Page: 1 2 3 4 5 6 7 8 9... 72
81 |
Are VQA Systems RAD? Measuring Robustness to Augmented Data with Focused Interventions ...
|
|
|
|
BASE
|
|
Show details
|
|
83 |
SemEval-2021 Task 6: Detection of Persuasion Techniques in Texts and Images ...
|
|
|
|
Abstract:
We describe SemEval-2021 task 6 on Detection of Persuasion Techniques in Texts and Images: the data, the annotation guidelines, the evaluation setup, the results, and the participating systems. The task focused on memes and had three subtasks: (i) detecting the techniques in the text, (ii) detecting the text spans where the techniques are used, and (iii) detecting techniques in the entire meme, i.e., both in the text and in the image. It was a popular task, attracting 71 registrations, and 22 teams that eventually made an official submission on the test set. The evaluation results for the third subtask confirmed the importance of both modalities, the text and the image. Moreover, some teams reported benefits when not just combining the two modalities, e.g., by using early or late fusion, but rather modeling the interaction between them in a joint model. ...
|
|
Keyword:
Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
|
|
URL: https://dx.doi.org/10.48448/xb4g-cf90 https://underline.io/lecture/30026-semeval-2021-task-6-detection-of-persuasion-techniques-in-texts-and-images
|
|
BASE
|
|
Hide details
|
|
84 |
A DQN-based Approach to Finding Precise Evidences for Fact Verification ...
|
|
|
|
BASE
|
|
Show details
|
|
85 |
Embedding Time Differences in Context-sensitive Neural Networks for Learning Time to Event ...
|
|
|
|
BASE
|
|
Show details
|
|
86 |
A Span-based Dynamic Local Attention Model for Sequential Sentence Classification ...
|
|
|
|
BASE
|
|
Show details
|
|
87 |
Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection ...
|
|
|
|
BASE
|
|
Show details
|
|
88 |
2A: Sentiment Analysis, Stylistic Analysis, and Argument Mining #1 ...
|
|
|
|
BASE
|
|
Show details
|
|
89 |
On Sample Based Explanation Methods for NLP: Faithfulness, Efficiency and Semantic Evaluation ...
|
|
|
|
BASE
|
|
Show details
|
|
90 |
How effective is BERT without word ordering? Implications for language understanding and data privacy ...
|
|
|
|
BASE
|
|
Show details
|
|
91 |
GEM: Natural Language Generation, Evaluation, and Metrics - Part 4 ...
|
|
|
|
BASE
|
|
Show details
|
|
92 |
The statistical advantage of automatic NLG metrics at the system level ...
|
|
|
|
BASE
|
|
Show details
|
|
94 |
Supporting Cognitive and Emotional Empathic Writing of Students ...
|
|
|
|
BASE
|
|
Show details
|
|
95 |
What's in the Box? An Analysis of Undesirable Content in the Common Crawl Corpus ...
|
|
|
|
BASE
|
|
Show details
|
|
96 |
Are Pretrained Convolutions Better than Pretrained Transformers? ...
|
|
|
|
BASE
|
|
Show details
|
|
97 |
Evaluation Examples are not Equally Informative: How should that change NLP Leaderboards? ...
|
|
|
|
BASE
|
|
Show details
|
|
98 |
Beyond Offline Mapping: Learning Cross-lingual Word Embeddings through Context Anchoring ...
|
|
|
|
BASE
|
|
Show details
|
|
99 |
Capturing Relations between Scientific Papers: An Abstractive Model for Related Work Section Generation ...
|
|
|
|
BASE
|
|
Show details
|
|
100 |
Hate Speech Detection Based on Sentiment Knowledge Sharing ...
|
|
|
|
BASE
|
|
Show details
|
|
Page: 1 2 3 4 5 6 7 8 9... 72
|
|