Abstract: Large language models (LLMs) and multimodal models (MMs) have exhibited impressive capabilities in various domains, particularly in general language understanding and visual reasoning.

🔥 Core Discovery: Visual generation capability naturally arises from understanding! With just 200K samples + co-training, LLMs can be taught to generate visual embeddings without extensive ...

Whether it is a 0.8B model running on a smartphone or a 9B model powering a coding terminal, the Qwen3.5 series is effectively democratizing the "agentic era." ...

Together Computer Inc. today launched a major update to its Fine-Tuning Platform aimed at making it cheaper and easier for developers to adapt open-source large language models over time. The startup, ...

Pre-trained LLMs require instruction tuning to align with human preferences. Still, the vast data collection and rapid model iteration often lead to oversaturation, making efficient data selection a ...

Large language models (LLMs) have demonstrated remarkable capabilities in natural language processing (NLP) tasks, yet they face significant challenges when applied to educational contexts. This paper ...

Have you ever wished AI could truly understand the complexities of your field—not just replicate data but reason through intricate, domain-specific challenges? Whether you’re a researcher analyzing ...