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20222026
most citedLLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities

37 citations · 85 across the 38 of their papers we have counts for

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6 papers · 1 filter

cs.AI2026

Mechanist: AI as a Scientific Instrument for Discovering the Mechanisms of Intelligence

Mengru Wang, Junfeng Fang, Shuofei Qiao +17

AI models are increasingly used in scientific discovery and human decision-making. Yet how AI models work and what risks they pose remain poorly understood. As AI development becom…

cs.AI2026

MobileMem: Learning from a Year of Mobile Experiences

Xinle Deng, Yida Xue, Xiangyuan Ru +16

The next generation of AI agents is increasingly moving beyond systems that answer isolated questions toward persistent personal assistants that can understand, remember, and conti…

cs.AI2026

Unsupervised Skill Discovery for Agentic Data Analysis

Zhisong Qiu, Kangqi Song, Shengwei Tang +4

Inference-time skill augmentation provides a lightweight way to improve data-analytic agents by injecting reusable procedural knowledge without updating model parameters. However,…

cs.AI2026

SciAtlas: A Computable Atlas of Science for Knowledge-Grounded AI Research

Shuofei Qiao, Yunxiang Wei, Busheng Zhang +16

Artificial intelligence is rapidly entering the core workflows of scientific research. Yet reliable scientific reasoning requires access to accumulated scientific knowledge with su…

cs.AI2026★ 1 cited

SkillNet: Create, Evaluate, and Connect AI Skills

Yuan Liang, Ruobin Zhong, Haoming Xu +47

Current AI agents can flexibly invoke tools and execute complex tasks, yet their long-term advancement is hindered by the lack of systematic accumulation and transfer of skills. Wi…

cs.AI2025

KnowRL: Exploring Knowledgeable Reinforcement Learning for Factuality

Baochang Ren, Shuofei Qiao, Da Zheng +2

Large Language Models (LLMs), particularly slow-thinking models, often exhibit severe hallucination, outputting incorrect content due to an inability to accurately recognize knowle…