Optimizing text representations to capture (dis)similarity between political parties

21 October 2022

Papers citing "Optimizing text representations to capture (dis)similarity between political parties"

10 / 10 papers shown

Title
SimCSE: Simple Contrastive Learning of Sentence Embeddings Tianyu Gao Xingcheng Yao Danqi Chen AILaw SSL 261 3,396 0 18 Apr 2021
Whitening Sentence Representations for Better Semantics and Faster Retrieval Jianlin Su Jiarun Cao Weijie Liu Yangyiwen Ou 51 303 0 29 Mar 2021
Language Models are Few-Shot Learners Tom B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan ... Christopher Berner Sam McCandlish Alec Radford Ilya Sutskever Dario Amodei BDL 808 42,055 0 28 May 2020
How Contextual are Contextualized Word Representations? Comparing the Geometry of BERT, ELMo, and GPT-2 Embeddings Kawin Ethayarajh 86 872 0 02 Sep 2019
Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks Nils Reimers Iryna Gurevych 1.3K 12,226 0 27 Aug 2019
Representation Degeneration Problem in Training Natural Language Generation Models Jun Gao Di He Xu Tan Tao Qin Liwei Wang Tie-Yan Liu 62 268 0 28 Jul 2019
RoBERTa: A Robustly Optimized BERT Pretraining Approach Yinhan Liu Myle Ott Naman Goyal Jingfei Du Mandar Joshi Danqi Chen Omer Levy M. Lewis Luke Zettlemoyer Veselin Stoyanov AIMat 665 24,464 0 26 Jul 2019
Political Text Scaling Meets Computational Semantics F. Nanni Goran Glavaš Ines Rehbein Simone Paolo Ponzetto Heiner Stuckenschmidt 28 15 0 12 Apr 2019
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding Jacob Devlin Ming-Wei Chang Kenton Lee Kristina Toutanova VLM SSL SSeg 1.8K 94,891 0 11 Oct 2018
Enriching Word Vectors with Subword Information Piotr Bojanowski Edouard Grave Armand Joulin Tomas Mikolov NAI SSL VLM 229 9,972 0 15 Jul 2016