CLAUSE: Agentic Neuro-Symbolic Knowledge Graph Reasoning via Dynamic Learnable Context Engineering CLAUSE: Agentic Neuro-Symbolic Knowledge Graph Reasoning via Dynamic Learnable Context EngineeringICLR ProceedingsYang Zhao, Chengxiao Dai, Wei Zhuo, Yue Xiu, Dusit Niyato Keywords * Agentic Resource-Aware KG Reasoning * Budget-aware Dynamic Context Engineering * Constrained Multi-Agent RL * 지식그래프를
Graph to Frame RAG: Visual-Space Knowledge Fusion for Training-Free and Auditable Video Reasoning Graph-to-Frame RAG: Visual-Space Knowledge Fusion for Training-Free and Auditable Video ReasoningWhen video reasoning requires external knowledge, many systems with large multimodal models (LMMs) adopt retrieval augmentation to supply the missing context.
From Agent Loops to Structured Graphs: A Scheduler-Theoretic Framework for LLM Agent Execution From Agent Loops to Structured Graphs:A Scheduler-Theoretic Framework for LLM Agent ExecutionThe dominant paradigm for building LLM based agents is the Agent Loop, an iterative cycle where a single language model decides what to
Graph Interview 소식 Graph Interview - 10th - Tobias Rebert - · LumaDifferentiate from LPG: RDF’s Real PowerLPG 대비 RDF가 가지는 결정적인 차별점과, 추상적인 온톨로지를 실제 데이터 레이어에서 강력하게 구현해내는 RDF만의 파워 Great Modeling for RDF (Migration from Knowledge…Yitae Jeong * 오는 8월 25일(화) 오후 8시–10시, 저희 GUG에서 진행하는 Graph Interview
Is GraphRAG Needed? From Basic RAG to Graph-/Agentic Solutions with Context Optimization Is GraphRAG Needed? From Basic RAG to Graph-/Agentic Solutions with Context OptimizationLong Chen, Ryan Razkenari, Yuxuan Zhou, Yuan Tian, Rahul Ghosh, Venkatesh Pappakrishnan, Disha Ahuja, Vidya Sagar Ravipati. Proceedings of the Fifth Workshop on Generation, Evaluation
Use Graph When It Needs: Efficiently and Adaptively Integrating Retrieval-Augmented Generation with Graphs Use Graph When It Needs: Efficiently and Adaptively Integrating Retrieval-Augmented Generation with GraphsLarge language models (LLMs) often struggle with knowledge-intensive tasks due to hallucinations and outdated parametric knowledge. While Retrieval-Augmented Generation (RAG) addresses
GUG 커뮤니티의 반가운 소식 * 오랜만에 인사드립니다 ! 다시 오마카세를 찾아주신 분들도, 이번에 처음 오신 분들도 모두 반갑습니다. 한국도 무더위가 이어지고 있다고 들었는데, 모두 건강하게 잘 지내고 계셨나요? * 최근 저희 GUG(Graph User Group)에 정말 반가운 소식이 있어서 전해드리고자 합니다. GUG가 2026 오픈소스 AI·SW 커뮤니티 지원사업에 선정되었습니다. 7월 25일(토요일)
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Topological Neural Operator Topological Neural OperatorsWe introduce Topological Neural Operators (TNOs), a principled framework for operator learning on cell complexes that lifts neural operators (NOs) from functions on points and/or edges to topological domains. TNOs represent data as features defined on cells of varying dimension and model their interactions
AI Must Embrace Specialization via Superhuman Adaptable Intelligence AI Must Embrace Specialization via Superhuman Adaptable IntelligenceEveryone from AI executives and researchers to doomsayers, politicians, and activists is talking about Artificial General Intelligence (AGI). Yet, they often don’t seem to agree on its exact definition. One common definition of AGI