Looped Transformers repeatedly apply the same set of Transformer layers, giving them a recurrent architecture for latent computation. Their strong performance on iterative reasoning and length-generalization tasks suggests an appealing explanation: recurrence may provide an inductive bias that lets the model reuse a le...
ContinualSkillBench is introduced, a dynamic evaluation framework for in-context continual skill learning that shows that current in-context skill evolution mechanisms can support continual adaptation, but still struggle to consistently consolidate experience into robust and transferable skills.
Tianyi Guan, Yiding Wang, Haotong Yang et al.· 2 citations
GABench is introduced, a comprehensive benchmark for agentic graph analysis that covers four graph analysis task categories: graph retrieval, graph theory, graph machine learning, and graph open-ended question answering and provides practical insights into the development and evaluation of LLM agents for graph analysis...
Jiarui Tan, Zhong-Jian Zhang, Yabo Guo et al.· 2 citations
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