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20212023
most citedOn the Robustness of Aspect-based Sentiment Analysis: Rethinking Model, Data, and Training

85 citations · 268 across the 14 of their papers we have counts for

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14 papers · 1 filter

cs.CL2024

Revisiting Structured Sentiment Analysis as Latent Dependency Graph Parsing

Chengjie Zhou, Bobo Li, Hao Fei +3

Structured Sentiment Analysis (SSA) was cast as a problem of bi-lexical dependency graph parsing by prior studies. Multiple formulations have been proposed to construct the graph,…

cs.CL2024

Modeling Unified Semantic Discourse Structure for High-quality Headline Generation

Minghui Xu, Hao Fei, Fei Li +4

Headline generation aims to summarize a long document with a short, catchy title that reflects the main idea. This requires accurately capturing the core document semantics, which…

cs.CL20241 cited

In-Context Learning for Few-Shot Nested Named Entity Recognition

Meishan Zhang, Bin Wang, Hao Fei +1

In nested Named entity recognition (NER), entities are nested with each other, and thus requiring more data annotations to address. This leads to the development of few-shot nested…

cs.CL2023

Reverse Multi-Choice Dialogue Commonsense Inference with Graph-of-Thought

Li Zheng, Hao Fei, Fei Li +4

With the proliferation of dialogic data across the Internet, the Dialogue Commonsense Multi-choice Question Answering (DC-MCQ) task has emerged as a response to the challenge of co…

cs.CL202317 cited

Revisiting Disentanglement and Fusion on Modality and Context in Conversational Multimodal Emotion Recognition

Bobo Li, Hao Fei, Lizi Liao +5

It has been a hot research topic to enable machines to understand human emotions in multimodal contexts under dialogue scenarios, which is tasked with multimodal emotion analysis i…

cs.CL2023

Revisiting Conversation Discourse for Dialogue Disentanglement

Bobo Li, Hao Fei, Fei Li +5

Dialogue disentanglement aims to detach the chronologically ordered utterances into several independent sessions. Conversation utterances are essentially organized and described by…