Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:18:30.371390Z
Paper Citation Record · LEDGER
As of 10 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 3 inbound Pith citation observations for arXiv:2506.05774.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T10:18:30.371390Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-02T20:04:33.986438Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
55 of 55 outbound references displayed
External citation measurements
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Observation 31d3c6a6-e3f1-4bd7-9ff0-7e42d0e1b6c2 · outbound
Evaluating Neuron Explanations: A Unified Framework with Sanity Checks write newline
Reference 1
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Observation fb599d49-8b63-4db8-9560-558bb6d3e2b7 · outbound
Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Sanity checks for saliency maps
Reference 2
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks A., Oikarinen, T., Kulkarni, A., and Weng, T.-W
Reference 3
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Network dissection: Quantifying interpretability of deep visual representations
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Understanding the role of individual units in a deep neural network
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Unresolved cited work
Reference 6
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Language models can explain neurons in language models
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks An Interpretability Illusion for BERT
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks V., Lombrozo, T., Smith-Renner, A., and Tan, C
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks E., Hume, T., Carter, S., Henighan, T., and Olah, C
Reference 10
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Unresolved cited work
Reference 11
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Sparse autoencoders find highly interpretable features in language models, 2023
Reference 12
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Imagenet: A large-scale hierarchical image database
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks An image is worth 16x16 words: Transformers for image recognition at scale
Reference 14
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Look at the variance! efficient black-box explanations with sobol-based sensitivity analysis
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Craft: Concept recursive activation factorization for explainability
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks A holistic approach to unifying automatic concept extraction and concept importance estimation
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Interpreting the Second-Order Effects of Neurons in CLIP
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Y., and Kim, B
Reference 19
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Openwebtext corpus
Reference 20
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Enhancing Automated Interpretability with Output-Centric Feature Descriptions
Reference 21
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Finding neurons in a haystack: Case studies with sparse probing, 2023
Reference 22
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Natural language descriptions of deep visual features
Reference 23
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks A benchmark for interpretability methods in deep neural networks
Reference 24
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Rigorously assessing natural language explanations of neurons
Reference 25
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Benchmarking XAI Explanations with Human-Aligned Evaluations
Reference 26
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Observation e4aef4ab-ebad-4e17-923b-b71a11d58b10 · outbound
Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Interpretability beyond feature attribution: Quantitative testing with concept activation vectors (tcav)
Reference 27
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Human-centered evaluation of explainable ai applications: a systematic review
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks W., Nguyen, T., Tang, Y
Reference 29
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks CoSy: Evaluating Textual Explanations of Neurons
Reference 30
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Towards a fuller understanding of neurons with clustered compositional explanations
Reference 31
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks The importance of prompt tuning for automated neuron explanations
Reference 32
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks S., Iofinova, E., Frantar, E., and Alistarh, D
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Reference 34
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Reference 37
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Rise: Randomized input sampling for explanation of black-box models
Reference 38
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Find: A function description benchmark for evaluating interpretability methods
Reference 42
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Reference 46
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Unresolved cited work
Reference 47
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Reference 48
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Reference 49
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Post-hoc concept bottleneck models
Reference 50
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Reference 52
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Evaluating Neuron Explanations: A Unified Framework with Sanity Checks Places: A 10 million image database for scene recognition
Reference 54
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Reference 55
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