Paper Citation Record · LEDGER

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning

As of 6 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 2 inbound Pith citation observations for arXiv:2602.02192.

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

pith.paper-citation-record.v1
2602.02192 v5

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T05:32:43.300084Z

measured 34 of 34 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T11:14:02.042304Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T14:20:29.515746Z

Reference resolution

32 of 32 outbound references displayed

verified exact0
verified fuzzy0
unresolved32
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fd332074-d05c-4168-a0d0-555cfd9ae0fc · outbound

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

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:40.373432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b736313e-0f23-4fbc-a511-49330b90fc59 · outbound

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

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:40.415345Z

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Unavailable: canonical work link unavailable.

Observation aaf7e38d-3e5e-4cb7-8a64-a84d9bd2f09f · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:40.495376Z

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Unavailable: canonical work link unavailable.

Observation 5769c27c-b16c-4a2a-8016-ed45413e7fe7 · outbound

This paper cites Proximal policy optimization algorithms, 2017.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Proximal policy optimization algorithms, 2017

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:40.591203Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 94293c0e-e9fd-4b58-9554-6c3bb9a181ae · outbound

This paper cites an unresolved cited work.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Unresolved cited work

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:40.701006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0108285f-5b65-4507-b5eb-b96e32f72cf8 · outbound

This paper cites Hybridflow: A flexible and efficient rlhf framework.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Hybridflow: A flexible and efficient rlhf framework

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:40.776914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af19c22a-1aa9-4c5b-87fb-42df5799b123 · outbound

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

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:40.837833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96d1c965-bc1d-46f9-bcf6-a69040c52b5e · outbound

This paper cites History Rhymes: Accelerating LLM Reinforcement Learning with RhymeRL.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning History Rhymes: Accelerating LLM Reinforcement Learning with RhymeRL

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:40.894045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb6b8965-7c31-4ef1-a1bd-ef3c6fc643e8 · outbound

This paper cites Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:40.971370Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 850b703d-a73a-4f39-aed9-60976c229ce6 · outbound

This paper cites StreamRL: Scalable, Heterogeneous, and Elastic RL for LLMs with Disaggregated Stream Generation.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning StreamRL: Scalable, Heterogeneous, and Elastic RL for LLMs with Disaggregated Stream Generation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:41.063975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fae02c87-3c7d-444a-9f1d-ee03fb58aea1 · outbound

This paper cites Echo: Decoupling Inference and Training for Large-Scale RL Alignment on Heterogeneous Swarms.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Echo: Decoupling Inference and Training for Large-Scale RL Alignment on Heterogeneous Swarms

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:41.151927Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4df1d50b-d04f-4206-b4a9-fc9988bf9375 · outbound

This paper cites Petals: Collaborative inference and fine-tuning of large models.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Petals: Collaborative inference and fine-tuning of large models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:41.253596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d687caa2-4372-4667-9d84-e19ce5eb68f9 · outbound

This paper cites Swarm parallelism: Training large models can be surprisingly communication-efficient.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Swarm parallelism: Training large models can be surprisingly communication-efficient

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:41.401706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ecfd94a-47e0-4d25-9fa2-aba0a051f621 · outbound

This paper cites Parallax: Efficient llm inference service over decentralized environment.arXiv preprint arXiv:2509.26182, 2025.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Parallax: Efficient llm inference service over decentralized environment.arXiv preprint arXiv:2509.26182, 2025

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:41.464947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 455bd1ca-a0a2-495c-afcd-1c5a8499f237 · outbound

This paper cites Rlax: Large-scale, distributed reinforcement learning for large language models on tpus.arXiv preprint arXiv:2512.06392, 2025.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Rlax: Large-scale, distributed reinforcement learning for large language models on tpus.arXiv preprint arXiv:2512.06392, 2025

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:41.584396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f870cc5-b633-4e0b-94a4-aec29766f9b4 · outbound

This paper cites an unresolved cited work.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Unresolved cited work

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:41.689686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72d94e30-d90c-45a2-8518-98893edff2fe · outbound

This paper cites A survey of reinforcement learning from human feedback, 2024.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning A survey of reinforcement learning from human feedback, 2024

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:41.805004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2836fbd5-05ce-498c-a907-273c8b6042fd · outbound

