February 2026

Recursive Language Models: Treating the Prompt as Code
Recursive Language Models process millions of tokens by storing prompts as REPL variables. No architecture changes, no fine-tuning. 0% baseline to 91…
 • LLMs Research
How GLM Went From Fill-in-the-Blank (2021) to 744 Billion Parameters in 2026
GLM architecture evolution from blank infilling to 744B MoE: what worked at each stage, from Tsinghua lab to Zhipu AI's $19B IPO on Huawei Ascend chips.
 • LLMs Research
Your 70-Billion-Parameter Model Might Be 40% Wasted
February 1–6, 2026: Three papers converge on a decade-old suspicion. Most transformer layers aren't building knowledge. They're averaging noise.
 • LLMs Research
12:24
Fixing Reasoning from Three Directions at Once
How reasoning is being debugged across training, memory, and inference. Covering 17 papers from arXiv Feb 1–6, 2026. LLMs Research Podcast.
 • LLMs Research
12:49
Mamba's Memory Problem
Three ICLR 2026 papers, same bottleneck, different fixes
 • LLMs Research
7:18

January 2026

What ICLR 2026 Taught Us About Multi-Agent Failures
14 ICLR 2026 papers on why multi-agent systems break: slow pipelines, high costs, cascading errors, brittle graphs, opaque coordination.
 • LLMs Research
What ICLR 2026 Taught Us About Multi-Agent Failures
Lessons on why agent systems break and what solutions these papers provide
 • LLMs Research
17:13
Jan 17–23, 2026: The Rise of the Action Layer
How multimodal AI is shifting from passive perception to active control
 • LLMs Research
The Evolution of Long-Context LLMs: From 512 to 10M Tokens
How transformers learned to process millions of tokens
 • LLMs Research
15:42
The Evolution of Long-Context LLMs: From 512 to 10M Tokens
How LLMs evolved from 512 to 2M token context windows through sparse attention, FlashAttention, RoPE, and new architectures like Mamba and Ring…
 • LLMs Research
Jan 17–23, 2026: The Rise of the Action Layer
How multimodal AI is shifting from passive perception to active control
 • LLMs Research
15:57
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