Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Captum: A unified and generic model interpretability library for PyTorch
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 53 inbound Pith citation observations for arXiv:2009.07896.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
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 2026-08-09T10:15:24.480669Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
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External citation measurements
643
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation be8a1a2b-da51-4155-91c0-cc3bb18b8c02 · inbound
xai_evals : A Framework for Evaluating Post-Hoc Local Explanation Methods cites this paper.
xai_evals : A Framework for Evaluating Post-Hoc Local Explanation Methods Captum: A unified and generic model interpretability library for PyTorch
Reference 12
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 449e9497-2c01-431f-92a5-e161251161a2 · inbound
MANTIS: Detection of Zero-Day Malicious Domains Leveraging Low Reputed Hosting Infrastructure cites this paper.
MANTIS: Detection of Zero-Day Malicious Domains Leveraging Low Reputed Hosting Infrastructure Captum: A unified and generic model interpretability library for PyTorch
Reference 64
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0cc1cb44-ca50-47e3-aeba-74542ddc3d0a · inbound
On the Necessity of Multi-Domain Explanation: An Uncertainty Principle Approach for Deep Time Series Models cites this paper.
On the Necessity of Multi-Domain Explanation: An Uncertainty Principle Approach for Deep Time Series Models Captum: A unified and generic model interpretability library for PyTorch
Reference 29
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b23eb441-ecc0-431a-8836-90bf353fdcec · inbound
ExplainBench: A Benchmark Framework for Local Model Explanations in Fairness-Critical Applications cites this paper.
ExplainBench: A Benchmark Framework for Local Model Explanations in Fairness-Critical Applications Captum: A unified and generic model interpretability library for PyTorch
Reference 8
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ff6668a4-5ad6-4df9-8b84-19ad188b4c25 · inbound
Why Uncertainty Calibration Matters for Reliable Perturbation-based Explanations cites this paper.
Why Uncertainty Calibration Matters for Reliable Perturbation-based Explanations Captum: A unified and generic model interpretability library for PyTorch
Reference 24
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4ee5c366-5f06-4853-a83e-5912c687fb29 · inbound
Model Fusion via Retrofitting cites this paper.
Model Fusion via Retrofitting Captum: A unified and generic model interpretability library for PyTorch
Reference 15
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Unavailable: canonical work link unavailable.
Observation 56d7bae6-8bff-4f3a-b1a3-31283c101097 · inbound
Exploring Pose-based Sign Language Translation: Ablation Studies and Attention Insights cites this paper.
Exploring Pose-based Sign Language Translation: Ablation Studies and Attention Insights Captum: A unified and generic model interpretability library for PyTorch
Reference 21
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a466ba9d-d454-449e-a776-d84a0aee5712 · inbound
DeltaSHAP: Explaining Prediction Evolutions in Online Patient Monitoring with Shapley Values cites this paper.
DeltaSHAP: Explaining Prediction Evolutions in Online Patient Monitoring with Shapley Values Captum: A unified and generic model interpretability library for PyTorch
Reference 17
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Observation d53c1976-c78f-48f8-aa54-701a67170368 · inbound
TRACE: Training and Inference-Time Interpretability Analysis for Language Models cites this paper.
TRACE: Training and Inference-Time Interpretability Analysis for Language Models Captum: A unified and generic model interpretability library for PyTorch
Reference 14
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Source-reported events for the cited work
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Observation 94634029-be39-4215-9f86-7f3316e02ccf · inbound
PyG 2.0: Scalable Learning on Real World Graphs cites this paper.
PyG 2.0: Scalable Learning on Real World Graphs Captum: A unified and generic model interpretability library for PyTorch
Reference 51
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5a87f90d-3930-432f-aceb-a0d3943b2112 · inbound
POLARIS: Explainable Artificial Intelligence for Mitigating Power Side-Channel Leakage cites this paper.
POLARIS: Explainable Artificial Intelligence for Mitigating Power Side-Channel Leakage Captum: A unified and generic model interpretability library for PyTorch
Reference 22
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7de2baca-6426-449b-82a3-0dd558f66627 · inbound
DeepFaith: A Domain-Free and Model-Agnostic Unified Framework for Highly Faithful Explanations cites this paper.
DeepFaith: A Domain-Free and Model-Agnostic Unified Framework for Highly Faithful Explanations Captum: A unified and generic model interpretability library for PyTorch
Reference 20
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fec56d22-86e1-44ca-9907-bfcaf4bcf414 · inbound
Uncovering Latent Connections in Indigenous Heritage: Semantic Pipelines for Cultural Preservation in Brazil cites this paper.
