Patent Language Model Pretraining with ModernBERT
Paper • 2509.14926 • Published • 1
Patent NLP
A collection of machine learning and natural language processing papers related to the patent domain.
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Fine-Tuning Causal LLMs for Text Classification: Embedding-Based vs. Instruction-Based Approaches
Paper • 2512.12677 • Published • 1 -
PatenTEB: A Comprehensive Benchmark and Model Family for Patent Text Embedding
Paper • 2510.22264 • Published • 2 -
AutoPatent: A Multi-Agent Framework for Automatic Patent Generation
Paper • 2412.09796 • Published • 2 -
PaECTER: Patent-level Representation Learning using Citation-informed Transformers
Paper • 2402.19411 • Published • 2 -
DAPFAM: A Domain-Aware Family-level Dataset to benchmark cross domain patent retrieval
Paper • 2506.22141 • Published • 2 -
Pap2Pat: Benchmarking Outline-Guided Long-Text Patent Generation with Patent-Paper Pairs
Paper • 2410.07009 • Published • 1 -
The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and Multi-Purpose Corpus of Patent Applications
Paper • 2207.04043 • Published -
Patent Representation Learning via Self-supervision
Paper • 2511.10657 • Published -
Intelligent System for Automated Molecular Patent Infringement Assessment
Paper • 2412.07819 • Published • 2 -
PatentBERT: Patent Classification with Fine-Tuning a pre-trained BERT Model
Paper • 1906.02124 • Published -
From scratch to silver: Creating trustworthy training data for patent-SDG classification using Large Language Models
Paper • 2509.09303 • Published