@inproceedings{kongqiang-etal-2026-wangkongqiang,
title = "wangkongqiang at {S}em{E}val-2026 Task 1: {MWAHAHA}- Competition on Humor Generation",
author = "Kongqiang, Wang and
Peng, Zhang and
Qingli, Tan",
editor = "Kochmar, Ekaterina and
Ghosh, Debanjan and
North, Kai and
Komachi, Mamoru",
booktitle = "Proceedings of the 20th {I}nternational {W}orkshop on {S}emantic {E}valuation (2026)",
month = jul,
year = "2026",
address = "San Diego, California, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.semeval-1.12/",
pages = "80--88",
ISBN = "979-8-89176-414-9",
abstract = "This paper presents our system developed for the SemEval-2026 Task 1: MWAHAHA-Competition on Humor Generation. on Subtask A: Text-based Humor Generation. Given a set of text-based constraints, generate a joke. This subtask A will be conducted in English, Spanish, and Chinese. on Subtask B: Image-Based Caption Generation. This subtask explores humor in a multimodal context, combining visual inputs with text generation. This subtask B is in English only. To this end, we mainly focus on Subtask A: Text-based Humor Generation in English and Chinese, Subtask B: Image-BasedCaption Generation in English language to use two important languages models: BLIP and Qwen series LLM. For Task B1: Image-only Humor Generation and Task B2: Image and Prompt Humor Generation. Our submission achieved the good ranking place in the test set. All subtasks evaluated using Rating (95{\%} CI) score across different languages and modality contexts. For Subtask A in English and Chinese, Rating score 950 and 1054, 95{\%} CI [ 922, 982] and [1024, 1104], ranked 16th and 1st respectively. For Subtask B in B1 and B2, Rating score 976 and 987, 95{\%} CI [ 941, 1007] and[948, 1016], ranked 5th and 3rd respectively. For the final ranking, organizers will use the Rating (95{\%} CI) score. Even so, our approach still has yielded good results."
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<abstract>This paper presents our system developed for the SemEval-2026 Task 1: MWAHAHA-Competition on Humor Generation. on Subtask A: Text-based Humor Generation. Given a set of text-based constraints, generate a joke. This subtask A will be conducted in English, Spanish, and Chinese. on Subtask B: Image-Based Caption Generation. This subtask explores humor in a multimodal context, combining visual inputs with text generation. This subtask B is in English only. To this end, we mainly focus on Subtask A: Text-based Humor Generation in English and Chinese, Subtask B: Image-BasedCaption Generation in English language to use two important languages models: BLIP and Qwen series LLM. For Task B1: Image-only Humor Generation and Task B2: Image and Prompt Humor Generation. Our submission achieved the good ranking place in the test set. All subtasks evaluated using Rating (95% CI) score across different languages and modality contexts. For Subtask A in English and Chinese, Rating score 950 and 1054, 95% CI [ 922, 982] and [1024, 1104], ranked 16th and 1st respectively. For Subtask B in B1 and B2, Rating score 976 and 987, 95% CI [ 941, 1007] and[948, 1016], ranked 5th and 3rd respectively. For the final ranking, organizers will use the Rating (95% CI) score. Even so, our approach still has yielded good results.</abstract>
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%0 Conference Proceedings
%T wangkongqiang at SemEval-2026 Task 1: MWAHAHA- Competition on Humor Generation
%A Kongqiang, Wang
%A Peng, Zhang
%A Qingli, Tan
%Y Kochmar, Ekaterina
%Y Ghosh, Debanjan
%Y North, Kai
%Y Komachi, Mamoru
%S Proceedings of the 20th International Workshop on Semantic Evaluation (2026)
%D 2026
%8 July
%I Association for Computational Linguistics
%C San Diego, California, USA
%@ 979-8-89176-414-9
%F kongqiang-etal-2026-wangkongqiang
%X This paper presents our system developed for the SemEval-2026 Task 1: MWAHAHA-Competition on Humor Generation. on Subtask A: Text-based Humor Generation. Given a set of text-based constraints, generate a joke. This subtask A will be conducted in English, Spanish, and Chinese. on Subtask B: Image-Based Caption Generation. This subtask explores humor in a multimodal context, combining visual inputs with text generation. This subtask B is in English only. To this end, we mainly focus on Subtask A: Text-based Humor Generation in English and Chinese, Subtask B: Image-BasedCaption Generation in English language to use two important languages models: BLIP and Qwen series LLM. For Task B1: Image-only Humor Generation and Task B2: Image and Prompt Humor Generation. Our submission achieved the good ranking place in the test set. All subtasks evaluated using Rating (95% CI) score across different languages and modality contexts. For Subtask A in English and Chinese, Rating score 950 and 1054, 95% CI [ 922, 982] and [1024, 1104], ranked 16th and 1st respectively. For Subtask B in B1 and B2, Rating score 976 and 987, 95% CI [ 941, 1007] and[948, 1016], ranked 5th and 3rd respectively. For the final ranking, organizers will use the Rating (95% CI) score. Even so, our approach still has yielded good results.
%U https://aclanthology.org/2026.semeval-1.12/
%P 80-88
Markdown (Informal)
[wangkongqiang at SemEval-2026 Task 1: MWAHAHA- Competition on Humor Generation](https://aclanthology.org/2026.semeval-1.12/) (Kongqiang et al., SemEval 2026)
ACL