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    <abstract>We describe DANGNT@SGU’s system for the English track of SemEval-2026 Task 1 (MWAHAHA), Subtask A (text-based humor generation). Our pipeline combines a two-stage QLoRA-adapted generator based on mistralai/Mistral-7B-Instruct-v0.2 with a DistilBERT reranker trained to distinguish jokes from non-jokes. The generator is first adapted on a raw joke corpus for general humor style, then further tuned on synthetic task-format instruction–response pairs for Word Inclusion and News Headlineprompts. At inference time, we generate five candidates per input, optionally enforce lexical constraints for Word Inclusion prompts, and rerank candidates with the classifier. In the official English Subtask A results, our team DANGNT@SGU obtained Elo 962 (95% CI: 926–986), ranking 13th. The system is practical, reproducible, and based entirely on open models and public data.</abstract>
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%0 Conference Proceedings
%T DANGNT@SGU at SemEval-2026 Task 1: A Two-Stage Mistral Generator with DistilBERT Reranking for English Humor Generation
%A Nguyen, Tan Loc
%A Nguyen, Dang Tuan
%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 nguyen-nguyen-2026-dangnt
%X We describe DANGNT@SGU’s system for the English track of SemEval-2026 Task 1 (MWAHAHA), Subtask A (text-based humor generation). Our pipeline combines a two-stage QLoRA-adapted generator based on mistralai/Mistral-7B-Instruct-v0.2 with a DistilBERT reranker trained to distinguish jokes from non-jokes. The generator is first adapted on a raw joke corpus for general humor style, then further tuned on synthetic task-format instruction–response pairs for Word Inclusion and News Headlineprompts. At inference time, we generate five candidates per input, optionally enforce lexical constraints for Word Inclusion prompts, and rerank candidates with the classifier. In the official English Subtask A results, our team DANGNT@SGU obtained Elo 962 (95% CI: 926–986), ranking 13th. The system is practical, reproducible, and based entirely on open models and public data.
%U https://aclanthology.org/2026.semeval-1.375/
%P 2986-2990

Markdown (Informal)

[DANGNT@SGU at SemEval-2026 Task 1: A Two-Stage Mistral Generator with DistilBERT Reranking for English Humor Generation](https://aclanthology.org/2026.semeval-1.375/) (Nguyen & Nguyen, SemEval 2026)

• DANGNT@SGU at SemEval-2026 Task 1: A Two-Stage Mistral Generator with DistilBERT Reranking for English Humor Generation (Nguyen & Nguyen, SemEval 2026)

ACL

• Tan Loc Nguyen and Dang Tuan Nguyen. 2026. DANGNT@SGU at SemEval-2026 Task 1: A Two-Stage Mistral Generator with DistilBERT Reranking for English Humor Generation. In Proceedings of the 20th International Workshop on Semantic Evaluation (2026), pages 2986–2990, San Diego, California, USA. Association for Computational Linguistics.