305 citations · 494 across the 14 of their papers we have counts for
14 papers
Generalizable Neural Fields as Partially Observed Neural Processes
Jeffrey Gu, Kuan-Chieh Wang, Serena Yeung
Neural fields, which represent signals as a function parameterized by a neural network, are a promising alternative to traditional discrete vector or grid-based representations. Co…
ToolQA: A Dataset for LLM Question Answering with External Tools
Yuchen Zhuang, Yue Yu, Kuan Wang +2
Large Language Models (LLMs) have demonstrated impressive performance in various NLP tasks, but they still suffer from challenges such as hallucination and weak numerical reasoning…
LOVM: Language-Only Vision Model Selection
Orr Zohar, Shih-Cheng Huang, Kuan-Chieh Wang +1
Pre-trained multi-modal vision-language models (VLMs) are becoming increasingly popular due to their exceptional performance on downstream vision applications, particularly in the…
Generation-Augmented Query Expansion For Code Retrieval
Dong Li, Yelong Shen, Ruoming Jin +3
Pre-trained language models have achieved promising success in code retrieval tasks, where a natural language documentation query is given to find the most relevant existing code s…
DiffusionBERT: Improving Generative Masked Language Models with Diffusion Models
Zhengfu He, Tianxiang Sun, Kuanning Wang +2
We present DiffusionBERT, a new generative masked language model based on discrete diffusion models. Diffusion models and many pre-trained language models have a shared training ob…
Grad2Task: Improved Few-shot Text Classification Using Gradients for Task Representation
Jixuan Wang, Kuan-Chieh Wang, Frank Rudzicz +1
Large pretrained language models (LMs) like BERT have improved performance in many disparate natural language processing (NLP) tasks. However, fine tuning such models requires a la…