Skip to content

Latest commit

 

History

History
168 lines (138 loc) · 14.2 KB

schedule.md

File metadata and controls

168 lines (138 loc) · 14.2 KB
Raw
title
SemEval-2023 Schedule

SemEval-2023 Schedule

SemEval-2023 will be colocated with ACL 2023 at the Westin Harbour Castle, Toronto.

Online poster sessions will be held on Gather.

In-person oral, poster sessions and invited talk will be held in the Queens Quay except for Junyi Jessy Li's invited talk (joint with *SEM), which will be in Pier 5. Oral sessions and talks will also be streamed on Zoom.

Thursday, 13th July

09:00-09:15 Welcome and Introduction to SemEval: by Workshop Chairs

09:20-10:30 Invited Talk 1, Junyi Jessy Li: Modeling Discourse as Questions and Answers [Shared with *SEM]

10:30-11:00 Coffee break

11:00-12:30 Oral Session I: Tasks 1-5
  • 11:00-11:12 SemEval-2023 Task 1: Visual Word Sense Disambiguation
  • 11:12-11:24 SemEval-2023 Task 2: Fine-grained Multilingual Named Entity Recognition (MultiCoNER 2)
  • 11:24-11:34 DAMO-NLP at SemEval-2023 Task 2: A Unified Retrieval-augmented System for Multilingual Named Entity Recognition
  • 11:34-11:46 SemEval-2023 Task 3: Detecting the Category, the Framing, and the Persuasion Techniques in Online News in a Multi-lingual Setup
  • 11:46-11:56 SheffieldVeraAI at SemEval-2023 Task 3: Mono and Multilingual Approaches for News Genre, Topic and Persuasion Technique Classification
  • 11:56-12:08 SemEval-2023 Task 4: ValueEval: Identification of Human Values behind Arguments
  • 12:08-12:18 Adam-Smith at SemEval-2023 Task 4: Discovering Human Values in Arguments with Ensembles of Transformer-based Models
  • 12:18-12:30 SemEval-2023 Task 5: Clickbait Spoiling

12:30-14:00 Lunch break

14:00-15:00 Oral Session II: Tasks 5-10
  • 14:00-14:10 TohokuNLP at SemEval-2023 Task 5: Clickbait Spoiling via Simple Seq2Seq Generation and Ensembling
  • 14:10-14:22 SemEval 2023 Task 6: LegalEval - Understanding Legal Texts
  • 14:22-14:34 SemEval-2023 Task 7: Multi-Evidence Natural Language Inference for Clinical Trial Data
  • 14:34-14:44 Saama AI Research at SemEval-2023 Task 7: Exploring the Capabilities of Flan-T5 for Multi-evidence Natural Language Inference in Clinical Trial Data
  • 14:44-14:56 SemEval 2023 Task 8: Causal Medical Claim Identification and Related PIO Frame Extraction from Social Media Posts

