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Bingjing Xu

2 accepted papers

2026

SegMem-RAG: Adaptive Memory for Retrieval-Augmented Generation in Open-Ended Knowledge Environments

AAAI 2026technical

Retrieval-Augmented Generation (RAG) improves the factual accuracy of large language models by grounding responses in external content. However, most RAG systems assume access to static and well-organized corpora with fixed retrieval logic. In practice, real-world sources are heterogeneous and unlab

Cited by 0SourcePDFScholar
2025

ICL-Bandit: Relevance Labeling in Advertisement Recommendation Systems via LLM

EMNLP 2025

Measuring the relevance between user queries and advertisements is a critical task for advertisement (ad) recommendation systems, such as Microsoft Bing Ads and Google Ads. Traditionally, this requires expert data labeling, which is both costly and time-consuming. Recent advances have explored using

Cited by 0SourcePDFScholar