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Found 16 papers, 1 papers with code
PALI at SemEval-2022 Task 7: Identifying Plausible Clarifications of Implicit and Underspecified Phrases in Instructional Texts
This paper describes our system used in the SemEval-2022 Task 7(Roth et al.): Identifying Plausible Clarifications of Implicit and Under-specified Phrases.
stce at SemEval-2022 Task 6: Sarcasm Detection in English Tweets
This paper describes the systematic approach applied in “SemEval-2022 Task 6 (iSarcasmEval) : Intended Sarcasm Detection in English and Arabic”.
PAIC at SemEval-2022 Task 5: Multi-Modal Misogynous Detection in MEMES with Multi-Task Learning And Multi-model Fusion
This paper describes our system used in the SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification (MAMI).
VarMAE: Pre-training of Variational Masked Autoencoder for Domain-adaptive Language Understanding
Pre-trained language models have achieved promising performance on general benchmarks, but underperform when migrated to a specific domain.
PALI-NLP at SemEval-2022 Task 4: Discriminative Fine-tuning of Transformers for Patronizing and Condescending Language Detection
Patronizing and condescending language (PCL) has a large harmful impact and is difficult to detect, both for human judges and existing NLP systems.
Ranked #1 on
Binary Condescension Detection
on DPM
Binary Condescension Detection
Multi-label Condescension Detection
+2
MM-DFN: Multimodal Dynamic Fusion Network for Emotion Recognition in Conversations
For multimodal ERC, it is vital to understand context and fuse modality information in conversations.
Ranked #23 on
Emotion Recognition in Conversation
on IEMOCAP
Sequential Attention Module for Natural Language Processing
In this paper, we target at how to further improve the token representations on the language models.
RG PA at SemEval-2021 Task 1: A Contextual Attention-based Model with RoBERTa for Lexical Complexity Prediction
In this paper we propose a contextual attention based model with two-stage fine-tune training using RoBERTa.
FPAI at SemEval-2021 Task 6: BERT-MRC for Propaganda Techniques Detection
The objective of subtask 2 of SemEval-2021 Task 6 is to identify techniques used together with the span(s) of text covered by each technique.
RefBERT: Compressing BERT by Referencing to Pre-computed Representations
Differently, in this paper, we propose RefBERT to leverage the knowledge learned from the teacher, i. e., facilitating the pre-computed BERT representation on the reference sample and compressing BERT into a smaller student model.
PALI at SemEval-2021 Task 2: Fine-Tune XLM-RoBERTa for Word in Context Disambiguation
Second, we construct a new vector on the fine-tuned embeddings from XLM-RoBERTa and feed it to a fully-connected network to output the probability of whether the target word in the context has the same meaning or not.
MagicPai at SemEval-2021 Task 7: Method for Detecting and Rating Humor Based on Multi-Task Adversarial Training
This paper describes MagicPai's system for SemEval 2021 Task 7, HaHackathon: Detecting and Rating Humor and Offense.
Sattiy at SemEval-2021 Task 9: An Ensemble Solution for Statement Verification and Evidence Finding with Tables
Question answering from semi-structured tables can be seen as a semantic parsing task and is significant and practical for pushing the boundary of natural language understanding.
FPAI at SemEval-2020 Task 10: A Query Enhanced Model with RoBERTa for Emphasis Selection
This paper describes the model we apply in the SemEval-2020 Task 10.
