Multimodal Queries Require Multimodal RAG: Researchers from KAIST and DeepAuto.ai Propose UniversalRAG—A New Framework That Dynamically Routes Across Modalities and Granularities for Accurate and Efficient Retrieval-Augmented Generation

RAG has proven effective in enhancing the factual accuracy of LLMs by grounding their outputs in external, relevant information. However, […]

Google Researchers Advance Diagnostic AI: AMIE Now Matches or Outperforms Primary Care Physicians Using Multimodal Reasoning with Gemini 2.0 Flash

LLMs have shown impressive promise in conducting diagnostic conversations, particularly through text-based interactions. However, their evaluation and application have largely […]

Training LLM Agents Just Got More Stable: Researchers Introduce StarPO-S and RAGEN to Tackle Multi-Turn Reasoning and Collapse in Reinforcement Learning

Large language models (LLMs) face significant challenges when trained as autonomous agents in interactive environments. Unlike static tasks, agent settings […]