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cs.CL2026

DynaKRAG: A Unified Framework for Learnable Evidence Control in Multi-Hop Retrieval-Augmented Generation

Yaqi Wu, Xiaolei Guo, Chenyu Zhou +7

Multi-hop retrieval-augmented generation (RAG) acquires evidence sequentially, with each document contributing supporting facts, bridge entities, query refinements, or sufficient e…

cs.CL2026

LatentSkill: From In-Context Textual Skills to In-Weight Latent Skills for LLM Agents

Aofan Yu, Chenyu Zhou, Tianyi Xu +8

Agent systems increasingly use textual skills to encode reusable task procedures, but injecting these skills into the prompt at every step incurs substantial context overhead and e…

cs.CL2026

Skills on the Fly: Test-Time Adaptive Skill Synthesis for LLM Agents

Jingxing Wang, Chenyu Zhou, Zhihui Fu +4

Additional test-time compute can give LLM agents access to more past experience, yet expanding the context or adding rollouts does not necessarily yield greater agent capability. W…

cs.CL2026

TextMineX: Data, Evaluation Framework and Ontology-guided LLM Pipeline for Humanitarian Mine Action

Chenyue Zhou, Gürkan Solmaz, Flavio Cirillo +2

Humanitarian Mine Action (HMA) addresses the challenge of detecting and removing landmines from conflict regions. Much of the life-saving operational knowledge produced by HMA agen…

cs.CL2024

Plausible-Parrots @ MSP2023: Enhancing Semantic Plausibility Modeling using Entity and Event Knowledge

Chong Shen, Chenyue Zhou

In this work, we investigate the effectiveness of injecting external knowledge to a large language model (LLM) to identify semantic plausibility of simple events. Specifically, we…