Abstract Automated Planning and Scheduling is among the growing areas in Artificial
Intelligence (AI) where mention of LLMs has gained popularity. Based on a comprehensive …

This survey presents an in-depth exploration of knowledge distillation (KD) techniques
within the realm of Large Language Models (LLMs), spotlighting the pivotal role of KD in …

We introduce a pipeline that enhances a general-purpose Vision Language Model, GPT-4V
(ision), by integrating observations of human actions to facilitate robotic manipulation. This …

Multilingual Large Language Models are capable of using powerful Large Language
Models to handle and respond to queries in multiple languages, which achieves remarkable …

Large language models (LLMs) are leading significant progress in code generation. Beyond
one-pass code generation, recent works further integrate unit tests and program verifiers into …

While large language models (LLMs) like ChatGPT have shown impressive capabilities in
Natural Language Processing (NLP) tasks, a systematic investigation of their potential in this …

Robotic behavior synthesis, the problem of understanding multimodal inputs and generating
precise physical control for robots, is an important part of Embodied AI. Despite successes in …

Multi-modal Chain-of-Thought (MCoT) requires models to leverage knowledge from both
textual and visual modalities for step-by-step reasoning, which gains increasing attention …

Learning reward functions remains the bottleneck to equip a robot with a broad repertoire of
skills. Large Language Models (LLM) contain valuable task-related knowledge that can …

Grounding the reasoning ability of large language models (LLMs) for embodied tasks is
challenging due to the complexity of the physical world. Especially, LLM planning for multi …