As an effective strategy, data augmentation (DA) alleviates data scarcity scenarios where
deep learning techniques may fail. It is widely applied in computer vision then introduced to …

Recently, large language models (LLMs) have attracted considerable attention due to their
remarkable capabilities. However, LLMs' generation of biased or hallucinatory content …

Few-shot learning is a challenging task that requires language models to generalize from
limited examples. Large language models like GPT-3 and PaLM have made impressive …

The increasing scale of large language models (LLMs) brings emergent abilities to various
complex tasks requiring reasoning, such as arithmetic and commonsense reasoning. It is …

Data augmentation has recently seen increased interest in NLP due to more work in low-
resource domains, new tasks, and the popularity of large-scale neural networks that require …

Consistency of a model—that is, the invariance of its behavior under meaning-preserving
alternations in its input—is a highly desirable property in natural language processing. In …

Recently, Chain-of-Thought (CoT) prompting has delivered success on complex reasoning
tasks, which aims at designing a simple prompt like``Let's think step by step''or multiple in …

ChatGPT has gained a huge popularity since its introduction. Its positive aspects have been
reported through many media platforms, and some analyses even showed that ChatGPT …

While progress has been made on the visual question answering leaderboards, models
often utilize spurious correlations and priors in datasets under the iid setting. As such …

Reasoning over natural language is a long-standing goal for the research community.
However, studies have shown that existing language models are inadequate in reasoning …