The field of artificial intelligence is witnessing significant advancements in real-time reasoning and multimodal agents. Researchers are focusing on developing agents that can make timely and logical judgments in dynamic environments, integrating multiple capabilities such as perception, search, and reasoning. The introduction of new problem formulations, benchmarks, and evaluation protocols is driving progress in this area. Notable developments include the proposal of real-time reasoning as a critical testbed for developing practical agents and the introduction of agentic multimodal models that can actively invoke external tools and integrate operations into reasoning.

Some noteworthy papers in this regard include: Real-Time Reasoning Agents in Evolving Environments, which introduces AgileThinker, a model that balances reasoning depth and response latency. DeepEyesV2: Toward Agentic Multimodal Model, which explores the development of an agentic multimodal model and introduces RealX-Bench, a comprehensive benchmark for evaluating real-world multimodal reasoning.