12 citations · 19 across the 6 of their papers we have counts for
7 papers
Could Giant Pretrained Image Models Extract Universal Representations?
Yutong Lin, Ze Liu, Zheng Zhang +4
Frozen pretrained models have become a viable alternative to the pretraining-then-finetuning paradigm for transfer learning. However, with frozen models there are relatively few pa…
Social Interpretable Tree for Pedestrian Trajectory Prediction
Liushuai Shi, Le Wang, Chengjiang Long +4
Understanding the multiple socially-acceptable future behaviors is an essential task for many vision applications. In this paper, we propose a tree-based method, termed as Social I…
Test-time Batch Normalization
Tao Yang, Shenglong Zhou, Yuwang Wang +2
Deep neural networks often suffer the data distribution shift between training and testing, and the batch statistics are observed to reflect the shift. In this paper, targeting of…
Input-Tuning: Adapting Unfamiliar Inputs to Frozen Pretrained Models
Shengnan An, Yifei Li, Zeqi Lin +6
Recently the prompt-tuning paradigm has attracted significant attention. By only tuning continuous prompts with a frozen pre-trained language model (PLM), prompt-tuning takes a ste…
Improved Drug-target Interaction Prediction with Intermolecular Graph Transformer
Siyuan Liu, Yusong Wang, Tong Wang +6
The identification of active binding drugs for target proteins (termed as drug-target interaction prediction) is the key challenge in virtual screening, which plays an essential ro…
Learning Algebraic Recombination for Compositional Generalization
Chenyao Liu, Shengnan An, Zeqi Lin +6
Neural sequence models exhibit limited compositional generalization ability in semantic parsing tasks. Compositional generalization requires algebraic recombination, i.e., dynamica…