Paper Citation Record · LEDGER

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement

As of 6 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2607.08782.

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

pith.paper-citation-record.v1
2607.08782 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-13T07:33:31.233659Z

measured 47 of 47 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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

47 of 47 outbound references displayed

verified exact0
verified fuzzy0
unresolved47
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 71c0feb2-454e-43a2-a59e-0918221ad819 · outbound

This paper cites The llama 4 herd: Native multimodality with a mixture-of-experts architecture,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement The llama 4 herd: Native multimodality with a mixture-of-experts architecture,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 48494770-eec2-44f4-8c50-deb0ede79d68 · outbound

This paper cites Qwen Technical Report.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Qwen Technical Report

Reference 2

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 18e0be56-6e26-4f66-a104-7984db799e4c · outbound

This paper cites Qwen2 Technical Report.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Qwen2 Technical Report

Reference 3

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation f3b369a3-e028-4566-b453-de0b06b67d43 · outbound

This paper cites Qwen3 Technical Report.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Qwen3 Technical Report

Reference 4

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 2f6b8dd7-222e-4ef7-8749-f57edca5d5d8 · outbound

This paper cites Deepseekmoe: Towards ultimate expert special- ization in mixture-of-experts language models,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Deepseekmoe: Towards ultimate expert special- ization in mixture-of-experts language models,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation b1b2d8e5-a5d8-4b8f-8d87-71ca2e652886 · outbound

This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 6

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation bea30814-d9e0-4b9b-ba02-7f3b80652752 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation b7145a54-95c9-41ca-a992-a8fa5507a256 · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 8

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 32ccd246-4750-4998-a950-14c421ec618e · outbound

This paper cites Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Switch transformers: Scaling to trillion parameter models with simple and efficient sparsity,

Reference 9

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation be38d49d-9f9f-4106-a249-727b50e1c613 · outbound

This paper cites Training and serving system of foundation models: A comprehensive survey,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Training and serving system of foundation models: A comprehensive survey,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 0b707fd0-2320-4a08-8605-a777043164e0 · outbound

This paper cites GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement GShard: Scaling Giant Models with Conditional Computation and Automatic Sharding

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation bbe6a236-87ec-4f2a-8ce0-081dd5b14598 · outbound

This paper cites Expert Parallelism Load Balancer,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Expert Parallelism Load Balancer,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 24f749bb-d31b-4939-8969-0157822bdb8f · outbound

This paper cites MoETuner: Optimized Mixture of Expert Serving with Balanced Expert Placement and Token Routing.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement MoETuner: Optimized Mixture of Expert Serving with Balanced Expert Placement and Token Routing

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation cddb2fcc-6a73-4f92-b880-dc3ef26b1bfc · outbound

This paper cites Fastermoe: modeling and optimizing training of large-scale dynamic pre-trained models,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Fastermoe: modeling and optimizing training of large-scale dynamic pre-trained models,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation c78b379b-df68-4619-8db1-9858a59402b0 · outbound

This paper cites Flexmoe: Scaling large-scale sparse pre-trained model training via dynamic device placement,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Flexmoe: Scaling large-scale sparse pre-trained model training via dynamic device placement,

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 74586f9a-5891-4573-9cb6-2fed3ee064be · outbound

This paper cites Tutel: Adaptive mixture-of-experts at scale,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Tutel: Adaptive mixture-of-experts at scale,

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation fafe8728-0916-4fe6-a9d7-0ef069f784fd · outbound

This paper cites Smartmoe: Efficiently training sparsely-activated models through combining offline and online parallelization,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Smartmoe: Efficiently training sparsely-activated models through combining offline and online parallelization,

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation ccfb7257-2d96-4479-bd40-be44abe62166 · outbound

This paper cites Janus: A unified distributed training framework for sparse mixture-of-experts models,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Janus: A unified distributed training framework for sparse mixture-of-experts models,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation b107627a-7203-4562-8eaa-cf9274888b8f · outbound

This paper cites A branch-and-price algorithm for the generalized assignment problem,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement A branch-and-price algorithm for the generalized assignment problem,

Reference 19

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation c2005257-f228-46cb-8b67-b80488bd173b · outbound

This paper cites Outrageously large neural networks: The sparsely-gated mixture-of-experts layer,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Outrageously large neural networks: The sparsely-gated mixture-of-experts layer,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 3d59945a-81e2-4493-ad5b-3d63ea496774 · outbound

This paper cites Not all experts are equal: Efficient expert pruning and skipping for mixture-of-experts large language models,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Not all experts are equal: Efficient expert pruning and skipping for mixture-of-experts large language models,

Reference 21

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 331452d3-39fa-4727-a2c2-478da7597b75 · outbound

This paper cites Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 94ddfb38-3c0e-445f-b4aa-16d41209b88e · outbound

This paper cites Ta-moe: topology-aware large scale mixture-of-expert training,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Ta-moe: topology-aware large scale mixture-of-expert training,

Reference 23

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 841e3ee0-2273-4423-8c2f-e9876c47a1e4 · outbound

This paper cites Schemoe: An extensible mixture-of-experts distributed training system with tasks scheduling,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Schemoe: An extensible mixture-of-experts distributed training system with tasks scheduling,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation c1906339-2fb5-4bb6-806a-4533246a13f5 · outbound

