Name: AI researchers made a sarcasm detection model and it’s sooo impressive
Brand: venturebeat.com
SKU: venturebeat-com-27
Availability: OnlineOnly

critic

AI researchers made a sarcasm detection model and it’s sooo impressive

preview

×Please wait...Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! .Researchers in China say they’ve created sarcasm detection AI that achieved state-of-the-art performance on a dataset drawn from Twitter. The AI uses multimodal learning that combines text and imagery since both are often needed to understand whether a person is being sarcastic.The researchers argue that sarcasm detection can assist with sentiment analysis and crowdsourced understanding of public attitudes about a particular subject. In a challenge initiated earlier this year, its terms of service.The researchers’ AI focuses on differences between text and imagery and then combines those results to make predictions. It also compares hashtags to tweet text to help assess the sentiment a user is trying to convey.MetaBeat 2022MetaBeat will bring together thought leaders to give guidance on how metaverse technology will transform the way all industries communicate and do business on October 4 in San Francisco, CA.“Particularly, the input tokens will give high attention values to the image regions contradicting them, as incongruity is a key character of sarcasm,” the paper reads. “As the incongruity might only appear within the text (e.g., a sarcastic text associated with an unrelated image), it is necessary to consider the intra modality incongruity.”On a the model achieved a 2.74% improvement on a sarcasm detection F1 score compared to HFM, a multimodal detection model introduced last year. The new model also achieved an 86% accuracy rate, compared to 83% for HFM.was published jointly by the Chinese Academy of Sciences and the Institute of Information Engineering, both in Beijing, China. The paper was presented this week at the virtual Empirical Methods in Natural Language Processing () conference.The AI is the latest example of multimodal sarcasm detection to emerge since sarcasm in multimodal content on Instagram, Tumblr, and Twitter in 2016.University of Michigan and University of Singapore researchers used language models and computer vision to detect sarcasm in television shows, a model titled “Towards Multimodal Sarcasm Detection (An Obviously Perfect Paper).” That work was highlighted as part of the Association for Computational Linguistics (ACL) last year.VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact.Join metaverse thought leaders in San Francisco on October 4 to learn how metaverse technology will transform the way all industries communicate and do business.Did you miss a session from Transform 2022? Head over to the on-demand library for all of our featured sessions.We may collect cookies and other personal information from your interaction with ourwebsite.For more information on the categories of personal information we collect and the purposes we usethem for,please view our

×Please wait...Were you unable to attend Transform 2022? Check out all of the summit sessions in our on-demand library now! .Researchers in China say they’ve created sarcasm detection AI that achieved state-of-the-art performance on a dataset drawn from Twitter. The AI uses multimodal learning that combines text and imagery since both are often needed to understand whether a person is being sarcastic.The researchers argue that sarcasm detection can assist with sentiment analysis and crowdsourced understanding of public attitudes about a particular subject. In a challenge initiated earlier...

public

Khari Johnson

Obsessed with covering transformative technology.

https://en.wikipedia.org/wiki/VentureBeat

venturebeat.com

Credible

Speculation

Anecdotal Evidence

Generalization

Stacking the Deck

Appeal to Authority

Straw Man

Slippery Slope

Emotional Appeal

Red Herring

False Dilemma

Illogical

Moral Equivalency

Ad Hominem

Correlation w/o Causation

Semantics

Begging the Question

Faulty Analogy

Non Sequitur

Bandwagon

Dogmatism

Failing Occam's Razor

Biased

Pure Opinion

Hit Piece

Racial Bias

National Bias

Religious Bias

Financial Incentive

Political Agenda

Gender Bias

Misused Image/Video

Study Misinterpreted

Mistake

Misused Term

Science Misrepresented

Factual Error

Satire

Surface Level

Lack of Reliable Sources

Sensational

Not Credible

Investigative

Balanced

Well Sourced

Great Context

sports

entertainment

U.S.

international

business

technology

science

culture

politics

media

health

AI researchers made a sarcasm detection model and it’s sooo impressive

No article scores yet.

CRITIC REVIEWS

PUBLIC REVIEWS