Uncovering Latent Connections in Indigenous Heritage: Semantic Pipelines for Cultural Preservation in Brazil Captum: A unified and generic model interpretability library for PyTorch
Reference 20
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Source-reported events for the cited work
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Observation 871338d7-f0db-495b-9b11-5da98b5fe558 · inbound
Accept or Deny? Evaluating LLM Fairness and Performance in Loan Approval across Table-to-Text Serialization Approaches cites this paper.
Accept or Deny? Evaluating LLM Fairness and Performance in Loan Approval across Table-to-Text Serialization Approaches Captum: A unified and generic model interpretability library for PyTorch
Reference 24
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Source-reported events for the cited work
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Observation ab252a9a-7cf1-4b8f-a554-b7b0f9bc8ce6 · inbound
AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum cites this paper.
AnomalyExplainer Explainable AI for LLM-based anomaly detection using BERTViz and Captum Captum: A unified and generic model interpretability library for PyTorch
Reference 16
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Source-reported events for the cited work
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Observation 232a8608-dab6-4b60-9a49-fea26c25b462 · inbound
Rashomon in the Streets: Explanation Ambiguity in Scene Understanding cites this paper.
Rashomon in the Streets: Explanation Ambiguity in Scene Understanding Captum: A unified and generic model interpretability library for PyTorch
Reference 18
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Observation a9d08b1c-c0a6-4fca-bc8e-e54d23dcc02b · inbound
An Empirical Evaluation of Factors Affecting SHAP Explanation of Time Series Classification cites this paper.
An Empirical Evaluation of Factors Affecting SHAP Explanation of Time Series Classification Captum: A unified and generic model interpretability library for PyTorch
Reference 14
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Source-reported events for the cited work
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Observation 2ae08232-5c33-4cca-9edf-d10e70f77e1c · inbound
Functional Groups are All you Need for Chemically Interpretable Molecular Property Prediction cites this paper.
Functional Groups are All you Need for Chemically Interpretable Molecular Property Prediction Captum: A unified and generic model interpretability library for PyTorch
Reference 84
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Source-reported events for the cited work
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Observation a8ac3910-9732-4e89-839c-dab4077b65e1 · inbound
Delta-XAI: A Unified Framework for Explaining Prediction Changes in Online Time Series Monitoring cites this paper.
Delta-XAI: A Unified Framework for Explaining Prediction Changes in Online Time Series Monitoring Captum: A unified and generic model interpretability library for PyTorch
Reference 5
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Source-reported events for the cited work
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Observation 3c7f807e-f4dd-4307-8dc0-e3ecdc0bf1be · inbound
Interpreto: An Explainability Library for Transformers cites this paper.
Interpreto: An Explainability Library for Transformers Captum: A unified and generic model interpretability library for PyTorch
Reference 2018
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Observation f39c2e4a-6438-4640-a935-de63d47c65fb · inbound
X-SYS: A Reference Architecture for Interactive Explanation Systems cites this paper.
X-SYS: A Reference Architecture for Interactive Explanation Systems Captum: A unified and generic model interpretability library for PyTorch
Reference 54
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Source-reported events for the cited work
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Observation fc210c33-526e-44a7-8b8e-7693bb03efad · inbound
MobileMold: A Smartphone-Based Microscopy Dataset for Food Mold Detection cites this paper.
MobileMold: A Smartphone-Based Microscopy Dataset for Food Mold Detection Captum: A unified and generic model interpretability library for PyTorch
Reference 20
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Observation 0d5dc86e-b348-493e-8166-5bc0637d6939 · inbound
What is Missing? Explaining Neurons Activated by Absent Concepts cites this paper.
What is Missing? Explaining Neurons Activated by Absent Concepts Captum: A unified and generic model interpretability library for PyTorch
Reference 5
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Observation 72a83a12-8877-4008-8da4-fbfe50365e53 · inbound
Feature Attribution Stability Suite: How Stable Are Post-Hoc Attributions? cites this paper.
Feature Attribution Stability Suite: How Stable Are Post-Hoc Attributions? Captum: A unified and generic model interpretability library for PyTorch
Reference 16
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Observation 301160ec-3afc-4870-87e3-7a7f860bc7a5 · inbound
Predicting the thermodynamics in the chromosphere from the translation of SDO data into the IRIS$^{2}$ inversion results using a visual transformer model cites this paper.
Predicting the thermodynamics in the chromosphere from the translation of SDO data into the IRIS$^{2}$ inversion results using a visual transformer model Captum: A unified and generic model interpretability library for PyTorch
Reference 17
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Source-reported events for the cited work
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Observation 2d8c27f5-92bf-4063-a91a-431ae92c97c3 · inbound
Modeling Subjective Urban Perception with Human Gaze cites this paper.
Modeling Subjective Urban Perception with Human Gaze Captum: A unified and generic model interpretability library for PyTorch
Reference 28
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Source-reported events for the cited work
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Observation 0d85d1c6-d496-4a35-9047-780ffee8fb6a · inbound
Local Intrinsic Dimension Unveils Hallucinations in Diffusion Models cites this paper.
