35 citations · 52 across the 6 of their papers we have counts for
6 papers
Model-diff: A Tool for Comparative Study of Language Models in the Input Space
Weitang Liu, Yuelei Li, Ying Wai Li +2
Comparing two (large) language models (LMs) side-by-side and pinpointing their prediction similarities and differences on the same set of inputs are crucial in many real-world scen…
Evaluation of human-model prediction difference on the Internet Scale of Data
Weitang Liu, Ying Wai Li, Yuelei Li +3
Evaluating models on datasets often fails to capture their behavior when faced with unexpected and diverse types of inputs. It would be beneficial if we could evaluate the differen…
WOT-Class: Weakly Supervised Open-world Text Classification
Tianle Wang, Zihan Wang, Weitang Liu +1
State-of-the-art weakly supervised text classification methods, while significantly reduced the required human supervision, still requires the supervision to cover all the classes…
Gradient-based Wang-Landau Algorithm: A Novel Sampler for Output Distribution of Neural Networks over the Input Space
Weitang Liu, Ying-Wai Li, Yi-Zhuang You +1
The output distribution of a neural network (NN) over the entire input space captures the complete input-output mapping relationship, offering insights toward a more comprehensive…
Can multi-label classification networks know what they don't know?
Haoran Wang, Weitang Liu, Alex Bocchieri +1
Estimating out-of-distribution (OOD) uncertainty is a central challenge for safely deploying machine learning models in the open-world environment. Improved methods for OOD detecti…
Gunrock: GPU Graph Analytics
Yangzihao Wang, Yuechao Pan, Andrew Davidson +8
For large-scale graph analytics on the GPU, the irregularity of data access and control flow, and the complexity of programming GPUs, have presented two significant challenges to d…