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Showing 2026 · cs.CLShow all
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cs.CL2026
Beyond Semantic Relevance: Counterfactual Risk Minimization for Robust Retrieval-Augmented Generation
Peiyang Liu, Qiang Yan, Ziqiang Cui +3
Standard Retrieval-Augmented Generation (RAG) systems predominantly rely on semantic relevance as a proxy for utility. However, this assumption collapses in realistic decision-maki…
cs.CL2026
Embedding Enhancement via Fine-Tuned Language Models for Learner-Item Cognitive Modeling
Yuanhao Liu, Zihan Zhou, Kaiying Wu +5
Learner-item cognitive modeling plays a central role in the web-based online intelligent education system by enabling cognitive diagnosis (CD) across diverse online educational sce…
cs.CL2026★ 1 cited
LLM-Confidence Reranker: A Training-Free Approach for Enhancing Retrieval-Augmented Generation Systems
Zhipeng Song, Xiangyu Kong, Xinrui Bao +5
Large language models (LLMs) have revolutionized natural language processing, yet hallucinations in knowledge-intensive tasks remain a critical challenge. Retrieval-augmented gener…