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SemEval-2024 Schedule

SemEval-2024 Schedule

SemEval-2024 will be colocated with NAACL 2024 at the Hilton Reforma Mexico City, Mexico City.

Online poster sessions will be held on Gather.

In-person oral and invited talks will be held in room Alberto 1 except for Heng Ji's invited talk (joint with *SEM), which will be in room Adaleta. Oral sessions and talks will also be streamed on Zoom. The in-person poster sessions will be held in the room DON DIEGO.

Thursday, June 20th

09:00-09:30 Welcome and Introduction to SemEval: by Workshop Chairs

09:30-10:30 Invited Talk 1, Heng Ji: Representing Illustrative Visual Semantics with Descriptive Language [Shared with *SEM]

10:30-11:00 Coffee break

11:00-12:30 Oral Session I: Tasks 1-5 and 7
  • 11:00-11:15 SemEval Task 1: Semantic Textual Relatedness for African and Asian Languages
  • 11:15-11:30 SemEval-2024 Task 2: Safe Biomedical Natural Language Inference for Clinical Trials
  • 11:30-11:45 SemEval-2024 Task 3: Multimodal Emotion Cause Analysis in Conversations
  • 11:45-12:00 SemEval-2024 Task 4: Multilingual Detection of Persuasion Techniques in Memes
  • 12:00-12:15 SemEval-2024 Task 5: Argument Reasoning in Civil Procedure
  • 12:15-12:30 SemEval-2024 Task 7: Numeral-Aware Language Understanding and Generation

12:30-14:00 Lunch break

14:00-15:00 Oral Session II: Tasks 6 and 8-10
  • 14:00-14:15 SemEval-2024 Task 6: SHROOM, a Shared-task on Hallucinations and Related Observable Overgeneration Mistakes
  • 14:15-14:30 SemEval-2024 Task 8: Multidomain, Multimodel and Multilingual Machine-Generated Text Detection
  • 14:30-14:45 SemEval-2024 Task 9: BRAINTEASER: A Novel Task Defying Common Sense
  • 14:45-15:00 SemEval 2024 - Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF)
15:00-15:30 Oral Session III: Best Paper Awards
  • 15:00-15:12 Best System Description Paper 1
  • 15:12-15:24 Best System Description Paper 2

15:30-16:00 Coffee break

15:30-17:30 Poster Session I (in person only)
  • UAlberta at SemEval-2024 Task 1: A Potpourri of Methods for Quantifying Multilingual Semantic Textual Relatedness and Similarity
  • AAdaM at SemEval-2024 Task 1: Augmentation and Adaptation for Multilingual Semantic Textual Relatedness
  • Pinealai at SemEval-2024 Task 1: Exploring Semantic Relatedness Prediction using Syntactic, TF-IDF, and Distance-Based Features.
  • GIL-IIMAS UNAM at SemEval-2024 Task 1: SAND: An In Depth Analysis of Semantic Relatedness Using Regression and Similarity Characteristics
  • VerbaNexAI Lab at SemEval-2024 Task 1: A Multilayer Artificial Intelligence Model for Semantic Relationship Detection
  • CLaC at SemEval-2024 Task 2: Faithful Clinical Trial Inference
  • UniBuc at SemEval-2024 Task 2: Tailored Prompting with Solar for Clinical NLI
  • SEME at SemEval-2024 Task 2: Comparing Masked and Generative Language Models on Natural Language Inference for Clinical Trials
  • Saama Technologies at SemEval-2024 Task 2: Three-module System for NLI4CT Enhanced by LLM-generated Intermediate Labels
  • UWBA at SemEval-2024 Task 3: Dialogue Representation and Multimodal Fusion for Emotion Cause Analysis
  • PetKaz at SemEval-2024 Task 3: Advancing Emotion Classification with an LLM for Emotion-Cause Pair Extraction in Conversations
  • VerbaNexAI Lab at SemEval-2024 Task 3: Deciphering emotional causality in conversations using multimodal analysis approach
  • BDA at SemEval-2024 Task 4: Detection of Persuasion in Memes Across Languages with Ensemble Learning and External Knowledge
  • BERTastic at SemEval-2024 Task 4: State-of-the-Art Multilingual Propaganda Detection in Memes via Zero-Shot Learning with Vision-Language Models
  • OtterlyObsessedWithSemantics at SemEval-2024 Task 4: Developing a Hierarchical Multi-Label Classification Head for Large Language Models
  • GreyBox at SemEval-2024 Task 4: Progressive Fine-tuning (for Multilingual Detection of Propaganda Techniques)
  • BCAmirs at SemEval-2024 Task 4: Beyond Words: A Multimodal and Multilingual Exploration of Persuasion in Memes
  • Pauk at SemEval-2024 Task 4: A Neuro-Symbolic Method for Consistent Classification of Propaganda Techniques in Memes
  • Edinburgh Clinical NLP at SemEval-2024 Task 2: Fine-tune your model unless you have access to GPT-4

