most citedStructural Bias for Aspect Sentiment Triplet Extraction

7 citations · 10 across the 6 of their papers we have counts for

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cs.CL2026

Orthogonal Representation Editing: Decoupling Semantic Entanglement in Batch Knowledge Editing of LLMs

Wenhao Yu, Zhicong Lu, Bo Lv +4

Knowledge editing aims to efficiently update factual information in Large Language Models (LLMs) without full retraining. However, existing methods still suffer from performance de…

cs.CL2022★ 2 cited

XPrompt: Exploring the Extreme of Prompt Tuning

Fang Ma, Chen Zhang, Lei Ren +5

Prompt tuning learns soft prompts to condition frozen Pre-trained Language Models (PLMs) for performing downstream tasks in a parameter-efficient manner. While prompt tuning has gr…

cs.CL2022★ 7 cited

Structural Bias for Aspect Sentiment Triplet Extraction

Chen Zhang, Lei Ren, Fang Ma +3

Structural bias has recently been exploited for aspect sentiment triplet extraction (ASTE) and led to improved performance. On the other hand, it is recognized that explicitly inco…

cs.CL2022★ 1 cited

A Multibias-mitigated and Sentiment Knowledge Enriched Transformer for Debiasing in Multimodal Conversational Emotion Recognition

Jinglin Wang, Fang Ma, Yazhou Zhang +1

Multimodal emotion recognition in conversations (mERC) is an active research topic in natural language processing (NLP), which aims to predict human's emotional states in communica…

cs.CL2022

Aspect-specific Context Modeling for Aspect-based Sentiment Analysis

Fang Ma, Chen Zhang, Bo Zhang +1

Aspect-based sentiment analysis (ABSA) aims at predicting sentiment polarity (SC) or extracting opinion span (OE) expressed towards a given aspect. Previous work in ABSA mostly rel…