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Paper Citation Record · LEDGER

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models

As of 7 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 1 inbound Pith citation observation for arXiv:2506.22950.

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

pith.paper-citation-record.v1
2506.22950 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:01:24.023367Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-22T07:40:35.113858Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

42 of 42 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved41
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation ae54f573-f745-4daf-ba65-108b384d61d9 · outbound

This paper cites Language Models are Few-Shot Learners.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Language Models are Few-Shot Learners

Reference 1

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source=pdf_text observed=2026-08-06T22:01:23.593717Z digest=sha256:11bc2afd1dbeca82849e427773ab0adacb2639cc2b02b522cc2e627e6b59aa51

Observation a0ffcfce-48fd-4696-8714-fe408679f181 · outbound

This paper cites an unresolved cited work.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Unresolved cited work

Reference 2

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source=pdf_text observed=2026-08-06T22:01:23.600719Z digest=sha256:e55f5291829718b82ebf2b7957be2aca24dfe88b6cba7d9f5aca0f8c2da92355

Observation 35687e8f-703a-4f9d-a023-0057372a4b2d · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Training Verifiers to Solve Math Word Problems

Reference 3

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source=pdf_text observed=2026-08-06T22:01:23.612403Z digest=sha256:1a900fa7644a0ba5ed867c28978ccf53ca91bc07f2016e71a3c40def5176a3a1

Observation 1fd0fafb-220a-499d-8d60-0cd0fefc6f90 · outbound

This paper cites FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning

Reference 4

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source=pdf_text observed=2026-08-06T22:01:23.617039Z digest=sha256:372f326007599cd2ba4fc195c67278ddffa826e7a48bf57ae7b9a9e5c1bb88b0

Observation 9ce02750-4d96-4171-96db-47d2b1064493 · outbound

This paper cites FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

Reference 5

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source=pdf_text observed=2026-08-06T22:01:23.623374Z digest=sha256:b7412725d4f347ef3b616870b3656deeb0c81fa07ffb3dcb4d3fa07aeb0bf264

Observation 02ca16c4-bb02-4f1a-9a5d-807e42616aab · outbound

This paper cites DeepSeek-V3 Technical Report.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models DeepSeek-V3 Technical Report

Reference 6

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source=pdf_text observed=2026-08-06T22:01:23.629095Z digest=sha256:51394577e124eea13d7d7e9a33b972e97516ac94856b5bca4fbc3cfb68226b97

Observation 7873e5f0-ff6d-4453-90e0-d934f9058916 · outbound

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

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 7

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Observation 7ab8bd83-868e-4506-8a6c-85bd7c9ace69 · outbound

This paper cites an unresolved cited work.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Unresolved cited work

Reference 8

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source=pdf_text observed=2026-08-06T22:01:23.643295Z digest=sha256:e06b11a1f880ddc41b53036b2ed342fef4ba173620ceea5c466467f49db8c269

Observation 21cdab9b-a7df-42a8-b479-38dd412f7c39 · outbound

This paper cites The Llama 3 Herd of Models.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models The Llama 3 Herd of Models

Reference 9

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source=pdf_text observed=2026-08-06T22:01:23.653086Z digest=sha256:115ddc96cfda96ca5bdc7de24833ddd1e15a1bf5cc0d2f1ade3d867836ff14e1

Observation 91e4a796-2636-4899-b357-0aaf145a915b · outbound

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

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models AReaL: A Large-Scale Asynchronous Reinforcement Learning System for Language Reasoning

Reference 10

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Observation e2a12bd6-bce4-45fc-a22b-36429e1786d8 · outbound

This paper cites an unresolved cited work.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Unresolved cited work

Reference 11

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Observation c0a218a9-1eb2-46de-ad02-6bbad8992223 · outbound

This paper cites an unresolved cited work.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Unresolved cited work

Reference 12

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source=pdf_text observed=2026-08-06T22:01:23.657733Z digest=sha256:1336b0cac31b4c23bbf92e3e226b0dfdb329bee1ee1f5b9cd87cfc8e86e748e6

Observation 3a7bf3c4-4390-4b18-83b9-b8bd7623e577 · outbound

This paper cites Let's Verify Step by Step.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Let's Verify Step by Step

Reference 13

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source=pdf_text observed=2026-08-06T22:01:23.678791Z digest=sha256:35fb16f4038134b26dba0e6edadd8c2b1fe39ddcbbd173f970019a9515d05235

Observation e5c73d4f-ed82-425e-bdd1-a28487e13bd2 · outbound

This paper cites an unresolved cited work.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Unresolved cited work

Reference 14

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source=pdf_text observed=2026-08-06T22:01:23.683935Z digest=sha256:9aed20e438c3306b49010efa414b58d368341c65bc4f4126b6a8cfbae381c35d

