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Paper Citation Record · LEDGER

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM

As of 22 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 0 inbound Pith citation observations for arXiv:2508.10553.

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

pith.paper-citation-record.v1
2508.10553 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:24:37.625786Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Source: cited_works

Reference resolution

35 of 35 outbound references displayed

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  • unresolved10
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External citation measurements

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Outbound references

Observation 882860f5-94d9-42c7-8e34-5c7909a7f9ae · outbound

This paper cites TransformerLens,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM TransformerLens,

Reference 1

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Observation be48d125-3362-4bcf-92a3-8c6e0c21ba14 · outbound

This paper cites An explainable transformer circuit for compositional generalization.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM An explainable transformer circuit for compositional generalization

Reference 2

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Observation 047c50a1-79bc-4e2a-9aa4-5c7eb1bdf6de · outbound

This paper cites Mechanistic Interpretability for AI Safety -- A Review.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM Mechanistic Interpretability for AI Safety -- A Review

Reference 3

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Observation 53d34682-c91c-4b6d-8d49-ff99880257c3 · outbound

This paper cites The 2024 Foundation Model Transparency Index.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM The 2024 Foundation Model Transparency Index

Reference 4

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Observation 4df88607-2299-4d92-bf80-3df3f4b60615 · outbound

This paper cites Comprehensive Analysis of Transparency and Accessibility of ChatGPT, DeepSeek, And other SoTA Large Language Models.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM Comprehensive Analysis of Transparency and Accessibility of ChatGPT, DeepSeek, And other SoTA Large Language Models

Reference 5

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Observation 681f64ce-b388-4ce4-9d8f-4c6d968cf882 · outbound

This paper cites NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals

Reference 6

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Observation 59350acb-0aec-4aa8-ab73-0e3ec09872d3 · outbound

This paper cites pyvene: A Library for Understanding and Improving PyTorch Models via Interventions.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM pyvene: A Library for Understanding and Improving PyTorch Models via Interventions

Reference 7

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Observation e7e4e0c4-d076-466c-a1fb-8230dc6fb934 · outbound

This paper cites baukit: Tools for inspecting and intervening in PyTorch models,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM baukit: Tools for inspecting and intervening in PyTorch models,

Reference 8

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Observation 235c002e-6966-439e-9811-831c54278b69 · outbound

This paper cites LUMI: One of the EuroHPC world-class su- percomputers,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM LUMI: One of the EuroHPC world-class su- percomputers,

Reference 9

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Observation 6511b32c-fe1f-46c3-bb94-8183ff6268ac · outbound

This paper cites MareNostrum 5,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM MareNostrum 5,

Reference 10

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Observation f2df32d3-2a10-4cc6-a18e-be0e6aeaaf90 · outbound

This paper cites NVIDIA RTX A6000 Datasheet,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM NVIDIA RTX A6000 Datasheet,

Reference 11

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Observation 27f11f85-cd27-4f83-886f-10b37f0347c3 · outbound

This paper cites Ubuntu 22.04 LTS released,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM Ubuntu 22.04 LTS released,

Reference 12

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Observation 25b6a966-5639-401d-920f-220c2da515dd · outbound

This paper cites Scalable parallel programming with CUDA,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM Scalable parallel programming with CUDA,

Reference 13

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Observation 2a6d3818-e0bd-486b-b6b8-366fcaa203fb · outbound

This paper cites Overview — Ray,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM Overview — Ray,

Reference 14

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Observation 7543f172-0a2e-490a-9180-295f647bcbd3 · outbound

This paper cites MinIO: High-performance, S3 compatible object storage,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM MinIO: High-performance, S3 compatible object storage,

Reference 15

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Observation 23f573df-37c7-4dc5-b39e-a5dd750c82d2 · outbound

This paper cites Grafana Loki.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM Grafana Loki

Reference 16

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Observation 8befef27-aded-4e92-bf84-25d1459b08da · outbound

This paper cites Prometheus: Overview,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM Prometheus: Overview,

Reference 17

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Observation 3d3ce713-6441-4234-a788-7b6c01c46ad7 · outbound

This paper cites InfluxDB Overview.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM InfluxDB Overview

