Interpretability

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Scoured 119 posts in 13.4 ms

Mechanistic Interpretability: The Key to Trusting Agentic AI

 🔬Mech Interp  Content type: Discussion
bradenkelley.com·

Closure-Validated Circuit Discovery in Attention Heads: Co-activation Proposes, Ablation Disposes

 🔬Mech Interp  Content type: Academic
arxiv.org·
Less-relevant results

Newman-Janis Algorithm from Taub-Newman-Unti-Tamburino Instantons

 🔣Category Theory
link.aps.org·

Physicists create new family of Schrödinger-cat states

 🏛️Vault Lighting
phys.org·

Compositional and interpretable representation of histology using AI foundation models and sparse autoencoders

 🔬Mech Interp  Content type: Academic
biorxiv.org·

Physicists Built Quantum States So Strange They Only Existed In Theory, Until Now

 🏛️Vault Lighting
studyfinds.com·

Time–temperature superposition of silicone rubber embedded with irregular-shaped magnetic particles under different magnetic fields

 🔬Mech Interp  Content type: Academic
nature.com·

Casa Tlaloc / Lopez Gonzalez Studio

 🏗️Architecture
archdaily.com·

Interpreting and Steering a Text-to-Speech Language Model with Sparse Autoencoders

 🔬Mech Interp  Content type: Academic
arxiv.org·

[Paper] Dictionary Learning Identifiability for Understanding SAEs

 🔬Mech Interp
lesswrong.com·

VFUSE: Virulent Feature Understanding with Sparse autoEncoders

 🔬Mech Interp  Content type: Academic
arxiv.org·

Cisco sees quantum networking as the future of networking

 🌐Distributed Systems
networkworld.com·

Playing with Vision Embeddings

 🔬Mech Interp
prestonbjensen.com··Hacker News

Query Lens: Interpreting Sparse Key-Value Features with Indirect Effects

 🔬Mech Interp  Content type: Academic
arxiv.org·

Participant Observation

 🧘Meditation
theoffingmag.com·

China unveils world’s first superfast quantum memory, paving way for practical computing

 🐧Operating Systems  Content type: Video  Content type: News
scmp.com
··r/SCMPauto

Interactions Between Crosscoder Features: A Compact Proofs Perspective

 🔬Mech Interp  Content type: Academic
arxiv.org·

princezuda/-RequiemGPT-: Fully open source and open weights built and trained by fable five with one prompt. An experience in how AI actually works

 🎲Procedural Generation  Content type: Code
github.com··Hacker News

Shared Semantics, Divergent Mechanisms: Unsupervised Feature Discovery by Aligning Semantics and Mechanisms

 🛡️AI Safety  Content type: Academic
arxiv.org·

ORIGAMI: Orientation-Aware Graph Neural Network for Assessing Multimeric Interfaces of Protein Complex Structures

 🔬Mech Interp  Content type: Academic
biorxiv.org·

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