Observation 0324c5d3-8bfb-43a9-b25e-f78c9f0978cd · outbound

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

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Efficient Memory Management for Large Language Model Serving with PagedAttention

Reference 15

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source=pdf_text observed=2026-08-06T22:01:23.672951Z digest=sha256:d05c6680700ca5683b25583b01ca4e1f8548fcf602d1f8e4c7350454b7e3d7be

Observation 83df7646-07b1-49a2-8b27-64def2f8506a · outbound

This paper cites Training language models to follow instructions with human feedback.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Training language models to follow instructions with human feedback

Reference 16

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Observation 556c831d-9d4d-4ebb-a79a-5b862a0c33b8 · outbound

This paper cites Efficiently Scaling Transformer Inference.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Efficiently Scaling Transformer Inference

Reference 17

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Observation 1b26baf4-b9f6-4004-89de-59e4080fa7a5 · outbound

This paper cites an unresolved cited work.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Unresolved cited work

Reference 18

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Observation 075eb96c-3cca-4954-8d59-bee904c6f77b · outbound

This paper cites an unresolved cited work.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Unresolved cited work

Reference 19

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source=pdf_text observed=2026-08-06T22:01:23.716259Z digest=sha256:1fb6dc8aa5e17ea5b0e680da9f8779d56a30b1afbe529e043c894eca6243a29a

Observation e24bbe5b-553d-4f20-8d0e-ab7256611dc3 · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 20

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Observation e501a27e-f3b9-4dd4-a11f-b5cb318a822c · outbound

This paper cites Kalbarczyk, Tamer Başar, and Ravishankar K.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Kalbarczyk, Tamer Başar, and Ravishankar K

Reference 21

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source=pdf_text observed=2026-08-06T22:01:23.706120Z digest=sha256:0394a836e1cb2425e127a3ff32ec89a19dbc8494d9de9acd427befe619c157e4

Observation 7831e371-0d79-4ee5-8c34-0a809bbc6b12 · outbound

This paper cites Efficient Interactive LLM Serving with Proxy Model-based Sequence Length Prediction.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Efficient Interactive LLM Serving with Proxy Model-based Sequence Length Prediction

Reference 22

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Observation 6342af0b-bbc0-4141-996f-1ae6c8fbad3a · outbound

This paper cites an unresolved cited work.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Unresolved cited work

Reference 23

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Observation 752630ae-3137-4788-a1d3-27aaf5239c58 · outbound

This paper cites an unresolved cited work.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Unresolved cited work

Reference 24

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source=pdf_text observed=2026-08-06T22:01:23.749311Z digest=sha256:444f553908b25bd897ad179337eba5d6ef9ca95c7d775b4712feb65ed7fe8d6a

Observation 526b10c1-46cf-4202-9774-2f0bc85bace8 · outbound

This paper cites ZeRO: Memory Optimizations Toward Training Trillion Parameter Models.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models ZeRO: Memory Optimizations Toward Training Trillion Parameter Models

Reference 25

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source=pdf_text observed=2026-08-06T22:01:23.728685Z digest=sha256:cc99d312314fe381e92d19ba49192dc6230028ccb1ab06740f3bb9863a5f9066

Observation e2b3638e-38a1-4326-946c-6c6f81a290f7 · outbound

This paper cites ZeRO-Infinity: Breaking the GPU Memory Wall for Extreme Scale Deep Learning.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models ZeRO-Infinity: Breaking the GPU Memory Wall for Extreme Scale Deep Learning

Reference 26

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source=pdf_text observed=2026-08-06T22:01:23.734112Z digest=sha256:810513df82914c78778f2f79863fa0ab551b1a1de83a0aebbf0182fe848e9caa

Observation 461a5b00-b6bf-454a-900d-d65b113bee91 · outbound

This paper cites Keep the Cost Down: A Review on Methods to Optimize LLM' s KV-Cache Consumption.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Keep the Cost Down: A Review on Methods to Optimize LLM' s KV-Cache Consumption

Reference 27

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Observation e8c2a1ec-fe9e-4a25-8d62-26aaef5ee500 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 28

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Observation 43b9d60f-dec3-466c-932b-8145eee0f448 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 29

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source=pdf_text observed=2026-08-06T22:01:23.778031Z digest=sha256:89aea144718e0f6cdb802d19325d550336c353d6a2fdffbc1c775e7e00a20fb7

Observation 5058069b-c939-46af-9846-4f54c05fc867 · outbound

This paper cites On Memorization of Large Language Models in Logical Reasoning.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models On Memorization of Large Language Models in Logical Reasoning

