Search Results for author:
Found 19 papers, 8 papers with code
Knowledge Distillation with Reptile Meta-Learning for Pretrained Language Model Compression
The teacher can continuously meta-learn the student’s learning objective to adjust its parameters for maximizing the student’s performance throughout the distillation process.
YNU-HPCC at SemEval-2022 Task 5: Multi-Modal and Multi-label Emotion Classification Based on LXMERT
We use Faster-RCNN to extract visual representation and utilize LXMERT’s cross-attention for multi-modal alignment.
YNU-HPCC at SemEval-2022 Task 6: Transformer-based Model for Intended Sarcasm Detection in English and Arabic
As participants in Task 6 (titled “iSarcasmEval: Intended Sarcasm Detection In English and Arabic”), we implement the sentiment system for all three subtasks in English and Arabic.
Accelerating Inference for Pretrained Language Models by Unified Multi-Perspective Early Exiting
To address this limitation, a unified horizontal and vertical multi-perspective early exiting (MPEE) framework is proposed in this study to accelerate the inference of transformer-based models.
YNU-HPCC at SemEval-2022 Task 2: Representing Multilingual Idiomaticity based on Contrastive Learning
However, for subtask A of idiomaticity detection, we simply did a few explorations and experiments based on the xlm-RoBERTa model.
YNU-HPCC at SemEval-2022 Task 4: Finetuning Pretrained Language Models for Patronizing and Condescending Language Detection
For the multi-label classification, we use the fine-tuned BERT model to extract the sentiment score of the text and a fully connected layer to classify the text into the PCL categories.
YNU-HPCC at ROCLING 2022 Shared Task: A Transformer-based Model with Focal Loss and Regularization Dropout for Chinese Healthcare Named Entity Recognition
This paper adopts a transformer-based model with focal Loss and regularization dropout.
YNU-HPCC at SemEval-2022 Task 8: Transformer-based Ensemble Model for Multilingual News Article Similarity
This paper describes the system submitted by our team (YNU-HPCC) to SemEval-2022 Task 8: Multilingual news article similarity.
Personalized LoRA for Human-Centered Text Understanding
Effectively and efficiently adapting a pre-trained language model (PLM) for human-centered text understanding (HCTU) is challenging since user tokens are million-level in most personalized applications and do not have concrete explicit semantics.
Learning to Memorize Entailment and Discourse Relations for Persona-Consistent Dialogues
Both memories collaborate to obtain entailment and discourse representation for the generation, allowing a deeper understanding of both consistency and coherence.
Ranked #1 on
Dialogue Generation
on Persona-Chat
(using extra training data)
YNU-HPCC at SemEval-2021 Task 6: Combining ALBERT and Text-CNN for Persuasion Detection in Texts and Images
In recent years, memes combining image and text have been widely used in social media, and memes are one of the most popular types of content used in online disinformation campaigns.
YNU-HPCC at SemEval-2021 Task 10: Using a Transformer-based Source-Free Domain Adaptation Model for Semantic Processing
To address the issue, the organizers provided the models that fine-tuned a large number of source domain data on pre-trained models and the dev data for participants.
YNU-HPCC at SemEval-2021 Task 11: Using a BERT Model to Extract Contributions from NLP Scholarly Articles
This paper describes the system we built as the YNU-HPCC team in the SemEval-2021 Task 11: NLPContributionGraph.
YNU-HPCC at SemEval-2021 Task 5: Using a Transformer-based Model with Auxiliary Information for Toxic Span Detection
In this paper, a transformer-based model with auxiliary information is proposed for SemEval-2021 Task 5.
YNU-HPCC at SemEval-2020 Task 10: Using a Multi-granularity Ordinal Classification of the BiLSTM Model for Emphasis Selection
In this study, we propose a multi-granularity ordinal classification method to address the problem of emphasis selection.
Graph Attention Network with Memory Fusion for Aspect-level Sentiment Analysis
Recent studies used attention-based methods that can effectively improve the performance of aspect-level sentiment analysis.
YNU-HPCC at SemEval-2020 Task 7: Using an Ensemble BiGRU Model to Evaluate the Humor of Edited News Titles
This paper describes an ensemble model designed for Semeval-2020 Task 7.
HPCC-YNU at SemEval-2020 Task 9: A Bilingual Vector Gating Mechanism for Sentiment Analysis of Code-Mixed Text
In this paper, we (my codalab username is kongjun) present a system that uses a bilingual vector gating mechanism for bilingual resources to complete the task.