This paper cites Areal-hex: Accommodating asynchronous rl training over heterogeneous gpus.arXiv preprint arXiv:2511.00796, 2025.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Areal-hex: Accommodating asynchronous rl training over heterogeneous gpus.arXiv preprint arXiv:2511.00796, 2025

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:41.886782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8421379f-61e6-4d87-86cd-a33c9be4cd00 · outbound

This paper cites INTELLECT-2: A Reasoning Model Trained Through Globally Decentralized Reinforcement Learning.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning INTELLECT-2: A Reasoning Model Trained Through Globally Decentralized Reinforcement Learning

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:41.992143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f317fd13-8f3d-41f4-9670-5dc1e9ab3e3e · outbound

This paper cites Qiu, and Yuqing Yang.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Qiu, and Yuqing Yang

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:42.231201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ac433fdb-c1fc-421c-bb75-796b546a0a9c · outbound

This paper cites Prosperity before collapse: How far can off-policy rl reach with stale data on llms?arXiv preprint arXiv:2510.01161, 2025.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Prosperity before collapse: How far can off-policy rl reach with stale data on llms?arXiv preprint arXiv:2510.01161, 2025

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:42.345375Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6b64a8b-f840-41b8-b7ae-3142e11314c9 · outbound

This paper cites Qwen3 Technical Report.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Qwen3 Technical Report

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:42.396096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d228c218-06aa-42f9-949b-aaa8edfe2962 · outbound

This paper cites American invitational mathematics examination (AIME), 2024.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning American invitational mathematics examination (AIME), 2024

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:42.483348Z

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Unavailable: canonical work link unavailable.

Observation e0d579c9-2615-42c2-8439-a081d552c22b · outbound

This paper cites Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Omni-MATH: A Universal Olympiad Level Mathematic Benchmark For Large Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:42.552709Z

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Unavailable: canonical work link unavailable.

Observation 116157ac-edb2-424b-8894-81aeb5d6d64d · outbound

This paper cites Have llms advanced enough? a challenging problem solving benchmark for large language models.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Have llms advanced enough? a challenging problem solving benchmark for large language models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:42.620970Z

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Unavailable: canonical work link unavailable.

Observation 4dd2a08d-e0c7-4bf7-b6cd-a2ab1774ba98 · outbound

This paper cites HARDMath: A Benchmark Dataset for Challenging Problems in Applied Mathematics.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning HARDMath: A Benchmark Dataset for Challenging Problems in Applied Mathematics

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:42.714144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7034725-cdcd-4ec5-b007-245f53c7c885 · outbound

This paper cites Towards robust mathematical reasoning.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Towards robust mathematical reasoning

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:42.814718Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1f678e05-4b38-44b7-89b7-87586fe4b4fc · outbound

This paper cites Qwen3 technical report, 2025.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Qwen3 technical report, 2025

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:42.880251Z

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Unavailable: canonical work link unavailable.

Observation 4cb84c57-40e0-4467-abfb-42345349719a · outbound

This paper cites Openai gpt-5 system card, 2025.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Openai gpt-5 system card, 2025

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:42.969166Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7554fe2-e003-4df1-851b-73403727d48c · outbound

This paper cites Grok 4 model card.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Grok 4 model card

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:43.038027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 623f8f9c-b9da-4be0-95a2-5d9ac5067be4 · outbound

This paper cites Claude sonnet 4.5 system card.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning Claude sonnet 4.5 system card

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:43.169909Z

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Unavailable: canonical work link unavailable.

Observation 93bdf701-1019-4e37-b5f2-86740f778b31 · outbound

This paper cites moba://hok_v2.

ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning moba://hok_v2

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-03T05:32:43.300084Z

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Pith citing papers

Observation f336f62a-0335-4939-a84d-3dd93dec191b · inbound

FAST: A Synergistic Framework of Attention and State-space Models for Spatiotemporal Traffic Prediction cites this paper.

FAST: A Synergistic Framework of Attention and State-space Models for Spatiotemporal Traffic Prediction ECHO-2: A Large-Scale Distributed Rollout Framework for Cost-Efficient Reinforcement Learning

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-27T02:04:33.896984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

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

DynaResize: Runtime GPU Reallocation for Disaggregated LLM Post-Training cites this paper.

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

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-02T11:14:02.042304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.