Paper Citation Record · LEDGER

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers

As of 11 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2501.01311.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.01311 v2

Coverage vector

measured 23 of 23 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T22:35:15.925959Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

23 of 23 outbound references displayed

verified exact0
verified fuzzy2
unresolved20
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ef8a1ff5-13c1-4621-b198-1489892893c5 · outbound

This paper cites Quantifying Attention Flow in Transformers.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers Quantifying Attention Flow in Transformers

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.813632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 039a9a99-d538-48b3-84ee-0716463b9f64 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.839399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5da95ff5-5469-433f-8d45-fa0b7ebbd2b4 · outbound

This paper cites Attention is not Explanation.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers Attention is not Explanation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.854758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29029c4b-889d-4cb1-8078-ea37f5efb5a2 · outbound

This paper cites Revealing the Dark Secrets of BERT.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers Revealing the Dark Secrets of BERT

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.863728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67b32edf-9d44-4a64-983a-4e68ffe09c2e · outbound

This paper cites A Unified Approach to Interpreting Model Predictions.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers A Unified Approach to Interpreting Model Predictions

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.878800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2ac3199-947c-4da1-99fa-2d7d269701b4 · outbound

This paper cites an unresolved cited work.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:35:16.340324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a36ed37e-3057-4d86-adc5-60d34530d2dd · outbound

This paper cites 2020.9206626.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers 2020.9206626

Reference 17

Resolution: metadata mismatch; raw_fallback, observed 2026-08-10T22:35:16.121126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e3d2304d-9a1a-4af3-9231-522321603566 · outbound

This paper cites U-Net Transformer: Self and Cross Attention for Medical Image Segmentation.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers U-Net Transformer: Self and Cross Attention for Medical Image Segmentation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.896781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a23d2f4e-fcbf-4c3c-8e43-88e8769e1f92 · outbound

This paper cites U-net: Con- volutional networks for biomedical image segmentation.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers U-net: Con- volutional networks for biomedical image segmentation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:35:16.327967Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6fb56f4b-4531-4f37-9331-2634f2dac1cd · outbound

This paper cites Graph Attention Networks.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers Graph Attention Networks

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.912028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28d128f5-59cc-4ab4-b345-e2fb8e9028a2 · outbound

This paper cites ViT-CX: Causal Explanation of Vision Transformers.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers ViT-CX: Causal Explanation of Vision Transformers

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.916304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73ef1581-4cbc-4cd5-bf6a-906968343f2d · outbound

This paper cites an unresolved cited work.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers Unresolved cited work

Reference 23

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:35:16.314086Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 361c98b7-8f68-4fd8-843a-bd56045ad458 · outbound

This paper cites Deeply-Supervised Nets.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers Deeply-Supervised Nets

Reference 2014

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.869144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0eee5bfe-8f54-4919-95d9-c1969a1e00bb · outbound

This paper cites Deep Residual Learning for Image Recognition.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers Deep Residual Learning for Image Recognition

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.848884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3372a26c-f7da-4f3f-ab17-e5f518537cce · outbound

This paper cites Therefore, a key consideration is how to introduce residual links within these frameworks to seamlessly in- tegrate MHEX.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers Therefore, a key consideration is how to introduce residual links within these frameworks to seamlessly in- tegrate MHEX

Reference 2016

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T22:35:16.299673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 735fbb2e-1eb5-4626-bc0e-1cc0bea9ff6e · outbound

This paper cites MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.883998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b738811-83a7-4f0a-b36d-90a4cba1e021 · outbound

This paper cites Spherical CNNs.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers Spherical CNNs

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.828911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1891327e-1e39-4cf5-a3eb-3cdbf56d11ef · outbound

This paper cites What Does BERT Look At? An Analysis of BERT's Attention.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers What Does BERT Look At? An Analysis of BERT's Attention

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.823846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb30a7a3-9159-4bea-8b61-d3ee91a9544d · outbound

This paper cites an unresolved cited work.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers Unresolved cited work

Reference 2020

Resolution: unresolved; raw_fallback, observed 2026-08-10T22:35:16.352645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9ede84f7-ac27-437d-af5a-0d57c57591d5 · outbound

This paper cites Semi-Supervised Classification with Graph Convolutional Networks.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers Semi-Supervised Classification with Graph Convolutional Networks

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.859447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b6f45f6-6ae1-4c99-b7e5-3acd1c70cb5f · outbound

This paper cites A Comprehensive Review on Deep Supervision: Theories and Applications.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers A Comprehensive Review on Deep Supervision: Theories and Applications

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.874330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 597d01d7-6596-4cba-814c-57b40b247721 · outbound

This paper cites Striving for Simplicity: The All Convolutional Net.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers Striving for Simplicity: The All Convolutional Net

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.907715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4ac5581-2b2d-4c4d-a9d7-8794ee848302 · outbound

This paper cites Setting the Record Straight on Transformer Oversmoothing.

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers Setting the Record Straight on Transformer Oversmoothing

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-10T22:35:15.843954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.