Show newer

Actuarial Applications of Natural Language Processing Using Transformers: Case Studies for Using Text Features in an Actuarial Context. (arXiv:2206.02014v3 [cs.CL] UPDATED) 

Crime Hot-Spot Modeling via Topic Modeling and Relative Density Estimation. (arXiv:2202.04176v3 [cs.LG] UPDATED) 

BLM-17m: A Large-Scale Dataset for Black Lives Matter Topic Detection on Twitter. (arXiv:2105.01331v2 [cs.CL] UPDATED) 

Calibrating LLM-Based Evaluator. (arXiv:2309.13308v1 [cs.CL]) 

OATS: Opinion Aspect Target Sentiment Quadruple Extraction Dataset for Aspect-Based Sentiment Analysis. (arXiv:2309.13297v1 [cs.CL]) 

Natural Language Processing for Requirements Formalization: How to Derive New Approaches?. (arXiv:2309.13272v1 [cs.SE]) 

A Survey of Document-Level Information Extraction. (arXiv:2309.13249v1 [cs.CL]) 

ChEDDAR: Student-ChatGPT Dialogue in EFL Writing Education. (arXiv:2309.13243v1 [cs.CL]) 

User Simulation with Large Language Models for Evaluating Task-Oriented Dialogue. (arXiv:2309.13233v1 [cs.CL]) 

NJUNLP's Participation for the WMT2023 Quality Estimation Shared Task. (arXiv:2309.13230v1 [cs.CL]) 

Hindi to English: Transformer-Based Neural Machine Translation. (arXiv:2309.13222v1 [cs.CL]) 

A Practical Survey on Zero-shot Prompt Design for In-context Learning. (arXiv:2309.13205v1 [cs.CL]) 

Large Language Models and Control Mechanisms Improve Text Readability of Biomedical Abstracts. (arXiv:2309.13202v1 [cs.CL]) 

Document Understanding for Healthcare Referrals. (arXiv:2309.13184v1 [cs.CL]) 

Effective Distillation of Table-based Reasoning Ability from LLMs. (arXiv:2309.13182v1 [cs.CL]) 

BenLLMEval: A Comprehensive Evaluation into the Potentials and Pitfalls of Large Language Models on Bengali NLP. (arXiv:2309.13173v1 [cs.CL]) 

Large Language Models Are Also Good Prototypical Commonsense Reasoners. (arXiv:2309.13165v1 [cs.CL]) 

Cardiovascular Disease Risk Prediction via Social Media. (arXiv:2309.13147v1 [cs.CL]) 

Towards Lexical Analysis of Dog Vocalizations via Online Videos. (arXiv:2309.13086v1 [cs.SD]) 

SPICED: News Similarity Detection Dataset with Multiple Topics and Complexity Levels. (arXiv:2309.13080v1 [cs.CL]) 

Show older
Qoto Mastodon

QOTO: Question Others to Teach Ourselves
An inclusive, Academic Freedom, instance
All cultures welcome.
Hate speech and harassment strictly forbidden.