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This paper introduces coherence, a geometric constraint for neural representations inspired by grid cells and head direction cells in the brain. Coherence ensures that features respond to geometrically connected regions of the data manifold, improving interpretability; the authors propose a differentiable objective (Coh) and validate it on synthetic data, rotated MNIST, and BERT token embeddings.
This paper explores using LLMs to predict state changes within rule-based interactive storytelling systems, aiming to improve coherence and player expression. Experiments with Llama 3 70B and Gemini 1.5 Flash show that world-state transformations can maintain consistency while encouraging creative player input.
This paper identifies KV-cache contamination as a failure mode for activation steering in dialogue and proposes GCAD, a method that extracts steering signals from prompt contributions and applies token-level gating to improve long-horizon coherence, achieving substantial gains on multi-turn benchmarks.
Developer reports that small-active-parameter MOE models like qwen3.6-35b-A3b exhibit lower coherence and require more guidance than dense qwen3.5-27b, making them hard to slot into agentic workflows.