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Found 8 papers, 0 papers with code
Long-range Sequence Modeling with Predictable Sparse Attention
(2) A sparse attention matrix estimation module, which predicts dominant elements of an attention matrix based on the output of the previous hidden state cross module.
A Unified Label-Aware Contrastive Learning Framework for Few-Shot Named Entity Recognition
Our approach enriches the context by utilizing label semantics as suffix prompts.
Samsung Research China-Beijing at SemEval-2024 Task 3: A multi-stage framework for Emotion-Cause Pair Extraction in Conversations
In human-computer interaction, it is crucial for agents to respond to human by understanding their emotions.
TA-MAMC at SemEval-2021 Task 4: Task-adaptive Pretraining and Multi-head Attention for Abstract Meaning Reading Comprehension
This paper describes our system used in the SemEval-2021 Task4 Reading Comprehension of Abstract Meaning, achieving 1st for subtask 1 and 2nd for subtask 2 on the leaderboard.
LIT Team's System Description for Japanese-Chinese Machine Translation Task in IWSLT 2020
This paper describes the LIT Team{'}s submission to the IWSLT2020 open domain translation task, focusing primarily on Japanese-to-Chinese translation direction.
Token-level Dynamic Self-Attention Network for Multi-Passage Reading Comprehension
Multi-passage reading comprehension requires the ability to combine cross-passage information and reason over multiple passages to infer the answer.
Yimmon at SemEval-2019 Task 9: Suggestion Mining with Hybrid Augmented Approaches
This paper gives a detailed system description of our submission in SemEval 2019 Task 9 Subtask A.
Quantifying Context Overlap for Training Word Embeddings
Most models for learning word embeddings are trained based on the context information of words, more precisely first order co-occurrence relations.
