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Paper Citation Record · LEDGER

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training

As of 18 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2607.22614.

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

pith.paper-citation-record.v1
2607.22614 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T11:14:02.893027Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

41 of 41 outbound references displayed

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  • unresolved41
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External citation measurements

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Outbound references

Observation 431f9042-c323-4147-8be6-22b5af8328c0 · outbound

This paper cites 2025.Training-Free Group Relative Policy Optimization.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training 2025.Training-Free Group Relative Policy Optimization

Reference 1

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source=pdf_text observed=2026-08-02T11:13:59.202663Z digest=sha256:b67f180518aaf3491194617567c4b136f759d379b71bb93467dfb6807b2dce52

Observation a579108a-d7d1-4102-84e2-6944a3776cde · outbound

This paper cites an unresolved cited work.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

Reference 2

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Observation 3a92ece5-3fd6-4962-9ea1-44fe1a5ab89b · outbound

This paper cites an unresolved cited work.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

Reference 3

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source=pdf_text observed=2026-08-02T11:13:59.364418Z digest=sha256:8798b4a469886c21121617a01c5f3a9bdc5b50ba40a6495d02137fb1eb2f30ea

Observation 0615b364-8985-429f-b35d-ff598d61b3a2 · outbound

This paper cites The Llama 3 Herd of Models.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training The Llama 3 Herd of Models

Reference 4

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Observation 64ffcc2a-3cd9-4eea-bcba-de093c193ae0 · outbound

This paper cites Truncated Proximal Policy Optimization.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Truncated Proximal Policy Optimization

Reference 5

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source=pdf_text observed=2026-08-02T11:13:59.500195Z digest=sha256:be99b889f6d5ce6eb1b86d479b9c7ea19e1bc1effa538c8efadeac211d02d0dd

Observation 4a1c46ae-723a-478a-990e-bf9e9890cca4 · outbound

This paper cites AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning

Reference 6

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source=pdf_text observed=2026-08-02T11:13:59.560465Z digest=sha256:018a9c9107c6ab3501cb3851c19e2c01020547b6c9bbc90173a64f77607ef70c

Observation 934a0579-dea5-41cb-89e3-6eddc2b36e16 · outbound

This paper cites an unresolved cited work.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

Reference 7

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source=pdf_text observed=2026-08-02T11:13:59.614113Z digest=sha256:44f98f61f0f2c6b04a855385187b7590fdf46b8b432428defe92e80d477d5d9a

Observation a36a1558-768b-40de-9ae5-7aceb0913ee1 · outbound

This paper cites ROSE: Rollout On Serving GPUs via Cooperative Elasticity for Agentic RL.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training ROSE: Rollout On Serving GPUs via Cooperative Elasticity for Agentic RL

Reference 8

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source=pdf_text observed=2026-08-02T11:13:59.715326Z digest=sha256:edf44705d0d247063fa58a3fb2f69654e133ff0e5489d94c22f823063e743056

Observation baa5ca5c-598f-4937-ba7a-7c0a3fb3e31a · outbound

This paper cites Multi-Bin Batching for Increasing LLM Inference Throughput.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Multi-Bin Batching for Increasing LLM Inference Throughput

Reference 9

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source=pdf_text observed=2026-08-02T11:13:59.783585Z digest=sha256:174a32cfc12dd4d12f2168ebd0d50d89558887c6e292b5d2ef1f7d2244680364

Observation b2a7c890-de8e-43d3-bd39-5f0139bbfee1 · outbound

This paper cites AsyncFlow: An Asynchronous Streaming RL Framework for Efficient LLM Post-Training.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training AsyncFlow: An Asynchronous Streaming RL Framework for Efficient LLM Post-Training

Reference 10

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source=pdf_text observed=2026-08-02T11:13:59.835182Z digest=sha256:3b7fa7764758f8c6fc63742f3face41bde4cb04be13ac3fb399b44034067e53e

Observation 4b1b6617-ecc0-486d-ae53-b3a0e3134f96 · outbound

This paper cites an unresolved cited work.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

Reference 11

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Observation 69b1ceb7-c6eb-4321-98db-b95fef3aa2b0 · outbound

This paper cites Efficient Memory Management for Large Language Model Serving with PagedAttention.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Efficient Memory Management for Large Language Model Serving with PagedAttention

Reference 12

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Observation c920d508-64bc-4f6d-b9d8-261ba752fd9e · outbound

This paper cites ReaL: Efficient RLHF Training of Large Language Models with Parameter Reallocation.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training ReaL: Efficient RLHF Training of Large Language Models with Parameter Reallocation

Reference 13

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Observation 9363794a-c91b-4bd0-a8cd-c42d2c498d46 · outbound

This paper cites Jordan, and Ion Stoica.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Jordan, and Ion Stoica

Reference 14

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source=pdf_text observed=2026-08-02T11:14:00.236726Z digest=sha256:0f9ac77ccba015f9e8f49de5f3e0b2c7e7839d0d2725081b8948a5b42a4dfab6

Observation 800d9ab0-6c63-49a5-b5c0-cf0998cda45f · outbound

This paper cites an unresolved cited work.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

