这个科学智能体模型能处理多模态数据，397B 版在时间序列预测上很强，还有个 4B 小模型能直接把生物任务分数拉高，适合搞科研的人看看。
Intern-S2-Preview 是一系列面向科学发现的智能体基础模型，支持多模态科学理解、推理、生成和长周期任务。训练流程包含科学多模态预训练、监督微调、多任务强化学习及智能体 RL，并引入部分 rollout、自适应长度正则化等技巧提升稳定性。其中 Intern-S2-Preview-397B 在 SciTS 时间序列基准上取得领先表现，同时其时间序列模块增强了科学信号理解与预测。独立的 Intern-MemDec-4B 扩展将 Biology-Instructions 平均分从 56.92 提升至 60.32，且无需修改冻结的 397B 主干。
Intern-S2-Preview: Scientific Agentic Foundation Model
Scientific discovery increasingly requires AI systems that can reason over scientific evidence of heterogeneous modalities, interact with scientific tools and environments, and sustain progress across long task horizons. We present Intern-S2-Preview, a series of scientific agentic foundation models designed to support multimodal scientific understanding, reasoning, generation, and long-horizon tasks. The training pipeline begins with scientific multimodal pre-training over rendered scientific documents, interleaved image-text data, and diverse scientific corpora. Starting from the pretrained checkpoint, we apply a unified post-training pipeline consisting of supervised fine-tuning, scalable multi-task reinforcement learning (RL), black- and white-box agentic RL, and on-policy distillation. This pipeline is supported by practical techniques that improve rollout and training stability and efficiency, including partial rollout with off-policy correction, adaptive length regularization, online speculative decoding, robust multi-task optimization, and trace-aware experience assembly for agentic tasks. At the architecture level, Intern-S2-Preview-397B extends time series modelling from efficient long-sequence understanding to numerical forecasting, while Memory Decoder is studied as a separate memory-augmented path for rapid scientific specialization without modifying the frozen 397B backbone. Evaluations across scientific, multimodal, agentic, and general-purpose benchmarks show that Intern-S2-Preview-397B achieves competitive or leading results in multiple settings. The time series modules improve scientific signal understanding and forecasting on SciTS, while the separate Intern-MemDec-4B extension improves the Biology-Instructions average score from 56.92 to 60.32 without modifying the frozen 397B backbone.