most citedAnalyzing Modality Robustness in Multimodal Sentiment Analysis

3 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2022

Generative Prompt Tuning for Relation Classification

Jiale Han, Shuai Zhao, Bo Cheng +2

Using prompts to explore the knowledge contained within pre-trained language models for downstream tasks has now become an active topic. Current prompt tuning methods mostly conver…

cs.CL20223 cited

Analyzing Modality Robustness in Multimodal Sentiment Analysis

Devamanyu Hazarika, Yingting Li, Bo Cheng +3

Building robust multimodal models are crucial for achieving reliable deployment in the wild. Despite its importance, less attention has been paid to identifying and improving the r…

cs.CL2022

Exploring Entity Interactions for Few-Shot Relation Learning (Student Abstract)

YI Liang, Shuai Zhao, Bo Cheng +2

Few-shot relation learning refers to infer facts for relations with a limited number of observed triples. Existing metric-learning methods for this problem mostly neglect entity in…

cs.CL2021

FCM: A Fine-grained Comparison Model for Multi-turn Dialogue Reasoning

Xu Wang, Hainan Zhang, Shuai Zhao +5

Despite the success of neural dialogue systems in achieving high performance on the leader-board, they cannot meet users' requirements in practice, due to their poor reasoning skil…

cs.CL2021

Integrating Subgraph-aware Relation and DirectionReasoning for Question Answering

Xu Wang, Shuai Zhao, Bo Cheng +5

Question Answering (QA) models over Knowledge Bases (KBs) are capable of providing more precise answers by utilizing relation information among entities. Although effective, most o…