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Found 7 papers, 4 papers with code
RECALL: A Benchmark for LLMs Robustness against External Counterfactual Knowledge
Therefore, to evaluate the ability of LLMs to discern the reliability of external knowledge, we create a benchmark from existing knowledge bases.
A Unified Framework for Multi-intent Spoken Language Understanding with prompting
Multi-intent Spoken Language Understanding has great potential for widespread implementation.
Incorporating Hierarchy into Text Encoder: a Contrastive Learning Approach for Hierarchical Text Classification
Hierarchical text classification is a challenging subtask of multi-label classification due to its complex label hierarchy.
Zero-shot Cross-lingual Transfer of Prompt-based Tuning with a Unified Multilingual Prompt
To collocate with the unified prompt, we propose a new initialization method for the target label word to further improve the model's transferability across languages.
First Target and Opinion then Polarity: Enhancing Target-opinion Correlation for Aspect Sentiment Triplet Extraction
Aspect Sentiment Triplet Extraction (ASTE) aims to extract triplets from a sentence, including target entities, associated sentiment polarities, and opinion spans which rationalize the polarities.
Ranked #8 on
Aspect Sentiment Triplet Extraction
on ASTE-Data-V2
Syntax-Aware Graph Attention Network for Aspect-Level Sentiment Classification
In this paper, we exploit syntactic awareness to the model by the graph attention network on the dependency tree structure and external pre-training knowledge by BERT language model, which helps to model the interaction between the context and aspect words better.
Text Level Graph Neural Network for Text Classification
Recently, researches have explored the graph neural network (GNN) techniques on text classification, since GNN does well in handling complex structures and preserving global information.
Ranked #2 on
Text Classification
on Ohsumed