Reference 15

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Observation 52528263-6885-4fa1-aa06-0faa8c3ed7ae · outbound

This paper cites Or et al.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Or et al

Reference 16

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source=pdf_text observed=2026-08-02T11:14:00.489562Z digest=sha256:be8ef0c0384880313ee5f61fa5ccf83d6c89a587436f33137eb39a12a2de9eb9

Observation 467d101b-13aa-4c6b-a590-fc093c2139b2 · outbound

This paper cites an unresolved cited work.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

Reference 17

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Observation 636b03fe-871f-4f16-bdce-22cf65cc0d47 · outbound

This paper cites an unresolved cited work.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

Reference 18

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Observation 7bb1c0f3-0cd4-4b14-8fe8-d3314c7601b5 · outbound

This paper cites an unresolved cited work.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

Reference 19

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Observation 203322d9-e1de-4299-938e-2b10dd30ebc5 · outbound

This paper cites an unresolved cited work.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

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Observation 3ab533a5-50d8-445b-92df-50f0f278bf79 · outbound

This paper cites Rajbhandari et al.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Rajbhandari et al

Reference 21

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Observation e1ae4feb-551d-42a5-bce0-cf652054424e · outbound

This paper cites an unresolved cited work.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

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Observation ef1bd6c9-7f1a-4fae-9c84-da8c1dc64402 · outbound

This paper cites an unresolved cited work.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

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Observation 3a025a21-d411-4d74-9349-f99f7f0bdeb7 · outbound

This paper cites Proximal Policy Optimization Algorithms.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Proximal Policy Optimization Algorithms

Reference 24

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Observation 93699b67-0772-472d-ae34-ee3f2b1d16ff · outbound

This paper cites an unresolved cited work.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

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Observation 67a18c02-0280-49ca-b842-6973ac330add · outbound

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DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

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Observation 4fc783c1-1122-4b43-b0dc-ae9333ccf17c · outbound

This paper cites an unresolved cited work.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

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Observation ac469568-a099-45e2-8356-24ee1eecb66e · outbound

This paper cites Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

Reference 28

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Observation c840c3b6-9bbd-424e-8df7-fd78f017bb59 · outbound

This paper cites Kimi k1.5: Scaling Reinforcement Learning with LLMs.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Kimi k1.5: Scaling Reinforcement Learning with LLMs

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Observation 5a773f85-f1fd-4ca5-9695-c49bdf381ce5 · outbound

This paper cites Qwen3 Technical Report.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Qwen3 Technical Report

Reference 30

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Observation 386e4ac9-87be-4ee8-a8d3-70af9b5d3e3a · outbound

This paper cites an unresolved cited work.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

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Observation 473eea03-8611-4288-b0c2-cd082772b9ec · outbound

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DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

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Observation 73182606-3436-4471-b46d-db063113c303 · outbound

This paper cites ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning

Reference 33

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Observation 2301aad0-1026-4c15-8f8b-bf7f81c3ee77 · outbound

This paper cites 2025.RLinf: Flexible and Efficient Large-scale Reinforcement Learning via Macro-to-Micro Flow Transformation.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training 2025.RLinf: Flexible and Efficient Large-scale Reinforcement Learning via Macro-to-Micro Flow Transformation

Reference 34

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Observation 3a13db93-354b-424b-917e-237f01af6d8b · outbound

This paper cites an unresolved cited work.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

Reference 35

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Observation c81ed167-a5cd-4dd1-a8dc-b5e68d3bd6b0 · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 36

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Observation 1c460363-5ad0-431e-a078-5c88ae885e9b · outbound

This paper cites 2026.ProRL Agent: Rollout-as-a-Service for RL Training of Multi-Turn LLM Agents.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training 2026.ProRL Agent: Rollout-as-a-Service for RL Training of Multi-Turn LLM Agents

Reference 37

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Observation 06e8427e-55ea-4cc8-aad2-8b4715de6660 · outbound

This paper cites an unresolved cited work.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

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Observation 53a5e31d-1727-43dd-8941-23f6ea389511 · outbound

This paper cites PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel

Reference 39

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no resolver link, observed 2026-08-02T11:14:02.713440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T11:14:02.713440Z digest=sha256:7f712d95e761ef5718b994035d416ff35b51f3e8a2428d1bdd22ed6f26dab12a

Observation 93385d83-f220-429d-b857-c316bd578466 · outbound

This paper cites 2025.APRIL: Active Partial Rollouts in Reinforcement Learning to tame long-tail generation.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training 2025.APRIL: Active Partial Rollouts in Reinforcement Learning to tame long-tail generation

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-02T11:14:02.821325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T11:14:02.821325Z digest=sha256:e8f1e883b041820f700d6ef72d6ce3af3ab71c10c39468ecd86014b1586765e4

Observation 614a081e-182b-4527-bd5f-f3134f7b24d5 · outbound

This paper cites an unresolved cited work.

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training Unresolved cited work

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-02T11:14:02.893027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T11:14:02.893027Z digest=sha256:a2241d63952e0fa9089bd103c69767a00386064571664db05d465559f6e079dc

Pith citing papers

No inbound Pith citation observations are available.