Text-Attributed Graphs (TAGs) are prevalent in various real-world scenarios, where each node is associated with a text attribute. Representation learning on TAGs relies on a comprehensive understanding of both the textual attributes and the topological connections. Recent works have enhanced graph neural networks (GNNs...
Hao Yan, Chao-Zhuo Li, Jun Yin et al.· ACM Transactions on Intellig...· 0 citations
Results show that long-horizon reflective data is an effective route toward self-improving agents, and synthesize long-horizon improvement trajectories from machine learning and algorithmic programming tasks, two domains that offer verifiable feedback and reward sustained iteration.
Hong-Jin Qian, Chao-Fan Li, Kun Luo et al.· 0 citations
Memory is critical for AI agents. Many existing agent-memory systems follow an Ahead-of-Time (AOT) design, constructing memory before a specific request arrives. While this reduces online serving cost, such request-agnostic memory construction can discard fine-grained information that later becomes important. To addres...
Bing-Yu Yan, Chao-Fan Li, Hong-Jin Qian et al.· 0 citations
The results show that LLMs continue to struggle with the cross-lingual understanding of Chinese internet buzzwords, particularly in fine-grained non-literal interpretation, robust equivalent matching under option perturbations, and calibrated harmfulness detection, which highlights the persistent challenges posed by cu...
Yi-Fan Wang, Jun-Yu Lu, Qi-Fan Wang et al.· 0 citations
TFM4POP is the first framework to introduce tabular foundation models (TFMs) into popularity prediction, leveraging their pre-trained tabular priors to unify the modeling of multiple heterogeneous information views and constructs a comprehensive multi-view cascade benchmark that covers all four information views.
Wenting Zhu, Chenghua Gong, Sanchuan Guo et al.· 0 citations
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
This work introduces Audio-Zero, the first label-free self-evolution framework in the field of LALMs that improves fine-grained auditory perception and reasoning and reveals that increasingly fine-grained auditory descriptions emerge naturally from game pressure.
Siqian Tong, Xuan Li, Chao-Zhuo Li et al.· arXiv.org· 1 citation
DisCo is presented, a skill-powered research agent that creates skills and uses them during research, and yields the AREX-Skill Library, with 5,000+ verified skills distilled from 1,000 widely used ML repositories and organized into 20 areas and 178 capability families.
Jianlyu Chen, Yuyang Hu, Hong-Jin Qian et al.· 1 citation
This work introduces AREX, a family of Recursively Self-Improving (RSI) deep research agents that substantially outperforms comparable-scale baselines and remains competitive with models using substantially more activated parameters.
Shuqi Lu, Chaofan Li, Kun Luo et al.· arXiv.org· 2 citations· ⚡1
A systematic evaluation of privacy risks in LLM-enhanced GNNs through a unified framework consisting of five stages and reveals that semantic enrichment amplifies link-, label-, and membership-related signals in the embedding space, making them more exploitable by inference attacks.
Long-Zhu He, Ze-Kun Wen, Chao-Zhuo Li et al.· 0 citations
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.· IEEE Transactions on Knowled...· 0 citations
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