Reference 30

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source=pdf_text observed=2026-08-06T22:01:23.782702Z digest=sha256:ff1ec6232a63319fe6b0cc6618dfe7430c091e2a73b83e955bb9e2fd3d02e462

Observation 1ca1adcf-f569-4157-91bf-3b52a2fd4607 · outbound

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

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 31

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Observation f3b65236-2515-4339-9181-4264bc3c47bf · outbound

This paper cites an unresolved cited work.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Unresolved cited work

Reference 32

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source=pdf_text observed=2026-08-06T22:01:23.764379Z digest=sha256:77c32ce85dae5ee1f0887f7d3a533a33ece2cafea85b0ae35efd7a2cb56c2846

Observation fe41b33c-e4ed-4d4c-b436-b80dc72d7493 · outbound

This paper cites SGLang: Efficient Execution of Structured Language Model Programs.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models SGLang: Efficient Execution of Structured Language Model Programs

Reference 33

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Observation dfb51034-43cd-4758-80a4-22ac06a00aa4 · outbound

This paper cites an unresolved cited work.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Unresolved cited work

Reference 34

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source=pdf_text observed=2026-08-06T22:01:23.837341Z digest=sha256:0e8fc915fde63cb79eba4271813691b2eb6557fb090543527a177e5a4cbe2032

Observation 09a90acc-3fd0-4efd-8eda-2e08a99ff9bb · outbound

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

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models StreamRL: Scalable, Heterogeneous, and Elastic RL for LLMs with Disaggregated Stream Generation

Reference 35

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source=pdf_text observed=2026-08-06T22:01:24.023367Z digest=sha256:e32ef9be087508daf14eaa649631e3e7aa666f3954ad4362cd840c49de81eca9

Observation 3a569497-5cc8-4f5e-89d9-40f93c10517d · outbound

This paper cites Qwen3 Technical Report.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Qwen3 Technical Report

Reference 37

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source=pdf_text observed=2026-08-06T22:01:23.788123Z digest=sha256:7038abc43861ed4ada241dba286b6ebae88d3738aed4d63acd81d92e8907d373

Observation 0abfcd2f-2d7b-478b-bbc5-bb11e48aa632 · outbound

This paper cites LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

Reference 38

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source=pdf_text observed=2026-08-06T22:01:23.797749Z digest=sha256:2fd2632ce700a10720e952aa73f9bcf69335ce1cd75f4d716f4abae77b1c9b59

Observation 584b6f7e-317a-418d-96e6-b6d1030f27e3 · outbound

This paper cites BatchLLM: Optimizing Large Batched LLM Inference with Global Prefix Sharing and Throughput-oriented Token Batching.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models BatchLLM: Optimizing Large Batched LLM Inference with Global Prefix Sharing and Throughput-oriented Token Batching

Reference 41

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Observation f353a0ea-3b89-42f4-bdd7-4bd10b908e8e · outbound

This paper cites Proximal Policy Optimization Algorithms.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Proximal Policy Optimization Algorithms

Reference 2017

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source=pdf_text observed=2026-08-06T22:01:23.755199Z digest=sha256:4dc3820ae10379cb4b8b2ec025be7f11356562e863e8add0fa343942f9ad7b46

Observation 5e13f927-1c64-4418-a0bd-da4134782729 · outbound

This paper cites High-Dimensional Continuous Control Using Generalized Advantage Estimation.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models High-Dimensional Continuous Control Using Generalized Advantage Estimation

Reference 2018

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source=pdf_text observed=2026-08-06T22:01:23.744845Z digest=sha256:975dfffb2ea71b83a619784a6110226a55477f75e515469ab0ca2484ea12e4ba

Observation 0226e5e9-c2e2-4ecc-b316-0636eeba918c · outbound

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

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models Multi-Bin Batching for Increasing LLM Inference Throughput

Reference 2024

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no resolver link, observed 2026-08-06T22:01:23.662435Z

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source=pdf_text observed=2026-08-06T22:01:23.662435Z digest=sha256:4c09592a8cd51c76f6b565ed1e5b22f6a5d6692638ae3d7f12afadf1a585406e

Observation 3b90de7b-6217-4c90-9730-19029bdad7de · outbound

This paper cites ELIS: Efficient LLM Iterative Scheduling System with Response Length Predictor.

Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models ELIS: Efficient LLM Iterative Scheduling System with Response Length Predictor

Reference 2025

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Pith citing papers

Observation 9cd97a3e-0019-4e55-a89f-21905f666d43 · inbound

F-TIS: Harnessing Diverse Models in Collaborative GRPO cites this paper.

F-TIS: Harnessing Diverse Models in Collaborative GRPO Infinite Sampling: Efficient and Stable Grouped RL Training for Large Language Models

Reference 14

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arxiv_id, observed 2026-05-22T07:41:14.382554Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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