15:00-15:30 Coffee break

15:30-17:15 Oral Session III: Tasks 9-12
  • 15:30-15:42 SemEval-2023 Task 10: Explainable Detection of Online Sexism
  • 15:42-15:54 DH-FBK at SemEval-2023 Task 10: Multi-Task Learning with Classifier Ensemble Agreement for Sexism Detection
  • 15:54-16:04 SemEval-2023 Task 11: Learning with Disagreements (Le-Wi-Di)
  • 16:04-16:16 University at Buffalo at SemEval-2023 Task 11: MASDA--Modelling Annotator Sensibilities through DisAggregation
  • 16:16-16:26 SemEval-2023 Task 12: Sentiment Analysis for African Languages (AfriSenti-SemEval)
  • 16:26-16:38 NLNDE at SemEval-2023 Task 12: Adaptive Pretraining and Source Language Selection for Low-Resource Multilingual Sentiment Analysis
  • 16:38-16:48 SemEval 2023 Task 9: Multilingual Tweet Intimacy Analysis
16:45-18:00 Poster Session I: System Description Papers (Queens Quay and Online: Gather)
  • lasigeBioTM at SemEval-2023 Task 7: Improving Natural Language Inference Baseline Systems with Domain Ontologies
  • BERTastic at SemEval-2023 Task 3: Fine-Tuning Pretrained Multilingual Transformers – Does Order Matter?
  • MELODI at SemEval-2023 Task 3: In-domain Pre-training for Low-resource Classification of News Articles
  • OPI at SemEval 2023 Task 9: A Simple but Effective Approach to Multilingual Tweet Intimacy Analysis
  • OPI at SemEval 2023 Task 1: Image-Text Embeddings and Multimodal Information Retrieval for Visual Word Sense Disambiguation
  • MaChAmp at SemEval-2023 Tasks 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, and 12: On the Effectiveness of Intermediate Training on an Uncurated Collection of Datasets.
  • UBC-DLNLP at SemEval-2023 Task 12: Impact of Transfer Learning on African Sentiment Analysis
  • RIGA at SemEval-2023 Task 2: NER Enhanced with GPT-3
  • LT at SemEval-2023 Task 1: Effective Zero-Shot Visual Word Sense Disambiguation Approaches Using External Knowledge Sources
  • OPI PIB at SemEval-2023 Task 1: A CLIP-based Solution Paired with an Additional Word Context Extension
  • MIND at SemEval-2023 Task 11: From Uncertain Predictions to Subjective Disagreement
  • uOttawa at SemEval-2023 Task 6: Deep Learning for Legal Text Understanding
  • Walter Burns at SemEval-2023 Task 5: NLP-CIMAT - Leveraging Model Ensembles for Clickbait Spoiling
  • SINAI at SemEval-2023 Task 10: Leveraging Emotions, Sentiments, and Irony Knowledge for Explainable Detection of Online Sexism
  • UZH_CLyp at SemEval-2023 Task 9: Head-First Fine-Tuning and ChatGPT Data Generation for Cross-Lingual Learning in Tweet Intimacy Prediction
  • Augustine of Hippo at SemEval-2023 Task 4: An Explainable Knowledge Extraction Method to Identify Human Values in Arguments with SuperASKE
  • UniBoe's at SemEval-2023 Task 10: Model-Agnostic Strategies for the Improvement of Hate-Tuned and Generative Models in the Classification of Sexist Posts
  • NLPeople at SemEval-2023 Task 2: A Staged Approach for Multilingual Named Entity Recognition
  • JUAGE at SemEval 2023 Task 10: Parameter Efficient Classification
  • IXA/Cogcomp at SemEval-2023 Task 2: Context-enriched Multilingual Named Entity Recognition Using Knowledge Bases
  • NAP at SemEval-2023 Task 3: Is Less Really More? (Back-)Translation as Data Augmentation Strategies for Detecting Persuasion Techniques
  • MilaNLP at SemEval-2023 Task 10: Ensembling Domain-Adapted and Regularized Pretrained Language Models for Robust Sexism Detection
  • Rutgers Multimedia Image Processing Lab at SemEval-2023 Task-1: Text-Augmentation-based Approach for Visual Word Sense Disambiguation
  • SafeWebUH at SemEval-2023 Task 11: Learning Annotator Disagreement in Derogatory Text: Comparison of Direct Training vs Aggregation
  • PAI at SemEval-2023 Task 4: A General Multi-label Classification System with Class-balanced Loss Function and Ensemble Module
  • Witcherses at SemEval-2023 Task 12: Ensemble Learning for African Sentiment Analysis
  • APatt at SemEval-2023 Task 3: The Sapienza NLP System for Ensemble-based Multilingual Propaganda Detection
  • Foul at SemEval-2023 Task 12 : MARBERT Language Model and Lexical Filtering for Sentiments Analysis of Tweets in Algerian Arabic
  • Diane Simmons at SemEval-2023 Task 5: Is It Possible to Make Good Clickbait Spoilers Using a Zero-Shot Approach? Check It Out
  • TAM of SCNU at SemEval-2023 Task 1: FCLL: A Fine-grained Contrastive Language-Image Learning Model for Cross-language Visual Word Sense Disambiguation
  • Appeal for Attention at SemEval-2023 Task 3: Data Augmentation and Extension Strategies for Detection of Online News Persuasion Techniques
  • KInITVeraAI at SemEval-2023 Task 3: Simple Yet Powerful Multilingual Fine-Tuning for Persuasion Techniques Detection
  • USTC-NELSLIP at SemEval-2023 Task 2: Statistical Construction and Dual Adaptation of Gazetteer for Multilingual Complex NER
  • SRCB at SemEval-2023 Task 2: A System of Complex Named Entity Recognition with External Knowledge
  • PAI at SemEval-2023 Task 2: A Universal System for Named Entity Recognition with External Entity Information
  • IITD at SemEval-2023 Task 2: A Multi-Stage Information Retrieval Approach for Fine-Grained Named Entity Recognition
  • L3I++ at SemEval-2023 Task 2: Prompting for Multilingual Complex Named Entity Recognition
  • mCPT at SemEval-2023 Task 3: Multilingual Label-Aware Contrastive Pre-Training of Transformers for Few- and Zero-shot Framing Detection
  • UIO at SemEval-2023 Task 12: Multilingual Fine-tuning for Sentiment Classification in Low-resource Languages
  • Jack-Ryder at SemEval-2023 Task 5: Zero-Shot Clickbait Spoiling by Rephrasing Titles as Questions
  • GMNLP at SemEval-2023 Task 12: Sentiment Analysis with Phylogeny-Based Adapters
  • QCRI at SemEval-2023 Task 3: News Genre, Framing and Persuasion Techniques Detection Using Multilingual Models
  • Nonet at SemEval-2023 Task 6: Methodologies for Legal Evaluation

