4 papers
ScaleNet: Scaling up Pretrained Neural Networks with Incremental Parameters
Zhiwei Hao, Jianyuan Guo, Li Shen +4
Recent advancements in vision transformers (ViTs) have demonstrated that larger models often achieve superior performance. However, training these models remains computationally in…
Robust Knowledge Editing via Explicit Reasoning Chains for Distractor-Resilient Multi-Hop QA
Yuchen Wu, Liang Ding, Li Shen +1
Large language models (LLMs) encode vast amounts of world knowledge but remain static once trained, making the timely integration of emerging facts prohibitively expensive via full…
Cross-Domain Diffusion with Progressive Alignment for Efficient Adaptive Retrieval
Junyu Luo, Yusheng Zhao, Xiao Luo +5
Unsupervised efficient domain adaptive retrieval aims to transfer knowledge from a labeled source domain to an unlabeled target domain, while maintaining low storage cost and high…
Dynamic Analysis and Adaptive Discriminator for Fake News Detection
Xinqi Su, Zitong Yu, Yawen Cui +7
In current web environment, fake news spreads rapidly across online social networks, posing serious threats to society. Existing multimodal fake news detection methods can generall…