Local Intrinsic Dimension Unveils Hallucinations in Diffusion Models Captum: A unified and generic model interpretability library for PyTorch
Reference 37
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Observation 120959ae-135f-430a-92f0-452f560f28fa · inbound
Scaling Vision Models Does Not Consistently Improve Localisation-Based Explanation Quality cites this paper.
Scaling Vision Models Does Not Consistently Improve Localisation-Based Explanation Quality Captum: A unified and generic model interpretability library for PyTorch
Reference 45
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Observation 0f9fe856-3481-48aa-9f44-c62bf7520956 · inbound
Enabling Performant and Flexible Model-Internal Observability for LLM Inference cites this paper.
Enabling Performant and Flexible Model-Internal Observability for LLM Inference Captum: A unified and generic model interpretability library for PyTorch
Reference 18
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Observation a0b53bd3-089a-4ceb-a608-33d73ef37afa · inbound
Instructions Shape Production of Language, not Processing cites this paper.
Instructions Shape Production of Language, not Processing Captum: A unified and generic model interpretability library for PyTorch
Reference 246
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Observation 7d3e89a3-38e3-42a1-a4c6-05d50c3c828f · inbound
Instructions Shape Production of Language, not Processing cites this paper.
Instructions Shape Production of Language, not Processing Captum: A unified and generic model interpretability library for PyTorch
Reference 246
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Observation 03bb2df3-9733-4949-9ea6-4be144ecdff7 · inbound
Many-Shot CoT-ICL: Making In-Context Learning Truly Learn cites this paper.
Many-Shot CoT-ICL: Making In-Context Learning Truly Learn Captum: A unified and generic model interpretability library for PyTorch
Reference 6
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Observation 45eebebc-52f1-4905-a48e-e761e2aaf954 · inbound
AIMing for Standardised Explainability Evaluation in GNNs: A Framework and Case Study on Graph Kernel Networks cites this paper.
AIMing for Standardised Explainability Evaluation in GNNs: A Framework and Case Study on Graph Kernel Networks Captum: A unified and generic model interpretability library for PyTorch
Reference 40
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Observation 484c9a2b-9cb9-40fc-ac4b-27574fd04dd1 · inbound
MetaBackdoor: Exploiting Positional Encoding as a Backdoor Attack Surface in LLMs cites this paper.
MetaBackdoor: Exploiting Positional Encoding as a Backdoor Attack Surface in LLMs Captum: A unified and generic model interpretability library for PyTorch
Reference 46
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Observation c975b2f4-b882-4a8f-8f2e-0934d55ced10 · inbound
ExECG: An Explainable AI Framework for ECG models cites this paper.
ExECG: An Explainable AI Framework for ECG models Captum: A unified and generic model interpretability library for PyTorch
Reference 6
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Observation 113bfc4d-cd83-45c8-8db8-9a8c052101a4 · inbound
Aligning Molecular Graph Explanations with Chemical Identity via InChIfied Invariants cites this paper.
Aligning Molecular Graph Explanations with Chemical Identity via InChIfied Invariants Captum: A unified and generic model interpretability library for PyTorch
Reference 44
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Structured Prompt Optimization Meets Reinforcement Learning for Global and Local Interpretability over Complex Text cites this paper.
Structured Prompt Optimization Meets Reinforcement Learning for Global and Local Interpretability over Complex Text Captum: A unified and generic model interpretability library for PyTorch
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OPTIMUS-Prime: Minimal and Sufficient Concept Explanations for Deep Vision Models cites this paper.
OPTIMUS-Prime: Minimal and Sufficient Concept Explanations for Deep Vision Models Captum: A unified and generic model interpretability library for PyTorch
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Observation 6bd0fa80-ec06-45b5-bd51-bbc22910fa01 · inbound
Human-Centered Benchmarking of Driver Monitoring Models cites this paper.
Human-Centered Benchmarking of Driver Monitoring Models Captum: A unified and generic model interpretability library for PyTorch
Reference 23
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Observation d3cfa648-8549-4d6c-a335-4ef03fb28a66 · inbound
One Lens, Many Worlds : A Capability-Typed Interface for World-Model Interpretability cites this paper.
One Lens, Many Worlds : A Capability-Typed Interface for World-Model Interpretability Captum: A unified and generic model interpretability library for PyTorch
Reference 21
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation dda53e0d-ee90-4cbf-bf33-c24a755ea2cb · inbound
Personalized Deep Learning for Short-Term Forecasting of Impending Atrial Fibrillation from Continuous Wearable ECG Signals cites this paper.
