Papers by Jiajian Guo
ProactiveEval: A Unified Evaluation Framework for Proactive Dialogue Agents (2026.acl-long)
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| Challenge: | Existing studies on proactive dialogue models focus on domain-specific or task-oriented scenarios, which leads to fragmented evaluations and limits the comprehensive exploration of models’ proactive dialogue abilities. |
| Approach: | They propose a framework for evaluating proactive dialogue capabilities of large language models that decomposes proactive dialogue into target planning and dialogue guidance, establishing evaluation metrics across various domains. |
| Outcome: | The proposed framework decomposes proactive dialogue into target planning and dialogue guidance, establishing evaluation metrics across various domains, and enables automatic generation of diverse and challenging evaluation data. |
ReAlign: Structured Revision for Small Language Model Alignment (2025.findings-emnlp)
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| Challenge: | weak policies struggle to generate informative on-policy samples and suffer from unstable gradients when trained on off-police signals from stronger models. |
| Approach: | They propose a training framework that combines stability of on-policy learning with reviser-assisted supervision. |
| Outcome: | The proposed training framework outperforms strong preference optimization baselines on AlpacaEval-2 and Arena-Hard. |