4 papers
Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations
Hao Chen, Ankit Shah, Jindong Wang +6
Learning with reduced labeling standards, such as noisy label, partial label, and multiple label candidates, which we generically refer to as \textit{imprecise} labels, is a common…
IRGen: Generative Modeling for Image Retrieval
Yidan Zhang, Ting Zhang, Dong Chen +11
While generative modeling has become prevalent across numerous research fields, its integration into the realm of image retrieval remains largely unexplored and underjustified. In…
PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts
Kaijie Zhu, Jindong Wang, Jiaheng Zhou +8
The increasing reliance on Large Language Models (LLMs) across academia and industry necessitates a comprehensive understanding of their robustness to prompts. In response to this…
PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization
Yidong Wang, Zhuohao Yu, Zhengran Zeng +10
Instruction tuning large language models (LLMs) remains a challenging task, owing to the complexity of hyperparameter selection and the difficulty involved in evaluating the tuned…