SMoA: Sparse Mixture of Adapters to Mitigate Multiple Dataset Biases

SMoA: Sparse Mixture of Adapters to Mitigate Multiple Dataset Biases

28 February 2023

Yanchen Liu

Jing Liu

Papers citing "SMoA: Sparse Mixture of Adapters to Mitigate Multiple Dataset Biases"

8 / 8 papers shown

Title
Make Your Decision Convincing! A Unified Two-Stage Framework: Self-Attribution and Decision-Making Yanrui Du Sendong Zhao Hao Wang Yuhan Chen Rui Bai Zewen Qiang Muzhen Cai Bing Qin 16 0 0 20 Oct 2023
DADA: Dialect Adaptation via Dynamic Aggregation of Linguistic Rules Yanchen Liu William B. Held Diyi Yang 43 10 0 22 May 2023
ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts Akari Asai Mohammadreza Salehi Matthew E. Peters Hannaneh Hajishirzi 124 100 0 24 May 2022
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 238 805 0 14 Oct 2021
Tailor: Generating and Perturbing Text with Semantic Controls Alexis Ross Tongshuang Wu Hao Peng Matthew E. Peters Matt Gardner 136 77 0 15 Jul 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,844 0 18 Apr 2021
Competency Problems: On Finding and Removing Artifacts in Language Data Matt Gardner William Merrill Jesse Dodge Matthew E. Peters Alexis Ross Sameer Singh Noah A. Smith 166 107 0 17 Apr 2021
HypoNLI: Exploring the Artificial Patterns of Hypothesis-only Bias in Natural Language Inference Tianyu Liu Xin Zheng Baobao Chang Zhifang Sui 43 23 0 05 Mar 2020