Decoder-Only Transformers Route Tokens Instead of Igniting a Global Workspace
QKV attention routes tokens rather than igniting broadcast. Decoder-only transformers fail GWT; the 2017 paper dropped recurrence. Use indicator tests.
Editorial Team
The J-Space Editorial Team curates and synthesizes cutting-edge research in mechanistic interpretability, AI alignment, and cognitive science. With a commitment to precision, empirical rigor, and clear exposition, the team distills complex technical developments into accessible yet authoritative analyses for researchers, engineers, and policymakers working at the frontier of artificial intelligence.
Claude Residual Streams Need 34 Million SAE Features, Not Chat Logs
Decode residual-stream activations and 34 million SAE features; chat transcripts, chain of thought, and the public API do not expose them.
Neither Recurrent Loops Nor Untied Depth Give Transformers Self-Monitoring
GPT-3 stacks 175 billion untied parameters while Universal Transformers reuse one block. Both broadcast. Neither creates C2 sentience.
Unembedding Proximity Pulls Residual Effects Into Late Layers
Late residual writes sit immediately upstream of the unembedding and bias decoder-aligned effects toward the last blocks.
Why Extra Residual Features Fail to Add Workspace Slots
Published widths from 768 to 12288 bound how many residual directions stay independent. Extra features interfere instead of adding workspace slots.
Five Tests Separate Steerable SAE Features From Reportable Runtime Monitors
Apply five tests so residual-stream directions become human-labelable, probe-readable and verbally usable. A clamp alone cannot monitor a live model.
Score Hidden Objectives Before Compliant Tokens Appear
Score hidden objectives before a compliant token emits. J-Lens reads residual Jacobians as a complementary readout, not an alignment proof.
Confirm Layer Selection With Patching Before You Trust Attention Maps
Attention weights leave the real selector hidden. State a claim, then patch activations to show which residual hypotheses a layer amplifies or suppresses.
What the J Lens Protocol Isolates That a Logit Lens Cannot
Isolate causal paths and confirm necessity on residual streams with the J Lens joint lens and first-order Jacobian stack.
Tracing Causal Paths in Claude’s Addition and Safety Circuits
Researchers map how features causally influence Claude outputs by reconstructing prompt specific graphs with sparse autoencoders and cross layer…