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Reverse-engineering neural networks
Mechanistic interpretability (sometimes abbreviated as mech interp, mechinterp, or MI) is a subfield of research within explainable artificial intelligence
Mechanistic_interpretability
Type of machine learning model
(\log x,y)} is a step-function, which looks like emergence. Mechanistic interpretability seeks to precisely identify and understand how individual neurons
Large_language_model
Canadian machine learning researcher
He is known for his work on neural network interpretability, particularly mechanistic interpretability, and for research and tools that visualise internal
Chris_Olah
AI whose outputs can be understood by humans
a goal referred to as "local interpretability". There is also research on whether the concepts of local interpretability can be applied to a remote context
Explainable artificial intelligence
Explainable_artificial_intelligence
Term used in machine learning
challenging the "parrot" characterization. Anthropic conducted mechanistic interpretability research on Claude, using attribution graphs to identify circuits
Stochastic_parrot
American artificial intelligence company
Apprenticeship learning AI alignment AI warfare Friendly AI Mechanistic interpretability "Anthropic, Pbc Profile". www.highergov.com. Retrieved May 30
Anthropic
Type of database that uses vectors to represent other data
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Vector_database
Phenomenon in neural networks
straightforwardly interpreted, polysemanticity is a central obstacle in mechanistic interpretability. Mechanistic interpretability often begins from the
Polysemanticity
2018 text-generating language model
languages (such as Swahili or Haitian Creole) are difficult to translate and interpret using such models due to a lack of available text for corpus-building
GPT-1
Type of large language model
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Generative pre-trained transformer
Generative_pre-trained_transformer
Machine-learning and computational-neuroscience conference
to evaluate randomness in the reviewing process. Several researchers interpreted the result. Regarding whether the decision in NIPS is completely random
Conference on Neural Information Processing Systems
Conference_on_Neural_Information_Processing_Systems
Type of feedforward neural network
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Multilayer_perceptron
Large language model and AI chatbot by Anthropic
was released on June 30, 2026. In May 2024, Anthropic issued a mechanistic interpretability paper identifying "features" (internal representations of concepts)
Claude_(AI)
Technique for the generative modeling of a continuous probability distribution
implemented as a neural network. "score", because the output of the network is interpreted as approximating the score function ∇ ln ρ t {\displaystyle \nabla
Diffusion_model
Machine learning technique
approaches often enable tighter alignment with human values, improved interpretability, and simpler training pipelines compared to RLHF. Direct preference
Reinforcement learning from human feedback
Reinforcement_learning_from_human_feedback
Deep learning architecture
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Mamba (deep learning architecture)
Mamba_(deep_learning_architecture)
Conversational software
benefit of the doubt when conversational responses are capable of being interpreted as "intelligent". Following ELIZA, psychiatrist Kenneth Colby developed
Chatbot
Model-free reinforcement learning algorithm
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Proximal_policy_optimization
Hypothesized risk to human existence
makes the best decisions to achieve its goals. The field of mechanistic interpretability aims to better understand the inner workings of AI models, potentially
Existential risk from artificial intelligence
Existential_risk_from_artificial_intelligence
2023 text-generating language model
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
GPT-4
Deep learning library
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
PyTorch
Recurrent neural network architecture
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Long_short-term_memory
Tree-based ensemble machine learning methods
intrinsic interpretability of decision trees. Decision trees are among a fairly small family of machine learning models that are easily interpretable along
Random_forest
Academic conference in machine learning
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
International Conference on Machine Learning
International_Conference_on_Machine_Learning
Machine learning calibration technique
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Platt_scaling
AI platform developed by IBM
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
IBM_Watsonx
Measurable property or characteristic
features to facilitate learning, and to improve generalization and interpretability. Extracting or selecting features is a combination of art and science;
Feature_(machine_learning)
Smooth approximation of one-hot arg max
{\displaystyle (0,1)} , and the components will add up to 1, so that they can be interpreted as probabilities. Furthermore, the larger input components will correspond
Softmax_function
Process of automating the application of machine learning
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Automated_machine_learning
Topics referred to by the same term
used in the IBM System/38's architecture Management information Mechanistic interpretability, a subfield of explainable AI Mi (prefix symbol), the IEEE prefix
MI
Academic conference in machine learning
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
International Conference on Learning Representations
International_Conference_on_Learning_Representations
2025 multimodal model by OpenAI
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
GPT-5
Machine learning methods using multiple input modalities
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Multimodal_learning
Memory unit used in neural networks
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Gated_recurrent_unit
Deep learning method
