Warning: this paper contains content that maybe offensive or upsetting. Recent research in
Natural Language Processing (NLP) has advanced the development of various toxicity …

Due to the natural multi-modal occurrence format (text, audio, vision) of the dialogues,
textual response generation in dialogues should rely on the multi-modal contexts beyond …

While large language models (LLMs) have demonstrated strong capability in structured
prediction tasks such as semantic parsing, few amounts of research have explored the …

The emergence of the transformer architecture has ushered in a new era of possibilities,
showcasing remarkable capabilities in generative tasks exemplified by models like GPT4o …

As large language models (LLMs) become easily accessible nowadays, the trade-off
between safety and helpfulness can significantly impact user experience. A model that …

As it is cumbersome and expensive to acquire a huge amount of data for training neural
dialog models, data augmentation is proposed to effectively utilize existing training samples …

Language models are often used as the backbone of modern dialogue systems. These
models are pre-trained on large amounts of written fluent language. Repetition is typically …

Due to the prevalent application of machine learning (ML) techniques and the intrinsic black-
box nature of ML models, the need for good explanations that are sufficient and necessary …

Explaining the decisions of AI has become vital for fostering appropriate user trust in these
systems. This paper investigates explanations for a structured prediction task called``text-to …

Large language models (LLMs) have shown strong arithmetic reasoning capabilities when
prompted with Chain-of-Thought (CoT) prompts. However, we have only a limited …