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Litian Zhang

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#natural language process... Preprint Sep 2026

When Updating Stops Being Learning: Rethinking LLM Self-Evolution via learnable information gain

A holistic framework based on learnable information gain, which measures how much novel, parameterizable information a round provides relative to the previous round, and proposes ATRI (Adaptive Training Regulation via Information-gain), which reweights samples within a round and halts training across rounds when inform...

Chen-Xu Wang, Chao-Zhuo Li, Xin-Ze Shi et al. · 0 citations
Preprint Aug 2026

Benign Alone, Harmful Together: Exploiting Experience Composition in Self-Evolving LLM Agents

EvoBreak is an experience-conditioned sequential attack that operates through individually benign attack-stage tasks and induced experiences, revealing benign experience composition as a persistent attack surface in self-evolving agents.

Bing-Yu Yan, Xiao-Ming Zhang, Chao-Zhuo Li et al. · 2 citations
#artificial intelligence Preprint Sep 2026

Reasoning through Evolution: Automatic Meta-path Discovery for LLM-based Fake News Detection

Propagation structures provide crucial evidence for fake news detection, yet existing approaches primarily rely on supervised GNN-based models, which require substantial labeled data and exhibit limited generalization. Although large language models (LLMs) exhibit strong reasoning capabilities, directly feeding them ra...

Zi-Yi Zhou, Xiao-Ming Zhang, Hui Pang et al. · 0 citations
Jul 2026

Toward Personalized Differentially Private Learning for Decentralized Local Graphs

PPGNN, a personalized differentially private framework for decentralized graph data, enables user-specific privacy budgets during local perturbation while preserving analytical utility in decentralized graph learning scenarios.

Longzhu He, Peng Tang, Chaozhuo Li et al. · 0 citations

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