Irony Detection, Reasoning and Understanding in Zero-shot Learning | Paper Citation Record

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This paper cites an unresolved cited work.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Unresolved cited work

Reference 1

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Observation 92a65f6f-8f9a-492a-af96-a09a1719293e · outbound

This paper cites Lear,A case for irony.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Lear,A case for irony

Reference 2

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Observation 2bbe599b-8b52-4ba4-9d0d-a96b11945739 · outbound

This paper cites Automatic sarcasm detection: A survey,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Automatic sarcasm detection: A survey,

Reference 3

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Observation 60600742-64e3-479e-a211-3220fd29976f · outbound

This paper cites Situational irony: A concept of events gone awry.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Situational irony: A concept of events gone awry

Reference 4

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Observation 7d64e9c1-d154-4f35-b155-5cf420a0cb33 · outbound

This paper cites From humor recognition to irony detection: The figurative language of social media,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning From humor recognition to irony detection: The figurative language of social media,

Reference 5

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This paper cites A transformer- based approach to irony and sarcasm detection,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning A transformer- based approach to irony and sarcasm detection,

Reference 6

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This paper cites Generalizable Sarcasm Detection Is Just Around The Corner, Of Course!.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Generalizable Sarcasm Detection Is Just Around The Corner, Of Course!

Reference 7

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Observation f787c4b1-dd16-4e15-9ebe-0f41ce72a444 · outbound

This paper cites We usually don’t like going to the dentist: Using common sense to detect irony on twitter,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning We usually don’t like going to the dentist: Using common sense to detect irony on twitter,

Reference 8

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Observation 19844420-f2a4-4b68-b1a9-71fc48ad877b · outbound

This paper cites Semeval-2022 task 6: isarcasmeval, intended sarcasm detection in english and arabic,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Semeval-2022 task 6: isarcasmeval, intended sarcasm detection in english and arabic,

Reference 9

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This paper cites Semeval-2018 task 3: Irony detection in english tweets,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Semeval-2018 task 3: Irony detection in english tweets,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:55:08.356546Z

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Observation 05320eb1-9a86-4190-8660-e8c2eb1f6227 · outbound

This paper cites Harnessing the power of llms in practice: A survey on chatgpt and beyond,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Harnessing the power of llms in practice: A survey on chatgpt and beyond,

Reference 11

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This paper cites Language Models are Few-Shot Learners.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Language Models are Few-Shot Learners

Reference 12

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This paper cites ChainLM: Empowering Large Language Models with Improved Chain-of-Thought Prompting.

Irony Detection, Reasoning and Understanding in Zero-shot Learning ChainLM: Empowering Large Language Models with Improved Chain-of-Thought Prompting

Reference 13

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Observation cb6e10f7-0a84-4208-bb62-77fb2d4e9aca · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Chain-of-thought prompting elicits reasoning in large language models,

Reference 14

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This paper cites Unlocking the Potential of ChatGPT: A Comprehensive Exploration of its Applications, Advantages, Limitations, and Future Directions in Natural Language Processing.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Unlocking the Potential of ChatGPT: A Comprehensive Exploration of its Applications, Advantages, Limitations, and Future Directions in Natural Language Processing

Reference 15

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This paper cites Training language models to follow instructions with human feedback,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Training language models to follow instructions with human feedback,

Reference 16

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This paper cites Chatgpt: A comprehensive review on background, applica- tions, key challenges, bias, ethics, limitations and future scope,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Chatgpt: A comprehensive review on background, applica- tions, key challenges, bias, ethics, limitations and future scope,

Reference 17

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Observation b352b043-fb5c-42ef-ae61-725b13b9c53c · outbound

This paper cites A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT.

