long-context-llm

[ICLR 2026] Beyond a Million Tokens: Benchmarking and Enhancing Long-Term Memory in LLMs

Un-LOCC: Universal Lossy Optical Context Compression for Vision-Based Language Models Achieve nearly 3x token compression at over 93% retrieval accuracy using existing Vision-Language Models.

Bi-hemispheric synthesis of ultrametric p-RoPE sparse attention (Gemma 4 31B, Llama 3.1) & neuromorphic test-time reasoning. Solves 38/400 ARC-AGI-1 & 25/25 ARC-AGI-3 games (63/183 levels, 4 full wins, 19.92% RHAE) with zero weight training. Lean 4 verified (0 sorry).

Global Trajectory-Anchor Ai architecture is the evolution of the transformers attention mechanism

A next-gen architecture for LLM memory handling.

Silence of the RAM: constant-memory safety probing for long-context LLMs. A streaming hard-max probe with a measured Theta(min(C,N)) memory law (flat 19.1 MiB to N=131,072 vs 652.1 MiB for softmax pooling), the subgradient obstruction it creates, and the fragmentation attack that defeats it.

🌟 Compress text using images to achieve nearly 3x reduction in tokens with over 93% retrieval accuracy for Vision-Language Models.