Large language model as attributed training data generator: A tale of diversity and bias
Large language models (LLMs) have been recently leveraged as training data generators
for various natural language processing (NLP) tasks. While previous research has explored …
for various natural language processing (NLP) tasks. While previous research has explored …
Generating training data with language models: Towards zero-shot language understanding
Pretrained language models (PLMs) have demonstrated remarkable performance in various
natural language processing tasks: Unidirectional PLMs (eg, GPT) are well known for their …
natural language processing tasks: Unidirectional PLMs (eg, GPT) are well known for their …
Text classification using label names only: A language model self-training approach
Current text classification methods typically require a good number of human-labeled
documents as training data, which can be costly and difficult to obtain in real applications …
documents as training data, which can be costly and difficult to obtain in real applications …
Tuning language models as training data generators for augmentation-enhanced few-shot learning
Recent studies have revealed the intriguing few-shot learning ability of pretrained language
models (PLMs): They can quickly adapt to a new task when fine-tuned on a small amount of …
models (PLMs): They can quickly adapt to a new task when fine-tuned on a small amount of …
Interactive continual learning: Fast and slow thinking
B Qi, X Chen, J Gao, D Li, J Liu… - Proceedings of the …, 2024 - openaccess.thecvf.com
Advanced life forms sustained by the synergistic interaction of neural cognitive mechanisms
continually acquire and transfer knowledge throughout their lifespan. In contrast …
continually acquire and transfer knowledge throughout their lifespan. In contrast …
Scimine: An efficient systematic prioritization model based on richer semantic information
Systematic review is a crucial method that has been widely used. by scholars from different
research domains. However, screening for relevant scientific literature from paper …
research domains. However, screening for relevant scientific literature from paper …
Weakly supervised temporal sentence grounding with uncertainty-guided self-training
The task of weakly supervised temporal sentence grounding aims at finding the
corresponding temporal moments of a language description in the video, given video …
corresponding temporal moments of a language description in the video, given video …
Topic discovery via latent space clustering of pretrained language model representations
Topic models have been the prominent tools for automatic topic discovery from text corpora.
Despite their effectiveness, topic models suffer from several limitations including the inability …
Despite their effectiveness, topic models suffer from several limitations including the inability …
Distantly-supervised named entity recognition with noise-robust learning and language model augmented self-training
We study the problem of training named entity recognition (NER) models using only distantly-
labeled data, which can be automatically obtained by matching entity mentions in the raw …
labeled data, which can be automatically obtained by matching entity mentions in the raw …
Contextualized weak supervision for text classification
Weakly supervised text classification based on a few user-provided seed words has recently
attracted much attention from researchers. Existing methods mainly generate pseudo-labels …
attracted much attention from researchers. Existing methods mainly generate pseudo-labels …