Irony Detection, Reasoning and Understanding in Zero-shot Learning A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT

Reference 18

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This paper cites Chatgpt is a remarkable tool—for experts,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Chatgpt is a remarkable tool—for experts,

Reference 19

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Observation b34d8f39-90d8-4cde-8092-86ab121ad9ac · outbound

This paper cites Parsing-based sarcasm sentiment recognition in twitter data,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Parsing-based sarcasm sentiment recognition in twitter data,

Reference 20

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Observation 4d045def-156a-452e-83c0-a84e7762f6eb · outbound

This paper cites Sarcasm as contrast between a positive sentiment and negative situa- tion,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Sarcasm as contrast between a positive sentiment and negative situa- tion,

Reference 21

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Observation 5d4bda3c-4e6c-49ff-861e-fdd4d3def8b4 · outbound

This paper cites Using lexical resources for irony and sarcasm classification,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Using lexical resources for irony and sarcasm classification,

Reference 22

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Observation 9bc623ee-a470-490f-b5f2-40cbe66e0d7e · outbound

This paper cites Identifying sar- casm in twitter: a closer look,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Identifying sar- casm in twitter: a closer look,

Reference 23

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Observation c13bde5e-4485-480b-ae34-8eb489921b13 · outbound

This paper cites Who cares about sarcastic tweets? investigating the impact of sarcasm on sentiment analysis,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Who cares about sarcastic tweets? investigating the impact of sarcasm on sentiment analysis,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:55:08.254820Z

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This paper cites Sar- casm and irony detection in english tweets,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Sar- casm and irony detection in english tweets,

Reference 25

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Observation 4ce411d5-32c0-49f8-868f-c042fa2d9829 · outbound

This paper cites an unresolved cited work.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Unresolved cited work

Reference 26

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Observation bc4697b8-742b-4cfe-8e7e-058c8981ac1c · outbound

This paper cites Detecting irony and sarcasm in microblogs: The role of expressive signals and ensemble classifiers,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Detecting irony and sarcasm in microblogs: The role of expressive signals and ensemble classifiers,

Reference 27

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Observation dc331c05-d48c-4038-8940-a13bde0a3ba6 · outbound

This paper cites Applying basic fea- tures from sentiment analysis for automatic irony detection,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Applying basic fea- tures from sentiment analysis for automatic irony detection,

Reference 28

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Observation d8771c3b-9bb5-4721-8a68-4da9a762c893 · outbound

This paper cites Towards a contextual pragmatic model to detect irony in tweets,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Towards a contextual pragmatic model to detect irony in tweets,

Reference 29

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Observation 4add9a18-c099-4e68-9f4c-9b585ed7972f · outbound

This paper cites Empirical study of shallow and deep learning models for sarcasm detection using context in benchmark datasets,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Empirical study of shallow and deep learning models for sarcasm detection using context in benchmark datasets,

Reference 30

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Observation 5bd84ab6-af61-477b-befe-27e1fa081b3c · outbound

This paper cites Irony detection with atten- tive recurrent neural networks,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Irony detection with atten- tive recurrent neural networks,

Reference 31

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Observation 638ce0bb-6cf0-4f62-a889-e0264aa68fcc · outbound

This paper cites Transformer-based word embedding with cnn model to detect sarcasm and irony,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Transformer-based word embedding with cnn model to detect sarcasm and irony,

Reference 32

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Observation 8b9b3992-57b5-47a0-98be-c19b24bc492a · outbound

This paper cites Utilizing an attention-based lstm model for detecting sarcasm and irony in social media,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Utilizing an attention-based lstm model for detecting sarcasm and irony in social media,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:55:08.150771Z

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Observation 7f26f097-d523-4596-b327-100f37c8b40a · outbound

This paper cites Leveraging ChatGPT As Text Annotation Tool For Sentiment Analysis.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Leveraging ChatGPT As Text Annotation Tool For Sentiment Analysis

Reference 34

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This paper cites On Sarcasm Detection with OpenAI GPT-based Models.

Irony Detection, Reasoning and Understanding in Zero-shot Learning On Sarcasm Detection with OpenAI GPT-based Models

Reference 35

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This paper cites Generative pre-trained transformer (gpt) models for irony detection and classification,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Generative pre-trained transformer (gpt) models for irony detection and classification,

Reference 36

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Observation 845fae71-7822-4a2e-a43f-9045d0e359c1 · outbound

This paper cites Improving language understanding by generative pre- training,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Improving language understanding by generative pre- training,

Reference 37

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This paper cites Language models are unsupervised multitask learners,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Language models are unsupervised multitask learners,

Reference 38

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Observation 2331ac1b-4e97-4206-b2a1-d8549e5bca80 · outbound

