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cs.AI2026
AERA: Adaptive Evidence Residual Allocation for Efficient Test-Time Reasoning
Ziming Wang, Ivor Tsang, Hangwei Qian
Test-time scaling improves language-model reasoning by generating additional candidate solutions, but allocating the same inference budget to every problem is computationally waste…
cs.AI2026
BadSKP: Backdoor Attacks on Knowledge Graph-Enhanced LLMs with Soft Prompts
Xiaoting Lyu, Yufei Han, Hangwei Qian +6
Recent knowledge graph (KG)-enhanced large language models (LLMs) move beyond purely textual knowledge augmentation by encoding retrieved subgraphs into continuous soft prompts via…
cs.AI2026
SCOUT-RAG: Scalable and Cost-Efficient Unifying Traversal for Agentic Graph-RAG over Distributed Domains
Longkun Li, Yuanben Zou, Jinghan Wu +4
Graph-RAG improves LLM reasoning using structured knowledge, yet conventional designs rely on a centralized knowledge graph. In distributed and access-restricted settings (e.g., ho…