a steering vector that can be injected into the model’s residual stream with controllable intensity. |
What’s the Difference? Supporting Users in Identifying the Effects of Prompt and Model Changes Through Token Patterns (2025.acl-long)
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| Challenge: | Existing evaluation methods for prompting for large language models have limitations such as being labor-intensive or lacking insights. |
| Approach: | They propose a new approach that automatically distinguishes between random variations and systematic differences in language model outputs by using token patterns. |
| Outcome: | The proposed method combines both automation and human analysis to provide new insights into established prompt data. |