Large Language Models (LLMs) have recently demonstrated remarkable capabilities in
natural language processing tasks and beyond. This success of LLMs has led to a large …

Autonomous agents have long been a research focus in academic and industry
communities. Previous research often focuses on training agents with limited knowledge …

Language is essentially a complex, intricate system of human expressions governed by
grammatical rules. It poses a significant challenge to develop capable AI algorithms for …

In this paper, we initiate an attempt of developing an end-to-end chat-centric video
understanding system, coined as VideoChat. It integrates video foundation models and …

Large multimodal models (LMMs) extend large language models (LLMs) with multi-sensory
skills, such as visual understanding, to achieve stronger generic intelligence. In this paper …

Large Language Models (LLMs) have seen an impressive wave of advances recently, with
models now excelling in a variety of tasks, such as mathematical reasoning and program …

Artificial agents have traditionally been trained to maximize reward, which may incentivize
power-seeking and deception, analogous to how next-token prediction in language models …

Neural compression is the application of neural networks and other machine learning
methods to data compression. Recent advances in statistical machine learning have opened …

Integrating large language models (LLMs) with various tools has led to increased attention
in the field. Existing approaches either involve fine-tuning the LLM, which is both …

Recent research has highlighted the potential of large language models (LLMs) to improve
their problem-solving capabilities with the aid of suitable external tools. In our work, we …