3 citations · 4 across the 4 of their papers we have counts for
4 papers
NLPBench: Evaluating Large Language Models on Solving NLP Problems
Linxin Song, Jieyu Zhang, Lechao Cheng +3
Recent developments in large language models (LLMs) have shown promise in enhancing the capabilities of natural language processing (NLP). Despite these successes, there remains a…
Taming Small-sample Bias in Low-budget Active Learning
Linxin Song, Jieyu Zhang, Xiaotian Lu +1
Active learning (AL) aims to minimize the annotation cost by only querying a few informative examples for each model training stage. However, training a model on a few queried exam…
Leveraging Instance Features for Label Aggregation in Programmatic Weak Supervision
Jieyu Zhang, Linxin Song, Alexander Ratner
Programmatic Weak Supervision (PWS) has emerged as a widespread paradigm to synthesize training labels efficiently. The core component of PWS is the label model, which infers true…
Adaptive Ranking-based Sample Selection for Weakly Supervised Class-imbalanced Text Classification
Linxin Song, Jieyu Zhang, Tianxiang Yang +1
To obtain a large amount of training labels inexpensively, researchers have recently adopted the weak supervision (WS) paradigm, which leverages labeling rules to synthesize traini…