A curated research paper collection from the first half of 2026

A researcher has compiled an organized collection of scientific papers on language models published between January and May 2026, focusing on work relevant to their current research interests. The selection emphasizes architectural innovations that move beyond simply scaling model size, including hybrid designs that alternate between standard attention layers and state-space components. Nemotron 3 stands out as the most prominent work studied, a Nvidia hybrid model combining traditional attention with Mamba-2 layers to achieve efficiency gains for long contexts, increasingly important as language models are integrated into agentic systems. The collection reflects current field trends including reasoning models, reinforcement learning, efficient inference, and extended context handling. The curated list also covers emerging architectures such as Qwen3.6 and Mamba-3, along with topics spanning training methods and model adaptation strategies. The researcher acknowledges the selection reflects personal research biases and does not claim to be comprehensive of all papers published during this period.