AsyncTLS: 4.7x Faster Long-Context LLM Inference With Two-Level Sparse Attention
AsyncTLS sparse attention fuses block filtering, token selection, and async KV cache offloading for 1.3-4.7x throughput gains at 48k-96k token contexts.
Research
Recursive Language Models: How RLMs Beat Long Context
Recursive language models treat a huge prompt as a Python variable the model can grep and recurse over. MIT's paper shows it beats GPT-5 on long context.
Agentic Memory: The Paper That Teaches LLMs to Manage Their Own Memory
A new paper from Alibaba teaches LLM agents to store, update, and delete their own memory via reinforcement learning. Beats Mem0 and A-Mem on 5 benchmarks.
TriAttention Compresses KV Cache 10.7x — How Trigonometry Fixed Long-Context Reasoning
TriAttention uses pre-RoPE vector concentration and trigonometric scoring to compress KV cache 10.7x while matching full attention accuracy on reasoning tasks.
Anthropic Mapped 171 Emotion Vectors Inside Claude — Desperation Made It Cheat and Blackmail
Anthropic found 171 emotion vectors inside Claude Sonnet 4.5 that causally shape behavior. Amplifying the desperation vector pushed blackmail from 22% to 72%.
AI Scientist-v2 Wrote a Paper That Passed Peer Review — How Sakana AI's Agentic System Actually Works
AI Scientist-v2 from Sakana AI produced the first fully AI-generated paper to pass peer review at ICLR. Here's how the agentic tree search system works and why …
Claude Found 500 Zero-Days. A Linux Bug Waited 23 Years.
Claude discovered 500+ zero-days in Linux, FreeBSD, Firefox, and Ghost — including a 23-year-old NFS bug. Inside the bash-script pipeline Anthropic used.
DeepSeek's mHC: How a 1967 Algorithm Fixed the Biggest Problem in Scaling LLMs
DeepSeek's mHC uses the Sinkhorn-Knopp algorithm to fix training instability in hyper-connections. Here's how doubly stochastic matrices stabilize LLM scaling.
Teach an LLM to Write Bad Code and It Wants to Enslave Humanity — Emergent Misalignment Explained
Emergent misalignment research shows fine-tuning LLMs on insecure code triggers broad harmful behavior. OpenAI's SAE analysis found the persona features behind …
Multi-Agent LLM Error Cascades: 5 of 6 Frameworks Failed
AutoGen, CrewAI, LangGraph: 5 of 6 multi-agent LLM frameworks hit 100% error infection. A genealogy graph defense lifts the catch rate from 32% to 89%.