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Factual Probing Is [MASK]: Learning vs. Learning to Recall

12 April 2021

Papers citing "Factual Probing Is [MASK]: Learning vs. Learning to Recall"

24 / 274 papers shown

Title
Rewire-then-Probe: A Contrastive Recipe for Probing Biomedical Knowledge of Pre-trained Language Models Zaiqiao Meng Fangyu Liu Ehsan Shareghi Yixuan Su Charlotte Collins Nigel Collier 93 28 0 15 Oct 2021
Exploring Universal Intrinsic Task Subspace via Prompt Tuning Yujia Qin Xiaozhi Wang Yusheng Su Yankai Lin Ning Ding ... Juanzi Li Lei Hou Peng Li Maosong Sun Jie Zhou VLM VPVLM 190 29 0 15 Oct 2021
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks Xiao Liu Kaixuan Ji Yicheng Fu Weng Lam Tam Zhengxiao Du Zhilin Yang Jie Tang VLM 301 864 0 14 Oct 2021
A Few More Examples May Be Worth Billions of Parameters Yuval Kirstain Patrick Lewis Sebastian Riedel Omer Levy 127 21 0 08 Oct 2021
Inferring Offensiveness In Images From Natural Language Supervision P. Schramowski Kristian Kersting 48 2 0 08 Oct 2021
Paradigm Shift in Natural Language Processing Tianxiang Sun Xiangyang Liu Xipeng Qiu Xuanjing Huang 224 84 0 26 Sep 2021
Benchmarking Commonsense Knowledge Base Population with an Effective Evaluation Dataset Tianqing Fang Weiqi Wang Sehyun Choi Shibo Hao Hongming Zhang Yangqiu Song Bin He 79 32 0 16 Sep 2021
Can Language Models be Biomedical Knowledge Bases? Mujeen Sung Jinhyuk Lee Sean S. Yi Minji Jeon Sungdong Kim Jaewoo Kang AI4MH 190 107 0 15 Sep 2021
PPT: Pre-trained Prompt Tuning for Few-shot Learning Yuxian Gu Xu Han Zhiyuan Liu Minlie Huang VLM 162 420 0 09 Sep 2021
Discrete and Soft Prompting for Multilingual Models Mengjie Zhao Hinrich Schütze LRM 92 72 0 08 Sep 2021
Learning to Prompt for Vision-Language Models Kaiyang Zhou Jingkang Yang Chen Change Loy Ziwei Liu VPVLM CLIP VLM 550 2,447 0 02 Sep 2021
Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners Ningyu Zhang Luoqiu Li Xiang Chen Shumin Deng Zhen Bi Chuanqi Tan Fei Huang Huajun Chen VLM 150 180 0 30 Aug 2021
Noisy Channel Language Model Prompting for Few-Shot Text Classification Sewon Min Michael Lewis Hannaneh Hajishirzi Luke Zettlemoyer VLM 90 220 0 09 Aug 2021
Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing Pengfei Liu Weizhe Yuan Jinlan Fu Zhengbao Jiang Hiroaki Hayashi Graham Neubig VLM SyDa 335 4,050 0 28 Jul 2021
A Closer Look at How Fine-tuning Changes BERT Yichu Zhou Vivek Srikumar 82 68 0 27 Jun 2021
Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models Robert L Logan IV Ivana Balavzević Eric Wallace Fabio Petroni Sameer Singh Sebastian Riedel VPVLM 106 212 0 24 Jun 2021
Why Do Pretrained Language Models Help in Downstream Tasks? An Analysis of Head and Prompt Tuning Colin Wei Sang Michael Xie Tengyu Ma 148 100 0 17 Jun 2021
BERTnesia: Investigating the capture and forgetting of knowledge in BERT Jonas Wallat Jaspreet Singh Avishek Anand CLL KELM 148 60 0 05 Jun 2021
True Few-Shot Learning with Language Models Ethan Perez Douwe Kiela Kyunghyun Cho 142 440 0 24 May 2021
Relational World Knowledge Representation in Contextual Language Models: A Review Tara Safavi Danai Koutra KELM 100 51 0 12 Apr 2021
ASER: Towards Large-scale Commonsense Knowledge Acquisition via Higher-order Selectional Preference over Eventualities Hongming Zhang Xin Liu Haojie Pan Hao Ke Jiefu Ou Tianqing Fang Yangqiu Song 77 48 0 05 Apr 2021
GPT Understands, Too Xiao Liu Yanan Zheng Zhengxiao Du Ming Ding Yujie Qian Zhilin Yang Jie Tang VLM 184 1,186 0 18 Mar 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 435 1,987 0 31 Dec 2020
Pre-trained Models for Natural Language Processing: A Survey Xipeng Qiu Tianxiang Sun Yige Xu Yunfan Shao Ning Dai Xuanjing Huang LM&MA VLM 395 1,500 0 18 Mar 2020