Friday, June 21th

9:00-10:30 Poster Session II: System Description Papers (Online: Gather)
  • WarwickNLP at SemEval-2024 Task 1: Low-Rank Cross-Encoders for Efficient Semantic Textual Relatedness
  • MBZUAI-UNAM at SemEval-2024 Task 1: Sentence-CROBI, a Simple Cross-Bi-Encoder-Based Neural Network Architecture for Semantic Textual Relatedness
  • MasonTigers at SemEval-2024 Task 1: An Ensemble Approach for Semantic Textual Relatedness
  • DFKI-NLP at SemEval-2024 Task 2: Towards Robust LLMs Using Data Perturbations and MinMax Training
  • FZI-WIM at SemEval-2024 Task 2: Self-Consistent CoT for Complex NLI in Biomedical Domain
  • Lisbon Computational Linguists at SemEval-2024 Task 2: Using a Mistral-7B Model and Data Augmentation
  • CaresAI at SemEval-2024 Task 2: Improving Natural Language Inference in Clinical Trial Data using Model Ensemble and Data Explanation
  • BAMBAS at SemEval-2024 Task 4: How far can we get without looking at hierarchies?
  • Fralak at SemEval-2024 Task 4: combining RNN-generated hierarchy paths with simple neural nets for hierarchical multilabel text classification in a multilingual zero-shot setting
  • Snarci at SemEval-2024 Task 4: Themis Model for Binary Classification of Memes
  • EURECOM at SemEval-2024 Task 4: Hierarchical Loss and Model Ensembling in Detecting Persuasion Techniques
  • whatdoyoumeme at SemEval-2024 Task 4: Hierarchical-label aware cross-lingual persuasion detection using translated texts
  • NLPNCHU at SemEval-2024 Task 4: A Comparison of MDHC Strategy and In-domain Pre-training for Multilingual Detection of Persuasion Techniques in Memes
  • SU-FMI at SemEval-2024 Task 5: From BERT Fine-Tuning to LLM Prompt Engineering - Approaches in Legal Argument Reasoning
  • Halu-NLP at SemEval-2024 Task 6: MetaCheckGPT - A Multi-task Hallucination Detection using LLM uncertainty and meta-models
  • SmurfCat at SemEval-2024 Task 6: Leveraging Synthetic Data for Hallucination Detection
  • AlphaIntellect at SemEval-2024 Task 6: Detection of Hallucinations in Generated Text
  • ClusterCore at SemEval-2024 Task 7: Few Shot Prompting With Large Language Models for Numeral-Aware Headline Generation
  • Bit_numeval at SemEval-2024 Task 7: Enhance Numerical Sensitivity and Reasoning Completeness for Quantitative Understanding
  • Genaios at SemEval-2024 Task 8: Detecting Machine-Generated Text by Mixing Language Model Probabilistic Features
  • RFBES at SemEval-2024 Task 8: Investigating Syntactic and Semantic Features for Distinguishing AI-Generated and Human-Written Texts
  • MasonTigers at SemEval-2024 Task 8: Performance Analysis of Transformer-based Models on Machine-Generated Text Detection
  • AIpom at SemEval-2024 Task 8: Detecting AI-produced Outputs in M4
  • DeepPavlov at SemEval-2024 Task 8: Leveraging Transfer Learning for Detecting Boundaries of Machine-Generated Texts
  • OUNLP at SemEval-2024 Task 9: Retrieval-Augmented Generation for Solving Brain Teasers with LLMs
  • MasonTigers at SemEval-2024 Task 9: Solving Puzzles with an Ensemble of Chain-of-Thought Prompts
  • CLTeam1 at SemEval-2024 Task 10: Large Language Model based ensemble for Emotion Detection in Hinglish
  • FeedForward at SemEval-2024 Task 10: Trigger and sentext-height enriched emotion analysis in multi-party conversations

10:30-11:00 Coffee break

11:00-12:00 Invited Talk 2, Andre Martins: Beyond Single Scores: Transparent Evaluation through Fine-Grained Error Detection and Uncertainty Quantification

12:00-14:00 Lunch break

14:00-15:30 Poster Session III: System Description Papers (in person only)
  • Archimedes-AUEB at SemEval-2024 Task 5: LLM explains Civil Procedure
  • TU Wien at SemEval-2024 Task 6: Unifying Model-Agnostic and Model-Aware Techniques for Hallucination Detection
  • HaRMoNEE at SemEval-2024 Task 6: Tuning-based Approaches to Hallucination Recognition
  • Pollice Verso at SemEval-2024 Task 6: The Roman Empire Strikes Back
  • CYUT at SemEval-2024 Task 7: A Numerals Augmentation and Feature Enhancement Approach to Numeral Reading Comprehension
  • Infrrd.ai at SemEval-2024 Task 7: RAG-based end-to-end training to generate headlines and numbers
  • hinoki at SemEval-2024 Task 7: NumEval Task 3: Numeral-Aware Headline Generation (English)
  • Team Unibuc - NLP at SemEval-2024 Task 8: Transformer and Hybrid Deep Learning Based Models for Machine-Generated Text Detection
  • iimasNLP at SemEval-2024 Task 8: Unveiling structure-aware language models for automatic generated text identification
  • PetKaz at SemEval-2024 Task 8: Can Linguistics Capture the Specifics of LLM-generated Text?
  • FI Group at SemEval-2024 Task 8: A Syntactically Motivated Architecture for Multilingual Machine-Generated Text Detection
  • CLULab-UofA at SemEval-2024 Task 8: Detecting Machine-Generated Text Using Triplet-Loss-Trained Text Similarity and Text Classification
  • SINAI at SemEval-2024 Task 8: Fine-tuning on Words and Perplexity as Features for Detecting Machine Written Text
  • VerbaNexAI Lab at SemEval-2024 Task 10: Emotion recognition and reasoning in mixed-coded conversations based on an NRC VAD approach
  • UCSC NLP at SemEval-2024 Task 10: Emotion Discovery and Reasoning its Flip in Conversation (EDiReF)
  • CLaC at SemEval-2024 Task 4: Decoding Persuasion in Memes – An Ensemble of Language Models with Paraphrase Augmentation
  • PWEITINLP at SemEval-2024 Task 3: Two Step Emotion Cause Analysis

15:30-16:00 Coffee break

16:00-16:30 Concluding Remarks