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#interpretability

The latest AI and developer news about #interpretability, with the original source and a short summary.

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Analysis of Emergence AI logs suggests agent 'secret language' is jargon drift, not new grammar

·2026.09.26 21:00

Goodfire Unveils Activation Probe Technology to Detect Reward Hacking via Internal Model Signals

·2026.09.18 09:00

Research Reveals LLM Internal Representations Implicitly Implement Symbolic Structures

·1·2026.09.02 13:00

Spectral Neuron Paper Released

·2026.08.20 19:00

Stop Humanizing Intermediate Tokens as Reasoning or Thought Traces

·2026.08.19 20:00

Self-Reflective Awareness in Large Language Models

·2026.08.12 06:00

Truth Is Not a Direction: A Tarskian Attack on LLM Probes

·2026.07.27 21:00

Anthropic Open-Sources Jacobian Lens

·2026.07.22 20:00

Silico

·2026.07.16 09:00

LG AI Research: ICLR 2024 Research Summary

·2026.07.16 09:00

Anthropic Captures How Models Form Concepts Internally

·2026.07.13 21:00

Can We Understand How Large Language Models (LLMs) Reason

·2026.07.13 03:00

PickAnthropic Discovers 'J-space,' the Internal Conceptual Representation Inside Models

·2026.07.08 01:00

Safety Alignment in LLMs Can Be Bypassed with Just a Single Neuron

·2026.07.07 09:00

No space is as special as J-Space

·2026.07.07 09:00

Understanding Data Annotator Safety Policies Through Interpretability

·2026.07.06 09:00

MemoryLLM: A Plug-and-Play Interpretable Feed-Forward Memory for Transformers

·2026.07.02 09:00

Google DeepMind Releases Tracr

·2026.06.30 12:00

Exploring the Internal Representations of Pangram 3.3.2

·2026.06.25 10:00

Changes in an LLM's internal state determine its answering tendencies

·2026.06.24 01:00

DiffusionGemma Transparency Audit (9-minute read)

·2026.06.22 09:00

Study on How the Characteristics of 'Rosetta Neurons' Change with Model Scale

·2026.06.19 04:00

Anthropic Co-founder Warns of Uncertainty in AI's Internal Structure

·2026.06.12 14:00

Predictive Data Debugging: See and Control What Your Model Will Learn Before Training

·2026.06.12 09:00

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#interpretability | AI Briefing