In the past year, MultiModal Large Language Models (MM-LLMs) have undergone
substantial advancements, augmenting off-the-shelf LLMs to support MM inputs or outputs …

Misinformation such as fake news and rumors is a serious threat for information ecosystems
and public trust. The emergence of large language models (LLMs) has great potential to …

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 …

Modern artificial intelligence (AI) systems are powered by foundation models. This paper
presents a new set of foundation models, called Llama 3. It is a herd of language models …

Large vision-language models (VLMs) have recently achieved remarkable progress,
exhibiting impressive multimodal perception and reasoning abilities. However, effectively …

Modality alignment serves as the cornerstone for large multi-modal models (LMMs).
However, the impact of different attributes (eg, data type, quality, and scale) of training data …

In this report, we introduce Qwen2. 5, a comprehensive series of large language models
(LLMs) designed to meet diverse needs. Compared to previous iterations, Qwen 2.5 has …

In this paper, we introduce InternVL 1.5, an open-source multimodal large language model
(MLLM) to bridge the capability gap between open-source and proprietary commercial …

Efficient fine-tuning is vital for adapting large language models (LLMs) to downstream tasks.
However, it requires non-trivial efforts to implement these methods on different models. We …

As a primary means of information acquisition, information retrieval (IR) systems, such as
search engines, have integrated themselves into our daily lives. These systems also serve …