Papers by Xinru Wang

3 papers
HiCoLoRA: Addressing Context-Prompt Misalignment via Hierarchical Collaborative LoRA for Zero-Shot DST (2026.findings-acl)

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Challenge: Existing approaches to zero-shot Dialog State Tracking (zs-DST) are inadequate to generalize to new domains without extensive training.
Approach: They propose a framework that enhances zero-shot slot inference through robust prompt alignment.
Outcome: Experiments on multi-domain datasets show that HiCoLoRA outperforms baselines, achieving SOTA in zs-DST.
DarwinTOD: LLM-Driven Lifelong Self-evolution for Task-oriented Dialog Systems (2026.acl-long)

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Challenge: Continual learning approaches fail to achieve autonomy lifelong improvement in dynamic environments . current task-oriented dialog systems are static, unable to learn from ongoing interactions .
Approach: They propose a lifelong self-evolving dialog framework that integrates evolutionary computation and LLM driven self-improvement into a single framework.
Outcome: The proposed framework surpasses state-of-the-art methods and exhibits continuous performance gains throughout evolution.
DyBBT: Dynamic Balance via Bandit-inspired Targeting for Dialog Policy with Cognitive Dual Systems (2026.acl-long)

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Challenge: Task oriented dialog systems often rely on static exploration strategies that do not adapt to dynamic dialog contexts.
Approach: They propose a dialog policy learning framework that formalizes the exploration challenge through a structured cognitive state space C.
Outcome: The proposed framework achieves SOTA performance in success rate, efficiency, and generalization.

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