9 papers
EHR-Bench: A Chinese Multi-Task Benchmark for Recruitment AI
Ruijia Yang, Bing Xu, Zulong Chen +5
Recruitment applications span diverse operations, from drafting job descriptions and interpreting queries to organizing profiles, assessing fit, and recommending candidates and job…
EntSQL: A Benchmark for Grounding Text-to-SQL in Long-Context Enterprise Knowledge
Chengxi Liao, Tao Xu, Zulong Chen +7
Text-to-SQL enables natural language access to databases, and recent LLMs have substantially advanced its capabilities. Existing benchmarks such as Spider, BIRD, and Spider~2.0 eva…
Ontology Memory-Augmented ASR Correction for Long Text-Speech Interleaved Conversations
Xinxin Li, Huiyao Chen, Meishan Zhang +6
Automatic speech recognition (ASR) correction has traditionally focused on isolated utterances or short local contexts. However, as text and speech become increasingly interleaved…
Enhancing Online Recruitment with Category-Aware MoE and LLM-based Data Augmentation
Minping Chen, Bing Xu, Zulong Chen +4
Person-Job Fit (PJF) is a critical component for online recruitment. Existing approaches face several challenges, particularly in handling low-quality job descriptions and similar…
DOne: Decoupling Structure and Rendering for High-Fidelity Design-to-Code Generation
Xinhao Huang, Jinke Yu, Wenhao Xu +5
While Vision Language Models (VLMs) have shown promise in Design-to-Code generation, they suffer from a "holistic bottleneck-failing to reconcile high-level structural hierarchy wi…
Taxon: Hierarchical Tax Code Prediction with Semantically Aligned LLM Expert Guidance
Jihang Li, Qing Liu, Zulong Chen +4
Tax code prediction is a crucial yet underexplored task in automating invoicing and compliance management for large-scale e-commerce platforms. Each product must be accurately mapp…
Enhancing Talent Search Ranking with Role-Aware Expert Mixtures and LLM-based Fine-Grained Job Descriptions
Jihang Li, Bing Xu, Zulong Chen +5
Talent search is a cornerstone of modern recruitment systems, yet existing approaches often struggle to capture nuanced job-specific preferences, model recruiter behavior at a fine…
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…
SEAL: Structure and Element Aware Learning to Improve Long Structured Document Retrieval
Xinhao Huang, Zhibo Ren, Yipeng Yu +3
In long structured document retrieval, existing methods typically fine-tune pre-trained language models (PLMs) using contrastive learning on datasets lacking explicit structural in…