Friday, 14th July

09:15-10:15 Invited Talk 2, Siva Reddy: Holistic Evaluation of Language Models for Information Seeking

10:30-11:00 Coffee break

11:00-12:30 Poster Session II: System Description Papers (Online: Gather)
  • ChaPat at SemEval-2023 Task 9: Text Intimacy Analysis Using Ensembles of Multilingual Transformers
  • MLlab4CS at SemEval-2023 Task 2: Named Entity Recognition in Low-resource Language Bangla Using Multilingual Language Models
  • FMI-SU at SemEval-2023 Task 7: Two-level Entailment Classification of Clinical Trials Enhanced by Contextual Data Augmentation
  • KDDIE at SemEval-2023 Task 2: External Knowledge Injection for Named Entity Recognition
  • WKU_NLP at SemEval-2023 Task 9: Translation Augmented Multilingual Tweet Intimacy Analysis
  • CLaC at SemEval-2023 Task 2: Comparing Span-Prediction and Sequence-Labeling Approaches for NER
  • DSHacker at SemEval-2023 Task 3: Genres and Persuasion Techniques Detection with Multilingual Data Augmentation through Machine Translation and Text Generation
  • Sakura at SemEval-2023 Task 2: Data Augmentation via Translation
  • DCU at SemEval-2023 Task 10: A Comparative Analysis of Encoder-only and Decoder-only Language Models with Insights into Interpretability
  • HEVS-TUW at SemEval-2023 Task 8: Ensemble of Language Models and Rule-based Classifiers for Claims Identification and PICO Extraction
  • Jus Mundi at SemEval-2023 Task 6: Using a Frustratingly Easy Domain Adaption for a Legal Named Entity Recognition System
  • Jack-flood at SemEval-2023 Task 5:Hierarchical Encoding and Reciprocal Rank Fusion-Based System for Spoiler Classification and Generation
  • BpHigh at SemEval-2023 Task 7: Can Fine-tuned Cross-encoders Outperform GPT-3.5 in NLI Tasks on Clinical Trial Data?
  • WADER at SemEval-2023 Task 9: A Weak-labelling Framework for Data Augmentation in tExt Regression Tasks
  • Arthur Caplan at SemEval-2023 Task 4: Enhancing Human Value Detection through Fine-tuned Pre-trained Models
  • UIRISC at SemEval-2023 Task 10: Explainable Detection of Online Sexism by Ensembling Fine-tuning Language Models
  • John Boy Walton at SemEval-2023 Task 5: An Ensemble Approach to Spoiler Classification and Retrieval for Clickbait Spoiling
  • CAISA at SemEval-2023 Task 8: Counterfactual Data Augmentation for Mitigating Class Imbalance in Causal Claim Identification
  • Team ReDASPersuasion at SemEval-2023 Task 3: Persuasion Detection Using Multilingual Transformers and Language Agnostic Features
  • Arguably at SemEval-2023 Task 11: Learning the Disagreements Using Unsupervised Behavioral Clustering and Language Models
  • SinaAI at SemEval-2023 Task 3: A Multilingual Transformer Language Model-based Approach for the Detection of News Genre, Framing and Persuasion Techniques
  • Friedrich Nietzsche at SemEval-2023 Task 4: Detection of Human Values from Text Using Machine Learning
  • ITTC at SemEval 2023-Task 7: Document Retrieval and Sentence Similarity for Evidence Retrieval in Clinical Trial Data
  • Ebhaam at SemEval-2023 Task 1: Comparing Cross-Domain and Same-Domain CLIP-Based Approaches for Visual Word Sense Disambiguation
  • Sartipi-Sedighin at SemEval-2023 Task 2: Fine-grained Named Entity Recognition with Pre-trained Contextual Language Models and Data Augmentation from Wikipedia
  • SSS at SemEval-2023 Task 10: Explainable Detection of Online Sexism Using Majority Voted Fine-Tuned Transformers

