7 papers
Pointer-Augmented Autoregressive Generation of Patent Claims with Joint Topology and Content Decoding
Yongmin Yoo, Zhangkai Wu, Longbing Cao
Autoregressive decoders emit flat token sequences and cannot enforce hierarchical constraints across output segments, a limitation that becomes acute in patent claim generation, wh…
Heterogeneous Dependency Graph-Guided Attentionfor Patent Representation Learning
Yongmin Yoo, Qiongkai Xu, Zhangkai Wu +1
Pre-trained language models advance patent classification and retrieval via encoding claims as flat token sequences, yet overlooking the dependency hierarchy among claims. Incorpor…
Adaptive Cost-Efficient Evaluation for Reliable Patent Claim Generation
Yongmin Yoo, Qiongkai Xu, Longbing Cao
Automated patent claim validation demands low error tolerance. However, existing approaches face a rigidity-resource dilemma: lightweight encoders cannot track long-range legal dep…
Self-Filtered Distillation with LLMs-generated Trust Indicators for Reliable Patent Classification
Yongmin Yoo, Xu Zhang, Longbing Cao
Organizing large-scale patent corpora according to classification schemes is a core information management task that determines the accuracy and efficiency of prior art retrieval,…
Beyond ESG Scores: Learning Dynamic Constraints for Sequential Portfolio Optimization
Xin Li, Yan Ke, Longbing Cao
ESG-aware portfolio optimization is increasingly important for sustainable capital allocation, yet most learning-based methods still operationalize ESG by appending static scores t…
PatentMind: A Multi-Aspect Reasoning Graph for Patent Similarity Evaluation
Yongmin Yoo, Qiongkai Xu, Longbing Cao
Patent similarity evaluation plays a critical role in intellectual property analysis. However, existing methods often overlook the intricate structure of patent documents, which in…