Papers by Xiaoyang Ye
Agentic Economic Modeling (2026.acl-industry)
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| Challenge: | AEM is a framework that aligns synthetic LLM choices with small-sample human evidence for reliable econometric inference. |
| Approach: | They introduce a framework that aligns synthetic LLM choices with small-sample human evidence for reliable econometric inference. |
| Outcome: | The proposed framework improves RCT efficiency and establishes a foundation method for LLM-based counterfactual generation. |
RISER: Orchestrating Latent Reasoning Skills for Adaptive Activation Steering (2026.findings-acl)
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| Challenge: | Existing methods for domain-specific reasoning with large language models require updating parameter updates. |
| Approach: | They propose a plug-and-play intervention framework that adaptively steers LLM reasoning in activation space. |
| Outcome: | The proposed framework achieves zero-shot accuracy improvements of 3.4–6.5% over the base model while outperforming chain-of-thought-style reasoning with 2–3 higher token efficiency and robust accuracy gains. |