12:30-14:00 Lunch break

14:00-15:00 Poster Session III: System Description Papers (Queens Quay)
  • AdamR at SemEval-2023 Task 10: Solving the Class Imbalance Problem in Sexism Detection with Ensemble Learning
  • PoliToHFI at SemEval-2023 Task 6: Leveraging Entity-Aware and Hierarchical Transformers for Legal Entity Recognition and Court Judgment Prediction
  • NLP-LTU at SemEval-2023 Task 10: The Impact of Data Augmentation and Semi-Supervised Learning Techniques on Text Classification Performance on an Imbalanced Dataset
  • CL-UZH at SemEval-2023 Task 10: Sexism Detection through Incremental Fine-Tuning and Multi-Task Learning with Label Descriptions
  • Mr-wallace at SemEval-2023 Task 5: Novel Clickbait Spoiling Algorithm Using Natural Language Processing
  • Gallagher at SemEval-2023 Task 5: Tackling Clickbait with Seq2Seq Models
  • Arizonans at SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis with XLM-T
  • iLab at SemEval-2023 Task 11 Le-Wi-Di: Modelling Disagreement or Modelling Perspectives?
  • THiFLY Research at SemEval-2023 Task 7: A Multi-granularity System for CTR-based Textual Entailment and Evidence Retrieval
  • Hitachi at SemEval-2023 Task 3: Exploring Cross-lingual Multi-task Strategies for Genre and Framing Detection in Online News
  • Hitachi at SemEval-2023 Task 4: Exploring Various Task Formulations Reveals the Importance of Description Texts on Human Values
  • {FiRC at SemEval-2023 Task 10: Fine-grained Classification of Online Sexism Content Using DeBERTa
  • UCAS-IIE-NLP at SemEval-2023 Task 12: Enhancing Generalization of Multilingual BERT for Low-resource Sentiment Analysis
  • Sebis at SemEval-2023 Task 7: A Joint System for Natural Language Inference and Evidence Retrieval from Clinical Trial Reports
  • SzegedAI at SemEval-2023 Task 1: Applying Quasi-Symbolic Representations in Visual Word Sense Disambiguation
  • UAlberta at SemEval-2023 Task 1: Context Augmentation and Translation for Multilingual Visual Word Sense Disambiguation
  • TeamEC at SemEval-2023 Task 4: Transformers vs. Low-Resource Dictionaries, Expert Dictionary vs. Learned Dictionary
  • azaad@BND at SemEval-2023 Task 2: How to Go from a Simple Transformer Model to a Better Model to Get Better Results in Natural Language Processing

15:00-15:30 Coffee break

15:30-16:00 Best Paper Awards and Concluding Remarks