48 citations · 60 across the 12 of their papers we have counts for
7 papers · 1 filter
Active Instruction Tuning: Improving Cross-Task Generalization by Training on Prompt Sensitive Tasks
Po-Nien Kung, Fan Yin, Di Wu +2
Instruction tuning (IT) achieves impressive zero-shot generalization results by training large language models (LLMs) on a massive amount of diverse tasks with instructions. Howeve…
Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations
Hammaad Adam, Fan Yin, Huibin +5
Randomized experiments often need to be stopped prematurely due to the treatment having an unintended harmful effect. Existing methods that determine when to stop an experiment ear…
Did You Read the Instructions? Rethinking the Effectiveness of Task Definitions in Instruction Learning
Fan Yin, Jesse Vig, Philippe Laban +3
Large language models (LLMs) have shown impressive performance in following natural language instructions to solve unseen tasks. However, it remains unclear whether models truly un…
Efficient Shapley Values Estimation by Amortization for Text Classification
Chenghao Yang, Fan Yin, He He +3
Despite the popularity of Shapley Values in explaining neural text classification models, computing them is prohibitive for large pretrained models due to a large number of model e…
Red Teaming Language Model Detectors with Language Models
Zhouxing Shi, Yihan Wang, Fan Yin +3
The prevalence and strong capability of large language models (LLMs) present significant safety and ethical risks if exploited by malicious users. To prevent the potentially decept…
Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation
Da Yin, Xiao Liu, Fan Yin +4
Instruction tuning has emerged to enhance the capabilities of large language models (LLMs) to comprehend instructions and generate appropriate responses. Existing methods either ma…
CleanCLIP: Mitigating Data Poisoning Attacks in Multimodal Contrastive Learning
Hritik Bansal, Nishad Singhi, Yu Yang +3
Multimodal contrastive pretraining has been used to train multimodal representation models, such as CLIP, on large amounts of paired image-text data. However, previous studies have…