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 …

Mathematical reasoning is a fundamental aspect of human intelligence and is applicable in
various fields, including science, engineering, finance, and everyday life. The development …

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 …

Multimodal Large Language Model (MLLM) recently has been a new rising research
hotspot, which uses powerful Large Language Models (LLMs) as a brain to perform …

How to efficiently transform large language models (LLMs) into instruction followers is
recently a popular research direction, while training LLM for multi-modal reasoning remains …

For a long time, humanity has pursued artificial intelligence (AI) equivalent to or surpassing
the human level, with AI agents considered a promising vehicle for this pursuit. AI agents are …

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 shown impressive performance on complex reasoning
by leveraging chain-of-thought (CoT) prompting to generate intermediate reasoning chains …

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

Attaining a high degree of user controllability in visual generation often requires intricate,
fine-grained inputs like layouts. However, such inputs impose a substantial burden on users …