NLPExplorer

SemEval - 2025

Total Papers:- 330

Total Papers accross all years:- 1682

Total Citations :- 0

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TreeSearch at SemEval-2025 Task 8: Monte Carlo Tree Search for Question-Answering over Tabular Data

Aakarsh Nair | Huixin Yang |

CIOL at SemEval-2025 Task 11: Multilingual Pre-trained Model Fusion for Text-based Emotion Recognition

Md. Hoque | Mahfuz Ahmed Anik | Abdur Rahman | Azmine Toushik Wasi |

CAIDAS at SemEval-2025 Task 7: Enriching Sparse Datasets with LLM-Generated Content for Improved Information Retrieval

UZH at SemEval-2025 Task 3: Token-Level Self-Consistency for Hallucination Detection

Michelle Wastl | Jannis Vamvas | Rico Sennrich |

tinaal at SemEval-2025 Task 11: Enhancing Perceived Emotion Intensity Prediction with Boosting Fine-Tuned Transformers

Ting Zhu | Liting Huang | Huizhi(elly) Liang |

SBU-NLP at SemEval-2025 Task 8: Self-Correction and Collaboration in LLMs for Tabular Question Answering

Rashin Rahnamoun | Mehrnoush Shamsfard |

TIFIN India at SemEval-2025: Harnessing Translation to Overcome Multilingual IR Challenges in Fact-Checked Claim Retrieval

CIC-IPN at SemEval-2025 Task 11: Transformer-Based Approach to Multi-Class Emotion Detection

HausaNLP at SemEval-2025 Task 2: Entity-Aware Fine-tuning vs. Prompt Engineering in Entity-Aware Machine Translation

AtlasIA at SemEval-2025 Task 11: FastText-Based Emotion Detection in Moroccan Arabic for Low-Resource Settings

Abdeljalil El Majjodi | Imane Momayiz | Nouamane Tazi |

COGNAC at SemEval-2025 Task 10: Multi-level Narrative Classification with Summarization and Hierarchical Prompting

Azwad Anjum Islam | Mark Finlayson |

Mr. Snuffleupagus at SemEval-2025 Task 4: Unlearning Factual Knowledge from LLMs Using Adaptive RMU

Arjun Dosajh | Mihika Sanghi |

NLP_CIMAT at SemEval-2025 Task 3: Just Ask GPT or look Inside. A prompt and Neural Networks Approach to Hallucination Detection

Jaime Stack - Sánchez | Miguel Alvarez - Carmona | Adrian Pastor Lopez Monroy |

AILS-NTUA at SemEval-2025 Task 8: Language-to-Code prompting and Error Fixing for Tabular Question Answering