Reference 18

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Observation 5a15d690-fda4-4373-b6b1-6a879878fcbf · outbound

This paper cites Available: https://grafana.com/grafana/ [Accessed: Jul.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM Available: https://grafana.com/grafana/ [Accessed: Jul

Reference 19

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Observation 081e642e-cc1a-44b9-a41f-1297e9cc83f8 · outbound

This paper cites NCCL – NVIDIA Collective Communications Library,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM NCCL – NVIDIA Collective Communications Library,

Reference 20

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Observation 7a0d09fe-ca79-4ead-8e75-47394431c724 · outbound

This paper cites RCCL – ROCm Collective Communica- tion Library,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM RCCL – ROCm Collective Communica- tion Library,

Reference 21

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Observation 59d1451b-4013-4243-96ab-d793a4144b65 · outbound

This paper cites NDIF: Development Guide,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM NDIF: Development Guide,

Reference 22

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Observation 47d6d16d-e3cb-4f21-a061-602b42d89bbf · outbound

This paper cites Available: https://huggingface.co/ openai-community/gpt2 [Accessed: Jul.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM Available: https://huggingface.co/ openai-community/gpt2 [Accessed: Jul

Reference 23

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Observation 6363951a-ac76-4354-ac5b-ab3aff6dd4b9 · outbound

This paper cites DeepSeek-R1-Distill-Llama-8B,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM DeepSeek-R1-Distill-Llama-8B,

Reference 24

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Observation 37b511a8-fbbf-4097-a082-f4aa7482dbee · outbound

This paper cites DeepSeek-R1-Distill-Llama-70B,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM DeepSeek-R1-Distill-Llama-70B,

Reference 25

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Observation be0f080c-f536-4079-9222-2c44c3f38b46 · outbound

This paper cites Singularity: Scientific containers for mobility of compute,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM Singularity: Scientific containers for mobility of compute,

Reference 26

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Observation cb9dfa7f-4e8a-41f0-b73a-b35dc5ef6880 · outbound

This paper cites How to use and interpret activation patching.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM How to use and interpret activation patching

Reference 27

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Observation 673b60c8-2421-436c-98ca-078212928239 · outbound

This paper cites interpreting GPT: the logit lens,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM interpreting GPT: the logit lens,

Reference 28

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Observation 187e5506-b9cc-4c70-99af-44ceed3be112 · outbound

This paper cites Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM Sparse Feature Circuits: Discovering and Editing Interpretable Causal Graphs in Language Models

Reference 29

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Observation ca11cc45-4a5e-4914-a1bb-addcfccb54b8 · outbound

This paper cites LLM Circuit Analyses Are Consistent Across Training and Scale.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM LLM Circuit Analyses Are Consistent Across Training and Scale

Reference 30

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Observation dffb666f-3809-4e4a-bb5f-0ae318c8af41 · outbound

This paper cites Available: https://github.com/ QwenLM/Qwen [Accessed: Jul.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM Available: https://github.com/ QwenLM/Qwen [Accessed: Jul

Reference 31

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Observation 0f984e2f-9f99-43e7-a2b3-7a512986deec · outbound

This paper cites Available: https://deepmind.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM Available: https://deepmind

Reference 32

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Observation 4abab392-8b65-4910-bca6-6c6de1a883f4 · outbound

This paper cites A Mathematical Framework for Transformer Circuits,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM A Mathematical Framework for Transformer Circuits,

Reference 33

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Observation a5d4c5ca-bf5d-432a-a5a2-3c5743bf00a8 · outbound

This paper cites Neuronpedia,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM Neuronpedia,

Reference 34

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Observation 1ee951df-5e4c-409f-8613-b2bd87288bf1 · outbound

This paper cites AMD vs NVIDIA Inference Benchmark: Who Wins? – Performance & Cost Per Million Tokens,.

eDIF: A European Deep Inference Fabric for Remote Interpretability of LLM AMD vs NVIDIA Inference Benchmark: Who Wins? – Performance & Cost Per Million Tokens,

Reference 35

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No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-05T20:24:37.625786Z digest=sha256:903d4fc87e6f2398211158c58d5d162d6310f8fa0bfb32f8d1fb77a7fad3c8c5

Pith citing papers

No inbound Pith citation observations are available.