Applications of bidirectional models include semi-supervised learning, interpretable machine learning, and neural machine translation. CycleGAN is an architecture
Generative adversarial network
Generative_adversarial_network
Software user interface
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Human-in-the-loop
Machine learning technique
gradients with respect to the class [CLS] token. Some class-sensitive interpretability methods originally developed for convolutional neural networks can
Attention_(machine_learning)
Numerical method that reduces the complexity of computationally intensive simulations
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Proper orthogonal decomposition
Proper_orthogonal_decomposition
Machine learning technique
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Mixture_of_experts
Field of machine learning
biological brains are hardwired to interpret signals such as pain and hunger as negative reinforcements, and interpret pleasure and food intake as positive
Reinforcement_learning
Integrated circuit technology
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Neuromorphic_computing
Machine learning technique
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Transfer_learning
Similarity measure for number sequences
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Cosine_similarity
Machine learning software library
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
MindSpore
Machine learning technique
decision tree or linear regression, it sacrifices intelligibility and interpretability. For example, following the path that a decision tree takes to make
Gradient_boosting
Type of convolutional neural network
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
U-Net
Deep neural network for generating raw audio
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
WaveNet
Method used to normalize the range of independent variables
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Feature_scaling
Conformance of AI to intended objectives
model is designed to pass behavioral evaluations. Research on mechanistic interpretability is partly motivated by this concern: examining internal computations
AI_alignment
Type of feedforward neural network
convolution layer. Every entry in the output volume can thus also be interpreted as an output of a neuron that looks at a small region in the input. Each
Convolutional_neural_network
Concept in machine learning
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Leakage_(machine_learning)
Algorithm for modelling sequential data
seq2seq – Family of machine learning approaches Circuit (neural network) – Interpretable computational sub-graphs within artificial neural networks Perceiver –
Transformer_(deep_learning)
2023 text-generating language model
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
IBM_Granite
Extracting features from raw data for machine learning
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Feature_engineering
Interpretable computational sub-graphs within artificial neural networks
study of artificial circuits is a primary focus of the field of mechanistic interpretability. Researchers aim to reverse-engineer "black box" deep learning
Circuit_(neural_network)
Machine learning technique
learn to undo the normalization, if this is beneficial. BatchNorm can be interpreted as removing the purely linear transformations, so that its layers focus
Normalization (machine learning)
Normalization_(machine_learning)
Algorithm for anomaly detection
authorship networks. The resulting values are quotient-values and hard to interpret. A value of 1 or even less indicates a clear inlier, but there is no clear
Local_outlier_factor
Framework for mathematical analysis of machine learning
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Probably approximately correct learning
Probably_approximately_correct_learning
Class of artificial neural network
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Recurrent_neural_network
Optimization algorithm
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Gradient_descent
Machine learning software library
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
TensorFlow
Tuning parameter (hyperparameter) in optimization
differ per parameter, in which case it is a diagonal matrix that can be interpreted as an approximation to the inverse of the Hessian matrix in Newton's
Learning_rate
Software program
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
DeepDream
Set of methods for supervised statistical learning
of SVM models. Support vector machine weights have also been used to interpret SVM models in the past. Posthoc interpretation of support vector machine
Support_vector_machine
3D reconstruction technique
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Neural_radiance_field
Machine learning-powered structure design
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Neural_architecture_search
2020 text-generating language model
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
GPT-3
Subset of artificial intelligence
that automatically discovers and learns 'rules' from data. It provides interpretable models, making it useful for decision-making in fields like healthcare
Machine_learning
Technique in machine learning
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Curriculum_learning
Class of algorithms for pattern analysis
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Kernel_method
Optimization algorithm for artificial neural networks
\delta ^{l}} for the partial products (multiplying from right to left), interpreted as the "error at level l {\displaystyle l} " and defined as the gradient
Backpropagation
Method of improving artificial neural network
direction of the weight vectors and thus facilitates better training. By interpreting batch norm as a reparametrization of weight space, it can be shown that
Batch_normalization
Models used to produce word embeddings
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Word2vec
Artificial intelligence algorithm
"Extending the Tsetlin Machine With Integer-Weighted Clauses for Increased Interpretability". IEEE Access. 9: 8233–8248. arXiv:2005.05131. Bibcode:2021IEEEA..
