natural-language-processing-10

Zero-Shot Stance Detection

3260 papers • 126 benchmarks • 313 datasets

This task has no description! Would you like to contribute one?

(Image credit: Papersgraph)

Benchmarks

These leaderboards are used to track progress in zero-shot-stance-detection-10

Trend

Dataset

Best Model

Actions

No benchmarks available.

Libraries

i

Use these libraries to find zero-shot-stance-detection-10 models and implementations

Datasets

No datasets available.

Subtasks

No subtasks available.

Most implemented papers

Zero-Shot Stance Detection: A Dataset and Model Using Generalized Topic Representations

Emily Allaway, K. McKeown•Tue Oct 06 2020

A new dataset for zero-shot stance detection is presented that captures a wider range of topics and lexical variation than in previous datasets and a new model is proposed that implicitly captures relationships between topics using generalized topic representations.

214

Content

0

Paper Graph

Adversarial Learning for Zero-Shot Stance Detection on Social Media

Emily Allaway, K. McKeown, Malavika Srikanth•Thu May 13 2021

This work proposes a new model for zero-shot stance detection on Twitter that uses adversarial learning to generalize across topics and achieves state-of-the-art performance on a number of unseen test topics with minimal computational costs.

105 0

Paper Graph

Exploiting Sentiment and Common Sense for Zero-shot Stance Detection

Zihan Liu, Yun Luo, Y. Shi•Wed Aug 17 2022

This work proposes to boost the transferability of the stance detection model by using sentiment and commonsense knowledge, which are seldom considered in previous studies, and shows that the model outperforms the state-of-the-art methods on the zero-shot and few-shot benchmark dataset–VAST.

38 0

Paper Graph

OpenStance: Real-world Zero-shot Stance Detection

Wenpeng Yin, Hanzi Xu, S. Vucetic•Mon Oct 24 2022

The key challenge of OpenStance lies in open-domain generalization: learning a system with fully unspecific supervision but capable of generalizing to any dataset, and a single system, without any topic-specific supervision, outperforms the supervised method on three popular datasets.

28 0

Paper Graph

Stance Reasoner: Zero-Shot Stance Detection on Social Media with Explicit Reasoning

E. Milios, Maksym Taranukhin, Vered Shwartz•Thu Mar 21 2024

An approach to zero-shot stance detection on social media that leverages explicit reasoning over background knowledge to guide the model’s inference about the document’s stance on a target, and uses a pre-trained language model as a source of world knowledge to generate intermediate reasoning steps.

16 0

Paper Graph

EDDA: A Encoder-Decoder Data Augmentation Framework for Zero-Shot Stance Detection

Daijun Ding, Li Dong, Zhichao Huang, Guangning Xu, Xu Huang, Bo Liu, Liwen Jing, Bowen Zhang•Fri Mar 22 2024

An encoder-decoder data augmentation (EDDA) framework that increases semantic relevance and syntactic variety in augmented texts while enabling interpretable rationale-based learning.

6 0

Paper Graph

Adding a benchmark result helps the community track progress.