40 citations · 164 across the 23 of their papers we have counts for
7 papers · 1 filter
Efficiently Enhancing Zero-Shot Performance of Instruction Following Model via Retrieval of Soft Prompt
Seonghyeon Ye, Joel Jang, Doyoung Kim +2
Enhancing the zero-shot performance of instruction-following models requires heavy computation, either by scaling the total number of training datasets or the model size. In this w…
Guess the Instruction! Flipped Learning Makes Language Models Stronger Zero-Shot Learners
Seonghyeon Ye, Doyoung Kim, Joel Jang +2
Meta-training, which fine-tunes the language model (LM) on various downstream tasks by maximizing the likelihood of the target label given the task instruction and input instance,…
Knowledge Unlearning for Mitigating Privacy Risks in Language Models
Joel Jang, Dongkeun Yoon, Sohee Yang +4
Pretrained Language Models (LMs) memorize a vast amount of knowledge during initial pretraining, including information that may violate the privacy of personal lives and identities…
Can Large Language Models Truly Understand Prompts? A Case Study with Negated Prompts
Joel Jang, Seonghyeon Ye, Minjoon Seo
Previous work has shown that there exists a scaling law between the size of Language Models (LMs) and their zero-shot performance on different downstream NLP tasks. In this work, w…
Prompt Injection: Parameterization of Fixed Inputs
Eunbi Choi, Yongrae Jo, Joel Jang +1
Recent works have shown that attaching prompts to the input is effective at conditioning Language Models (LM) to perform specific tasks. However, prompts are always included in the…
TemporalWiki: A Lifelong Benchmark for Training and Evaluating Ever-Evolving Language Models
Joel Jang, Seonghyeon Ye, Changho Lee +5
Language Models (LMs) become outdated as the world changes; they often fail to perform tasks requiring recent factual information which was absent or different during training, a p…
Music2Video: Automatic Generation of Music Video with fusion of audio and text
Yoonjeon Kim, Joel Jang, Sumin Shin
Creation of images using generative adversarial networks has been widely adapted into multi-modal regime with the advent of multi-modal representation models pre-trained on large c…