6 citations · 8 across the 8 of their papers we have counts for
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cs.IR2026
TA-Mem: Tool-Augmented Autonomous Memory Retrieval for LLM in Long-Term Conversational QA
Mengwei Yuan, Jianan Liu, Jing Yang +4
Large Language Model (LLM) has exhibited strong reasoning ability in text-based contexts across various domains, yet the limitation of context window poses challenges for the model…
cs.IR2026
Tiny-Critic RAG: Empowering Agentic Fallback with Parameter-Efficient Small Language Models
Yichao Wu, Penghao Liang, Yafei Xiang +5
Retrieval-Augmented Generation (RAG) grounds Large Language Models (LLMs) to mitigate factual hallucinations. Recent paradigms shift from static pipelines to Modular and Agentic RA…
cs.IR2024★ 2 cited
Maximizing User Experience with LLMOps-Driven Personalized Recommendation Systems
Chenxi Shi, Penghao Liang, Yichao Wu +2
The integration of LLMOps into personalized recommendation systems marks a significant advancement in managing LLM-driven applications. This innovation presents both opportunities…