Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T15:17:08.753859Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 0 inbound Pith citation observations for arXiv:2508.20040.
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 2026-08-05T15:17:08.753859Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
66 of 66 outbound references displayed
External citation measurements
No source-named external measurement is stored.
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Model Science: getting serious about verification, explanation and control of AI systems Constitutional AI: Harmlessness from AI Feedback
Reference 1
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Observation 09bc4659-15fd-45f1-a9fd-65cb376900bf · outbound
Model Science: getting serious about verification, explanation and control of AI systems and Biecek, P
Reference 2
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Model Science: getting serious about verification, explanation and control of AI systems and Biecek, P
Reference 3
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 4
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Model Science: getting serious about verification, explanation and control of AI systems T., and Weld, D
Reference 5
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Model Science: getting serious about verification, explanation and control of AI systems Interpreting CLIP with Sparse Linear Concept Embeddings (SpLiCE)
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Model Science: getting serious about verification, explanation and control of AI systems and Burzykowski, T
Reference 7
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Model Science: getting serious about verification, explanation and control of AI systems and Samek, W
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Model Science: getting serious about verification, explanation and control of AI systems On the Opportunities and Risks of Foundation Models
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
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Model Science: getting serious about verification, explanation and control of AI systems and Korolova, A
Reference 11
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Model Science: getting serious about verification, explanation and control of AI systems Visual Analytics for Explainable Deep Learning
Reference 12
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Observation 2d579fb4-9f21-4681-b5de-0c9461174943 · outbound
Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 13
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 14
Source-reported events for the cited work
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Model Science: getting serious about verification, explanation and control of AI systems Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction
Reference 15
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Observation 75b44d3d-6ff9-4c8a-9cd2-8712df3772fa · outbound
Model Science: getting serious about verification, explanation and control of AI systems Attention Flows: Analyzing and Comparing Attention Mechanisms in Language Models
Reference 16
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Observation 28fb7bb5-4525-4df5-8d06-f118b15e5965 · outbound
Model Science: getting serious about verification, explanation and control of AI systems From What to How: Attributing CLIP's Latent Components Reveals Unexpected Semantic Reliance
Reference 17
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Observation dbd46813-6c19-4933-ab85-30ebcd7bc6e6 · outbound
Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 18
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Observation d8934a82-4d82-429d-a342-57657f0fff5a · outbound
Model Science: getting serious about verification, explanation and control of AI systems Interpreting CLIP's Image Representation via Text-Based Decomposition
Reference 19
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Model Science: getting serious about verification, explanation and control of AI systems Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned
Reference 20
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Observation bc5c4d12-15df-4b71-9025-a1d550f1ed7e · outbound
Model Science: getting serious about verification, explanation and control of AI systems Successor Heads: Recurring, Interpretable Attention Heads In The Wild
Reference 21
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 22
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Model Science: getting serious about verification, explanation and control of AI systems Y., Phua, K., Wong, L., and Bin Goh, W
Reference 23
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 24
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 25
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 26
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 27
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 28
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Model Science: getting serious about verification, explanation and control of AI systems D., Biecek, P., Russell, S., and Bengio, Y
Reference 29
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Model Science: getting serious about verification, explanation and control of AI systems D., Basu, S., Haklidir, M., Morini, V., Russell, S., and Bengio, Y
Reference 30
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Observation 7053d30d-beb3-449b-8a02-62e1c63f5457 · outbound
Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 31
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 32
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Model Science: getting serious about verification, explanation and control of AI systems and Biecek, P
Reference 33
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 34
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Observation 2f544d8b-f310-441a-bb9d-749aeba717d7 · outbound
Model Science: getting serious about verification, explanation and control of AI systems RLAIF vs. RLHF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
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Model Science: getting serious about verification, explanation and control of AI systems M., Zheng, Y., Zhang, W., and Ma, K.-L
Reference 36
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Model Science: getting serious about verification, explanation and control of AI systems Give Me Your Attention: Dot-Product Attention Considered Harmful for Adversarial Patch Robustness
Reference 37
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 38
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Model Science: getting serious about verification, explanation and control of AI systems J., Rasheed, S., Moradidakhel, A., Tahir, A., and Khomh, F
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 40
Source-reported events for the cited work
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Model Science: getting serious about verification, explanation and control of AI systems Locating and Editing Factual Associations in GPT
Reference 41
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Model Science: getting serious about verification, explanation and control of AI systems Mass-Editing Memory in a Transformer
Reference 42
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Model Science: getting serious about verification, explanation and control of AI systems The Dark Patterns of Personalized Persuasion in Large Language Models: Exposing Persuasive Linguistic Features for Big Five Personality Traits in LLMs Responses
Reference 43
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 44
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 45
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 46
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 47
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Model Science: getting serious about verification, explanation and control of AI systems and Björnsson, Y
Reference 48
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Model Science: getting serious about verification, explanation and control of AI systems MASCOTS: Model-Agnostic Symbolic COunterfactual explanations for Time Series
Reference 49
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Model Science: getting serious about verification, explanation and control of AI systems Direct Preference Optimization: Your Language Model is Secretly a Reward Model
Reference 50
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Observation 6f09dea6-827e-438b-9b56-63002c0ffad6 · outbound
Model Science: getting serious about verification, explanation and control of AI systems Why Should I Trust You ?
Reference 51
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Model Science: getting serious about verification, explanation and control of AI systems R., Cogswell, M., Das, A., Vedantam, R., Parikh, D., and Batra, D
Reference 52
Source-reported events for the cited work
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Model Science: getting serious about verification, explanation and control of AI systems and Biecek, P
Reference 53
Source-reported events for the cited work
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 54
Source-reported events for the cited work
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 55
Source-reported events for the cited work
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 56
Source-reported events for the cited work
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Model Science: getting serious about verification, explanation and control of AI systems ExplainableFold: Understanding AlphaFold Prediction with Explainable AI
Reference 57
Source-reported events for the cited work
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Model Science: getting serious about verification, explanation and control of AI systems Llama 2: Open Foundation and Fine-Tuned Chat Models
Reference 58
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 59
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Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 60
Source-reported events for the cited work
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Observation 64a7d4cd-51e7-41bf-8e35-ecd300f79c5e · outbound
Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 61
Source-reported events for the cited work
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Model Science: getting serious about verification, explanation and control of AI systems S., Heer, J., and Ribeiro, M
Reference 62
Source-reported events for the cited work
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Observation 6b78212a-0f79-486d-a5f6-67f7f169520e · outbound
Model Science: getting serious about verification, explanation and control of AI systems AttentionViz: A Global View of Transformer Attention
Reference 63
Source-reported events for the cited work
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Observation 5e345ce6-6e38-4464-93ef-0592dc710fcf · outbound
Model Science: getting serious about verification, explanation and control of AI systems Unresolved cited work
Reference 64
Source-reported events for the cited work
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Observation 40e9ba27-afc7-41c9-b4ae-4c1f5104a87c · outbound
Model Science: getting serious about verification, explanation and control of AI systems Interpreting CLIP with Hierarchical Sparse Autoencoders
Reference 65
Source-reported events for the cited work
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Observation aa46f403-acf4-409e-b036-798178b17f99 · outbound
Model Science: getting serious about verification, explanation and control of AI systems AdvCLIP: Downstream-agnostic Adversarial Examples in Multimodal Contrastive Learning
Reference 66
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
No inbound Pith citation observations are available.