This paper cites Large lan- guage models are zero-shot reasoners,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Large lan- guage models are zero-shot reasoners,

Reference 39

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This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 40

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This paper cites Automatic Chain of Thought Prompting in Large Language Models.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Automatic Chain of Thought Prompting in Large Language Models

Reference 41

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This paper cites Tree of thoughts: Deliberate problem solving with large language models,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Tree of thoughts: Deliberate problem solving with large language models,

Reference 42

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This paper cites Large Language Model Guided Tree-of-Thought.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Large Language Model Guided Tree-of-Thought

Reference 43

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This paper cites Using tree-of-thought prompting to boost chatgpt’s reason- ing,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Using tree-of-thought prompting to boost chatgpt’s reason- ing,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:55:08.099029Z

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This paper cites Generated Knowledge Prompting for Commonsense Reasoning.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Generated Knowledge Prompting for Commonsense Reasoning

Reference 45

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Irony Detection, Reasoning and Understanding in Zero-shot Learning Large language models as optimizers,

Reference 46

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This paper cites Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution

Reference 47

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This paper cites Large Language Models Are Human-Level Prompt Engineers.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Large Language Models Are Human-Level Prompt Engineers

Reference 48

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This paper cites PRewrite: Prompt Rewriting with Reinforcement Learning.

Irony Detection, Reasoning and Understanding in Zero-shot Learning PRewrite: Prompt Rewriting with Reinforcement Learning

Reference 49

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This paper cites Finetuned Language Models Are Zero-Shot Learners.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Finetuned Language Models Are Zero-Shot Learners

Reference 51

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This paper cites Multitask Prompted Training Enables Zero-Shot Task Generalization.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Multitask Prompted Training Enables Zero-Shot Task Generalization

Reference 52

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This paper cites Creating and Characterizing a Diverse Corpus of Sarcasm in Dialogue.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Creating and Characterizing a Diverse Corpus of Sarcasm in Dialogue

Reference 53

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This paper cites Humans require context to infer ironic intent (so computers probably do, too),.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Humans require context to infer ironic intent (so computers probably do, too),

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:55:08.074284Z

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Observation 6665142e-d789-479e-835a-ed20dbcf45b0 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Irony Detection, Reasoning and Understanding in Zero-shot Learning BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 55

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This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Irony Detection, Reasoning and Understanding in Zero-shot Learning RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 56

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This paper cites Mpnet: Masked and permuted pre-training for language understanding,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Mpnet: Masked and permuted pre-training for language understanding,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:55:08.062478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 350db769-5845-4824-96ef-e501f1b87ba0 · outbound

This paper cites A Survey in Automatic Irony Processing: Linguistic, Cognitive, and Multi-X Perspectives.

Irony Detection, Reasoning and Understanding in Zero-shot Learning A Survey in Automatic Irony Processing: Linguistic, Cognitive, and Multi-X Perspectives

Reference 58

Resolution: verified exact; local_arxiv, observed 2026-08-10T05:55:07.768263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3fca4c73-fc30-4c9c-bc8f-76a91cdf21b2 · outbound

This paper cites Shalev-Shwartz and S.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Shalev-Shwartz and S

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-10T05:55:07.697683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d59be93c-fc03-4da8-bc6a-cc250b83107c · outbound

This paper cites Machine reasoning: Technology, dilemma and future,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Machine reasoning: Technology, dilemma and future,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:55:08.041216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 9d738570-31ff-4932-a25c-f6df88209306 · outbound

This paper cites Studying irony detection beyond ironic criticism: Let’s include ironic praise,.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Studying irony detection beyond ironic criticism: Let’s include ironic praise,

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T05:55:08.029023Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ece74cf4-2100-47cb-bfd8-4a82eceb662f · outbound

This paper cites Meta Prompting for AI Systems.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Meta Prompting for AI Systems

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-10T05:55:07.709990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2575f4f-e191-4276-8482-cff25a8611c8 · outbound

This paper cites Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-10T05:55:07.714092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c00aa1b-1a33-42a0-9cac-cc1dde692a4f · outbound

This paper cites Simplification of flesch reading ease formula.

Irony Detection, Reasoning and Understanding in Zero-shot Learning Simplification of flesch reading ease formula

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-10T05:55:07.718017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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