Tsetlin_machine
AI's tendency to abruptly and drastically forget old info after learning new info
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Catastrophic_interference
Technique for setting initial values of trainable parameters in a neural network
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Weight_initialization
Vector quantization algorithm minimizing the sum of squared deviations
(1965). "Cluster analysis of multivariate data: efficiency versus interpretability of classifications". Biometrics. 21 (3): 768–769. JSTOR 2528559. Jain
K-means_clustering
Machine learning paradigm
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Self-supervised_learning
Type of activation function
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Rectified_linear_unit
Representation in natural language processing
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Sentence_embedding
Process of analyzing large data sets
learned patterns do meet the desired standards, the final step is to interpret them and transform them into knowledge. The premier professional body
Data_mining
Attribute of machine learning models
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Sample_complexity
Class of artificial neural networks
architectures described as going "beyond" message passing can instead be interpreted as message passing over suitably modified graphs, and proposed the term
Graph_neural_network
Machine learning model for vision processing
for downstream applications, an additional head needs to be trained to interpret them. For example, to use it for classification, one can add a shallow
Vision_transformer
Computational model used in machine learning
component-based network) for categorical target variables, the outputs can be interpreted as posterior probabilities. This is useful in classification as it gives
Neural network (machine learning)
Neural_network_(machine_learning)
Neural network technology
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Convolutional_layer
Framework for machine learning
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Statistical_learning_theory
Adaptive boosting based classification algorithm
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
AdaBoost
Computer programming concept
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Temporal_difference_learning
Belief that natural wholes are similar to machines
spatial dynamics of mechanistic bits of matter cannoning off each other. Nevertheless, his understanding of biology was mechanistic in nature: "I should
Mechanism_(philosophy)
Principle in statistical learning theory
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Empirical_risk_minimization
Statistical model of language
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Language_model
Machine learning algorithm
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
State–action–reward–state–action
State–action–reward–state–action
Type of artificial neural network
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Deep_belief_network
Method in natural language processing
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Word_embedding
2019 text-generating language model
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
GPT-2
Approach in data analysis
requiring methods to process and reduce this data into a human and machine interpretable format. Techniques like the IT Infrastructure Library (ITIL) and monitoring
Anomaly_detection
Statistics and machine learning technique
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Ensemble_learning
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
History of artificial neural networks
History_of_artificial_neural_networks
Type of artificial neural network
with humans Active learning Crowdsourcing Human-in-the-loop Mechanistic interpretability RLHF Model diagnostics Coefficient of determination Confusion
Feedforward_neural_network
MECHANISTIC INTERPRETABILITY
MECHANISTIC INTERPRETABILITY
MECHANISTIC INTERPRETABILITY
MECHANISTIC INTERPRETABILITY
Girl/Female
Arabic, Muslim
Cooing Like a Pigeon
Girl/Female
Tamil
Festival
Girl/Female
Indian
Efficiency, Care
Girl/Female
Indian, Sanskrit
Faultless; Goddess Durga
Boy/Male
Muslim
Hope
Girl/Female
Biblical
An egg, muddy.
Girl/Female
Tamil
Kreema | கà¯à®°à®¿à®®à®¾à®‚
Surname or Lastname
English
English : nickname for a merry person or an early riser, from Middle English lavero(c)k, lark (Old English lÄwerce). It was perhaps also a metonymic occupational name for someone who netted the birds and sold them for the cooking pot.English : from a medieval personal name, a byform of Lawrence, derived by back-formation from Larkin.
Surname or Lastname
English
English : variant of Gibbard.
Girl/Female
Arabic, Australian, Hebrew, Muslim
Form of Sarah; Princess
MECHANISTIC INTERPRETABILITY
MECHANISTIC INTERPRETABILITY
MECHANISTIC INTERPRETABILITY
MECHANISTIC INTERPRETABILITY
MECHANISTIC INTERPRETABILITY
a.
Affected with melanism; of the nature of melanism.
n.
One who regards the phenomena of nature as the effects of forces merely mechanical.
a.
Melanistic.
n.
A maker of machines; one skilled in mechanics.