This paper cites Fsmoe: A flexible and scalable training system for sparse mixture-of- experts models,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Fsmoe: A flexible and scalable training system for sparse mixture-of- experts models,

Reference 25

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 7820b9a8-a016-45c4-81f2-e6c1421539a6 · outbound

This paper cites Pipemoe: Accelerating mixture-of- experts through adaptive pipelining,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Pipemoe: Accelerating mixture-of- experts through adaptive pipelining,

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation f97f1395-c9a5-4006-8c38-2d3ca225806d · outbound

This paper cites Klotski: Efficient mixture-of-expert inference via expert- aware multi-batch pipeline,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Klotski: Efficient mixture-of-expert inference via expert- aware multi-batch pipeline,

Reference 27

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation f0ba0975-dc1d-4c19-95d6-b7b35fcfc859 · outbound

This paper cites Parm: Efficient training of large sparsely-activated models with dedicated schedules,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Parm: Efficient training of large sparsely-activated models with dedicated schedules,

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 8a3cca7c-417a-4e5a-95db-0327bfd5738f · outbound

This paper cites Expertflow: Optimized expert activation and token allocation for efficient mixture-of-experts inference,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Expertflow: Optimized expert activation and token allocation for efficient mixture-of-experts inference,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation d86a64ba-7f11-4099-86a0-2edbbba1cadf · outbound

This paper cites Netmoe: Accelerating moe training through dynamic sample placement,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Netmoe: Accelerating moe training through dynamic sample placement,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 123b17a5-97a2-4d20-b60a-a87de76a0b84 · outbound

This paper cites Communication-efficient sparsely-activated model training via sequence migration and token condensation,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Communication-efficient sparsely-activated model training via sequence migration and token condensation,

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 4c58dac2-856e-4c2b-b276-5e56a7dfbb84 · outbound

This paper cites {PopFetcher}: Towards accelerated{Mixture-of-Experts} training via popularity based{Expert-Wise}prefetch,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement {PopFetcher}: Towards accelerated{Mixture-of-Experts} training via popularity based{Expert-Wise}prefetch,

Reference 32

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Observation a6c6aaf9-5c03-4fac-bdd8-c85e6d8dafb9 · outbound

This paper cites Pointer sentinel mixture models,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Pointer sentinel mixture models,

Reference 33

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Observation e9b0cdf9-1c1d-413d-94f9-79187c4b3fd6 · outbound

This paper cites Let’s verify step by step,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Let’s verify step by step,

Reference 34

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Observation 77e01d70-f73b-4627-ab4e-faddceecc7bb · outbound

This paper cites LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

Reference 35

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation e6faae90-ae8f-448d-80ae-182c0136819c · outbound

This paper cites Sida: Sparsity-inspired data-aware serving for efficient and scalable large mixture-of-experts models,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Sida: Sparsity-inspired data-aware serving for efficient and scalable large mixture-of-experts models,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation c8d1d64e-c068-4277-91ef-084b3ea4656e · outbound

This paper cites D2moe: Dual routing and dynamic scheduling for efficient on-device moe-based llm serving,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement D2moe: Dual routing and dynamic scheduling for efficient on-device moe-based llm serving,

Reference 37

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Observation 956de3b5-8403-46fd-b8f7-39f8579d400a · outbound

This paper cites On tail probabilities for martingales,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement On tail probabilities for martingales,

Reference 38

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 028ef24d-fbed-4d1d-8fe2-e5df50c91534 · outbound

This paper cites Approximation-friendly discrepancy rounding,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Approximation-friendly discrepancy rounding,

Reference 39

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 4598b9de-4a95-4b56-a6ef-0d41ab7190b2 · outbound

This paper cites Constructive algorithms for discrepancy minimization,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Constructive algorithms for discrepancy minimization,

Reference 40

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation cca1fb54-86cb-4c2f-9f1b-ae856b7140a1 · outbound

This paper cites Constructive discrepancy minimization by walking on the edges,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Constructive discrepancy minimization by walking on the edges,

Reference 41

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 69dba63c-6654-492c-b57f-959fafb26a4d · outbound

This paper cites an unresolved cited work.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Unresolved cited work

Reference 42

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Observation 92948a4d-ada3-452c-9b64-82e238762421 · outbound

This paper cites Colossal-ai: A unified deep learning system for large-scale parallel training,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Colossal-ai: A unified deep learning system for large-scale parallel training,

Reference 43

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 9f6a9bee-96a4-4073-a222-2c0425e81814 · outbound

This paper cites SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python,

Reference 44

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 7b0199b4-506e-474d-bfc8-aa45181ed28a · outbound

This paper cites Awq: Activation-aware weight quantization for on-device llm compression and acceleration,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Awq: Activation-aware weight quantization for on-device llm compression and acceleration,

Reference 45

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation 6ad07ccf-7bdb-46fa-9321-6577a8bc15a3 · outbound

This paper cites Mixtral of Experts.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Mixtral of Experts

Reference 46

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Observation aa84e84b-573e-4dd3-be77-850c19cb1365 · outbound

This paper cites Deepspeed-moe: Advancing mixture-of-experts inference and training to power next-generation ai scale,.

Director: Accelerating Distributed MoE Serving via Online Proactive Expert Placement Deepspeed-moe: Advancing mixture-of-experts inference and training to power next-generation ai scale,

Reference 47

Resolution: unresolved; no resolver link, observed 2026-07-13T07:33:31.233659Z

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Pith citing papers

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