19 citations · 33 across the 8 of their papers we have counts for
8 papers
VL-PET: Vision-and-Language Parameter-Efficient Tuning via Granularity Control
Zi-Yuan Hu, Yanyang Li, Michael R. Lyu +1
As the model size of pre-trained language models (PLMs) grows rapidly, full fine-tuning becomes prohibitively expensive for model training and storage. In vision-and-language (VL),…
CLEVA: Chinese Language Models EVAluation Platform
Yanyang Li, Jianqiao Zhao, Duo Zheng +8
With the continuous emergence of Chinese Large Language Models (LLMs), how to evaluate a model's capabilities has become an increasingly significant issue. The absence of a compreh…
Eliciting Knowledge from Large Pre-Trained Models for Unsupervised Knowledge-Grounded Conversation
Yanyang Li, Jianqiao Zhao, Michael R. Lyu +1
Recent advances in large-scale pre-training provide large models with the potential to learn knowledge from the raw text. It is thus natural to ask whether it is possible to levera…
Diverse Text Generation via Variational Encoder-Decoder Models with Gaussian Process Priors
Wanyu Du, Jianqiao Zhao, Liwei Wang +1
Generating high quality texts with high diversity is important for many NLG applications, but current methods mostly focus on building deterministic models to generate higher quali…
FlowEval: A Consensus-Based Dialogue Evaluation Framework Using Segment Act Flows
Jianqiao Zhao, Yanyang Li, Wanyu Du +4
Despite recent progress in open-domain dialogue evaluation, how to develop automatic metrics remains an open problem. We explore the potential of dialogue evaluation featuring dial…
JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs
Pei Ke, Haozhe Ji, Yu Ran +5
Existing pre-trained models for knowledge-graph-to-text (KG-to-text) generation simply fine-tune text-to-text pre-trained models such as BART or T5 on KG-to-text datasets, which la…
Improving Weakly Supervised Visual Grounding by Contrastive Knowledge Distillation
Liwei Wang, Jing Huang, Yin Li +3
Weakly supervised phrase grounding aims at learning region-phrase correspondences using only image-sentence pairs. A major challenge thus lies in the missing links between image re…
Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network
Kun Xu, Liwei Wang, Mo Yu +4
Previous cross-lingual knowledge graph (KG) alignment studies rely on entity embeddings derived only from monolingual KG structural information, which may fail at matching entities…