84 citations · 85 across the 6 of their papers we have counts for
6 papers
Estimating Commonsense Plausibility through Semantic Shifts
Wanqing Cui, Wei Huang, Keping Bi +2
Commonsense plausibility estimation is critical for evaluating language models (LMs), yet existing generative approaches--reliant on likelihoods or verbalized judgments--struggle w…
LINKAGE: Listwise Ranking among Varied-Quality References for Non-Factoid QA Evaluation via LLMs
Sihui Yang, Keping Bi, Wanqing Cui +2
Non-Factoid (NF) Question Answering (QA) is challenging to evaluate due to diverse potential answers and no objective criterion. The commonly used automatic evaluation metrics like…
MVAM: Multi-View Attention Method for Fine-grained Image-Text Matching
Wanqing Cui, Rui Cheng, Jiafeng Guo +1
Existing two-stream models, such as CLIP, encode images and text through independent representations, showing good performance while ensuring retrieval speed, have attracted attent…
MORE: Multi-mOdal REtrieval Augmented Generative Commonsense Reasoning
Wanqing Cui, Keping Bi, Jiafeng Guo +1
Since commonsense information has been recorded significantly less frequently than its existence, language models pre-trained by text generation have difficulty to learn sufficient…
WenLan: Bridging Vision and Language by Large-Scale Multi-Modal Pre-Training
Yuqi Huo, Manli Zhang, Guangzhen Liu +32
Multi-modal pre-training models have been intensively explored to bridge vision and language in recent years. However, most of them explicitly model the cross-modal interaction bet…
Beyond Language: Learning Commonsense from Images for Reasoning
Wanqing Cui, Yanyan Lan, Liang Pang +2
This paper proposes a novel approach to learn commonsense from images, instead of limited raw texts or costly constructed knowledge bases, for the commonsense reasoning problem in…