3 papers
cs.AI2026
Mitigating Hallucination in Financial Retrieval-Augmented Generation via Fine-Grained Knowledge Verification
Taoye Yin, Haoyuan Hu, Yaxin Fan +5
In financial Retrieval-Augmented Generation (RAG) systems, models frequently rely on retrieved documents to generate accurate responses due to the time-sensitive nature of the fina…
cs.CL2025
Layout-Aware Parsing Meets Efficient LLMs: A Unified, Scalable Framework for Resume Information Extraction and Evaluation
Fanwei Zhu, Jinke Yu, Zulong Chen +6
Automated resume information extraction is critical for scaling talent acquisition, yet its real-world deployment faces three major challenges: the extreme heterogeneity of resume…
cs.LG2025
Auto-Rubric: Learning From Implicit Weights to Explicit Rubrics for Reward Modeling
Lipeng Xie, Sen Huang, Zhuo Zhang +9
Conventional reward modeling relies on gradient descent over neural weights, creating opaque, data-hungry "black boxes." We propose a paradigm shift from implicit to explicit rewar…