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WOVEN 提出了一个面向视觉转移推理的训练数据源与基准，涵盖 20 种场景、5 种动作和 8 种推理类型共 36,076 个样本，并对 38 个前沿多模态大模型进行了评测。研究发现训练后的能力可广泛迁移到 26 个外部基准中的 22 个，最高提升 27.3 个百分点，并总结出一套可复用的视觉世界建模训练配方。
This paper from Salesforce audits public RL environments for terminal agents, finding significant defects, and introduces RIVER, a training recipe that filters defective environments and penalizes repetitive behavior to enhance model performance.
A detailed write-up on training a 210M text-to-image diffusion transformer from scratch on a single GPU, sharing key measurements on attention sinks, loss as a health signal, and timestep shifting benefits.
Announcement of a blog post explaining the design of BarunLM, a 35M-parameter language model, covering its architecture, training recipe, and dataset preparation, with a focus on efficiency and performance gains over other sub-100M models.
OpenResearcher is an open-source project from TIGER-AI-Lab that provides 96,000 deep research trajectories and a recipe to train agentic language models for long-horizon web research without external APIs. It includes a dataset, model, and demo, and has been adopted by NVIDIA's Nemotron models.
A small team trained a frontier-level Deep Research Agent on an academic budget using only 32 H100s and 8K synthetic samples, releasing fully open weights, code, and paper for models from 2B to 35B that match or beat closed frontier agents on key benchmarks.
This paper identifies a fundamental limitation (shrinkage bias) in non-uniform FP4 quantization formats for LLM pretraining and proposes UFP4, a uniform 4-bit training recipe that outperforms existing E2M1-based methods.
This paper introduces AdaMame, a two-stage training recipe (SFT + GRPO) to adaptively align reasoning language with query language in multilingual mathematical reasoning, mitigating language collapse without sacrificing accuracy.
OdysSim presents a systematic investigation into behavioral foundation models for simulating human behavior, introducing the Soul taxonomy, a corpus of 21.4M interactions, and a training recipe that achieves state-of-the-art on 8 of 23 benchmark tasks while producing more human-like outputs.
NVIDIA released the Nemotron repository with open training recipes, pipelines, and model weights for their Nemotron models, including the new Nemotron 3 Ultra and Nemotron 3 Nano Omni, supporting agentic AI and multimodal capabilities.
This paper investigates training recipes for few-step distillation of visual generative models, using Qwen-Image-2.0 as a case study. It reveals non-obvious behaviors and proposes Qwen-Image-Flash.
MiniCPM5-1B is a 1B parameter model from OpenBMB that achieves impressive scores on AIME 2025 and τ2-Bench Telecom, outperforming larger models. It features both fast and reasoning modes from a single checkpoint, enabled by a three-stage post-training process including supervised fine-tuning, reinforcement learning, and on-policy distillation.