CalibDCD is proposed, a broadly applicable calibration framework for feature-based DCD methods, comprising Multi-View Shift Detection, which identifies recurring feature shifts associated with post-training, and Bounded Feature Correction, which selectively mitigates their influence on membership prediction.
Zhen Yang, Mengqi Wang, Gengda Zhao et al.· 0 citations
EvoSQL is presented, a co-evolution framework that formulates SQL synthesis as an iterative interaction between a generator and a critic and maintains a contextualized candidate memory, verifies SQL candidates with both execution signals and LLM-based critique, and updates its memory through utility-guided aggregation.
SymCA is an LLM-empowered interpretable CA framework that materializes column annotation as a global-to-local symbolic decision process and is accurate, robust, and interpretable.
Mengqi Wang, Jianwei Wang, Qing Liu et al.· arXiv.org· 0 citations
LUCID, an LLM-guided, interpretable, training-free, and unsupervised community detection method, designed as a four-stage pipeline that achieves state-of-the-art performance and consistently outperforms leading unsupervised and semi-supervised baselines.
Aoting Zeng, Kai Wang, Jianwei Wang et al.· 0 citations
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