activity
20202023
most citedOn the Robustness of Aspect-based Sentiment Analysis: Rethinking Model, Data, and Training

85 citations · 289 across the 27 of their papers we have counts for

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Showing cs.CLShow all

29 papers · 1 filter

cs.CL2023★ 17 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

DialogRE^C+: An Extension of DialogRE to Investigate How Much Coreference Helps Relation Extraction in Dialogs

Yiyun Xiong, Mengwei Dai, Fei Li +5

Dialogue relation extraction (DRE) that identifies the relations between argument pairs in dialogue text, suffers much from the frequent occurrence of personal pronouns, or entity…

cs.CL2023★ 2 cited

A Bi-directional Multi-hop Inference Model for Joint Dialog Sentiment Classification and Act Recognition

Li Zheng, Fei Li, Yuyang Chai +2

The joint task of Dialog Sentiment Classification (DSC) and Act Recognition (DAR) aims to predict the sentiment label and act label for each utterance in a dialog simultaneously. H…

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…

cs.CL2023★ 6 cited

TKDP: Threefold Knowledge-enriched Deep Prompt Tuning for Few-shot Named Entity Recognition

Jiang Liu, Hao Fei, Fei Li +5

Few-shot named entity recognition (NER) exploits limited annotated instances to identify named mentions. Effectively transferring the internal or external resources thus becomes th…

cs.CL2023★ 5 cited

ECQED: Emotion-Cause Quadruple Extraction in Dialogs

Li Zheng, Donghong Ji, Fei Li +5

The existing emotion-cause pair extraction (ECPE) task, unfortunately, ignores extracting the emotion type and cause type, while these fine-grained meta-information can be practica…