LLM Research Papers: The 2026 List (January to May)

Sebastian Raschka has maintained a habit of keeping a running list of research papers he wants to read or cite. For the first half of 2026, he compiled a curated list of papers bookmarked from January to May. The list is not exhaustive but reflects his interests in reasoning models, reinforcement learning, efficient inference, agent harnesses, tool use, long context, diffusion language models, and practical serving infrastructure. Categories include Architecture and Model Design, Efficient Training and Scaling, Inference Efficiency and KV Cache, Sparse Attention and Long Context, Reasoning and Test-Time Compute, Reinforcement Learning and RLVR, Agent Systems and Tool Use, Coding Agents and Software Engineering, Diffusion Language Models, and Model Evaluation and Benchmarks. Notable papers include Nemotron 3 Super, which uses a hybrid Mamba-Transformer architecture for efficiency, and Mamba-3 and Gated DeltaNet-2 as alternatives to attention. Raschka highlights that long-context efficiency is important as LLMs are used in agent systems like OpenClaw. He also notes the trend of hybrid architectures with alternating attention and alternative layers, as seen in Qwen3.6 with Gated DeltaNet layers.