NLP Model

Natural Language Processing (NLP) models aim to enable computers to understand, interpret, and generate human language. Current research focuses on improving model robustness to noisy or user-generated content, enhancing explainability and interpretability through techniques like counterfactual explanations and latent concept attribution, and addressing biases related to fairness and privacy. These advancements are crucial for building reliable and trustworthy NLP systems with broad applications across various domains, including legal tech, healthcare, and social media analysis.

Papers

February 4, 2022

A Benchmark Corpus for the Detection of Automatically Generated Text in Academic Publications
Vijini Liyanage, Davide Buscaldi, Adeline Nazarenko
Data Detection Text Modality Text Generation NLP Model Generated Text Scholarly Document

January 24, 2022

Artefact Retrieval: Overview of NLP Models with Knowledge Base Access
Vilém Zouhar, Marius Mosbach, Debanjali Biswas, Dietrich Klakow
Language Model Question Answering NLP Model Artefact Detection

January 18, 2022

Annotating the Tweebank Corpus on Named Entity Recognition and Building NLP Models for Social Media Analysis
Hang Jiang, Yining Hua, Doug Beeferman, Deb Roy
Entity Recognition Social Medium Named Entity Recognition NLP Model Annotation Rather NLP Pipeline Twitter Corpus

December 15, 2021

Measure and Improve Robustness in NLP Models: A Survey
Xuezhi Wang, Haohan Wang, Diyi Yang
Timely Survey Native Robustness NLP Field NLP Model Open Challenge Robustness Issue

November 18, 2021

Swin Transformer V2: Scaling Up Capacity and Resolution
Ze Liu, Han Hu, Yutong Lin, Zhuliang Yao, Zhenda Xie, Yixuan Wei, Jia Ning, Yue Cao, Zheng Zhang, Li Dong, Furu Wei, Baining Guo
Swin Transformer NLP Model Large Vision Model Conjunct ReSolution Capacity Loss Image Statistic

November 15, 2021

Triggerless Backdoor Attack for NLP Tasks with Clean Labels
Leilei Gan, Jiwei Li, Tianwei Zhang, Xiaoya Li, Yuxian Meng, Fei Wu, Yi Yang, Shangwei Guo, Chun Fan
Backdoor Attack NLP Field NLP Task NLP Model Textual Backdoor Attack Multimodal Backdoor Semantic Anomaly Clean Label

November 14, 2021

Time Waits for No One! Analysis and Challenges of Temporal Misalignment
Kelvin Luu, Daniel Khashabi, Suchin Gururangan, Karishma Mandyam, Noah A. Smith
General Analysis Technical Challenge Time Matter NLP Model Task Specific One 2 Temporal Misalignment