DeFormer: Decomposing Pre-trained Transformers for Faster Question Answering

2 May 2020

Papers citing "DeFormer: Decomposing Pre-trained Transformers for Faster Question Answering"

8 / 8 papers shown

Title
EAVE: Efficient Product Attribute Value Extraction via Lightweight Sparse-layer Interaction Li Yang Qifan Wang Jianfeng Chi Jiahao Liu Jingang Wang Fuli Feng Zenglin Xu Yi Fang Lifu Huang Dongfang Liu 28 1 0 10 Jun 2024
Comparing Neighbors Together Makes it Easy: Jointly Comparing Multiple Candidates for Efficient and Effective Retrieval Jonghyun Song Cheyon Jin Wenlong Zhao Jay Yoon Lee 38 0 0 21 May 2024
Vesper: A Compact and Effective Pretrained Model for Speech Emotion Recognition Weidong Chen Xiaofen Xing Peihao Chen Xiangmin Xu VLM 28 35 0 20 Jul 2023
Improving Text Semantic Similarity Modeling through a 3D Siamese Network Jianxiang Zang Hui Liu 3DPC 20 2 0 18 Jul 2023
Investigating the Role of Feed-Forward Networks in Transformers Using Parallel Attention and Feed-Forward Net Design Shashank Sonkar Richard G. Baraniuk 11 2 0 22 May 2023
Question Generation for Evaluating Cross-Dataset Shifts in Multi-modal Grounding Arjun Reddy Akula OOD 21 3 0 24 Jan 2022
Optimizing Inference Performance of Transformers on CPUs D. Dice Alex Kogan 19 15 0 12 Feb 2021
Learning Dense Representations of Phrases at Scale Jinhyuk Lee Mujeen Sung Jaewoo Kang Danqi Chen RALM DML NAI 13 115 0 23 Dec 2020