Towards Comprehensive Patent Approval Predictions:Beyond Traditional Document Classification

no code implementations • ACL 2022 • Xiaochen Gao, Zhaoyi Hou, Yifei Ning, Kewen Zhao, Beilei He, Jingbo Shang, Vish Krishnan

novelty scores.

Classification Document Classification

What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions

1 code implementation • 22 May 2024 • Sang Keun Choe, Hwijeen Ahn, Juhan Bae, Kewen Zhao, Minsoo Kang, Youngseog Chung, Adithya Pratapa, Willie Neiswanger, Emma Strubell, Teruko Mitamura, Jeff Schneider, Eduard Hovy, Roger Grosse, Eric Xing

Large language models (LLMs) are trained on a vast amount of human-written data, but data providers often remain uncredited.

Data Valuation

Beyond Scaling: Predicting Patent Approval with Domain-specific Fine-grained Claim Dependency Graph

1 code implementation • 22 Apr 2024 • Xiaochen Kev Gao, Feng Yao, Kewen Zhao, Beilei He, Animesh Kumar, Vish Krishnan, Jingbo Shang

In this paper, we delve into the patent approval pre-diction task and unveil that simple domain-specific graph methods outperform enlarging the model, using the intrinsic dependencies within the patent data.

Formulating Few-shot Fine-tuning Towards Language Model Pre-training: A Pilot Study on Named Entity Recognition

1 code implementation • 24 May 2022 • Zihan Wang, Kewen Zhao, Zilong Wang, Jingbo Shang

Fine-tuning pre-trained language models has recently become a common practice in building NLP models for various tasks, especially few-shot tasks.

Few-shot NER Language Modelling +2