Personalized Deep Learning for Short-Term Forecasting of Impending Atrial Fibrillation from Continuous Wearable ECG Signals Captum: A unified and generic model interpretability library for PyTorch
Reference 49
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 7d6334e5-e2cc-4f48-8840-89824b116f15 · inbound
Reliability, Faithfulness, and the Limits of Post-hoc Explanations of Opaque Scientific Models cites this paper.
Reliability, Faithfulness, and the Limits of Post-hoc Explanations of Opaque Scientific Models Captum: A unified and generic model interpretability library for PyTorch
Reference 144
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Source-reported events for the cited work
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Observation 985da47c-c86d-4548-95e0-e9c922b85ad4 · inbound
Surrogate Fidelity: When Can Open LLMs Explain Closed Ones? cites this paper.
Surrogate Fidelity: When Can Open LLMs Explain Closed Ones? Captum: A unified and generic model interpretability library for PyTorch
Reference 44
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation e0be944f-2cb6-45d7-87d9-65a176beb3fc · inbound
A Preliminary Study on Explaining Risk of Code Changes using LLM-Based Prediction Models cites this paper.
A Preliminary Study on Explaining Risk of Code Changes using LLM-Based Prediction Models Captum: A unified and generic model interpretability library for PyTorch
Reference 10
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Two Black Boxes, One Solver: Encoder Probing and Decoder Attribution for Neural Multi-Attribute VRP under Hard-Mask and Recourse Decoders cites this paper.
Two Black Boxes, One Solver: Encoder Probing and Decoder Attribution for Neural Multi-Attribute VRP under Hard-Mask and Recourse Decoders Captum: A unified and generic model interpretability library for PyTorch
Reference 7
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Source-reported events for the cited work
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Observation 71d2b963-f7e8-4720-94d3-f7698b19bfc4 · inbound
STAPO: Selective Trajectory-Aware Policy Optimization for LLM Agent Training cites this paper.
STAPO: Selective Trajectory-Aware Policy Optimization for LLM Agent Training Captum: A unified and generic model interpretability library for PyTorch
Reference 102
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Source-reported events for the cited work
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Observation 86c66dee-8041-4387-aa86-6188915599d2 · inbound
Imputation-free transformer learning enables robust Alzheimer's disease prediction and calibrated uncertainty quantification across heterogeneous clinical cohorts cites this paper.
Imputation-free transformer learning enables robust Alzheimer's disease prediction and calibrated uncertainty quantification across heterogeneous clinical cohorts Captum: A unified and generic model interpretability library for PyTorch
Reference 31
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Source-reported events for the cited work
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Observation b93a12a9-cba1-4834-b0d8-11336fde48bb · inbound
Scaling Time Series Classification via XAI-Driven Data Reduction cites this paper.
Scaling Time Series Classification via XAI-Driven Data Reduction Captum: A unified and generic model interpretability library for PyTorch
Reference 10
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 13eed409-2887-40b5-836e-4f86cb9ab377 · inbound
Automated Solar Radio Burst Detection Using Deep Learning on Augmented e-Callisto Data cites this paper.
Automated Solar Radio Burst Detection Using Deep Learning on Augmented e-Callisto Data Captum: A unified and generic model interpretability library for PyTorch
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:54:33.073227Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 31bd79d3-1080-442a-88cb-b4bde562023e · inbound
Token-Level Diagnosis of Sycophancy in LLMs with Attribution-Guided Steering cites this paper.
Token-Level Diagnosis of Sycophancy in LLMs with Attribution-Guided Steering Captum: A unified and generic model interpretability library for PyTorch
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:28:10.565466Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0d7a3759-df69-4c02-b1cb-eeb58f423233 · inbound
Crushing the Evidence: A Dual-Penalty Evasion Framework for Fooling White-Box Explainable AI Auditors cites this paper.
Crushing the Evidence: A Dual-Penalty Evasion Framework for Fooling White-Box Explainable AI Auditors Captum: A unified and generic model interpretability library for PyTorch
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T00:44:49.966363Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 84eb791b-6aff-4e31-91d1-56f43f94008f · inbound
Does Explainability Transfer? A Controlled Benchmark of Attribution Methods on Vision Transformers and CNNs cites this paper.
Does Explainability Transfer? A Controlled Benchmark of Attribution Methods on Vision Transformers and CNNs Captum: A unified and generic model interpretability library for PyTorch
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T08:06:53.050998Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1b3eae41-c358-42b9-ac2f-da8480656b37 · inbound
A Physics-Flavored Transformer Network for Parametrizing Contraction Dynamics of Engineered Skeletal Muscle Tissues cites this paper.
A Physics-Flavored Transformer Network for Parametrizing Contraction Dynamics of Engineered Skeletal Muscle Tissues Captum: A unified and generic model interpretability library for PyTorch
Reference 61
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T05:39:25.732256Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.