Paper Citation Record · LEDGER

MinT: Managed Infrastructure for Training and Serving Millions of LLMs

As of 5 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 2 inbound Pith citation observations for arXiv:2605.13779.

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

pith.paper-citation-record.v1
2605.13779 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-30T21:47:00.295144Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T21:32:04.139639Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-01T22:16:16.701869Z

Reference resolution

36 of 36 outbound references displayed

verified exact19
verified fuzzy5
unresolved1
parse uncertain0
malformed identifier2
metadata mismatch9

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 6ea8c167-a213-4160-9fad-1778663c90e4 · outbound

This paper cites Anthropic.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Anthropic

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:03:57.997723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 07f10be1-22ce-4888-9fc8-dde4daa2ccfe · outbound

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

MinT: Managed Infrastructure for Training and Serving Millions of LLMs AsyncFlow: An Asynchronous Streaming RL Framework for Efficient LLM Post-Training

Reference 2

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T14:15:47.696815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 912df5af-97a5-4feb-833d-37a25a11c0c4 · outbound

This paper cites Punica: Multi-Tenant LoRA Serving.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Punica: Multi-Tenant LoRA Serving

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T14:15:47.694420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e8cb5f6c-b04d-487a-9016-6c8ca75cbd0a · outbound

This paper cites QLoRA: Efficient Finetuning of Quantized LLMs.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs QLoRA: Efficient Finetuning of Quantized LLMs

Reference 4

Resolution: metadata mismatch; local_arxiv, observed 2026-06-30T22:05:06.249776Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b427aebe-8038-408e-9ace-722d433a6351 · outbound

This paper cites LawBench: Benchmarking Legal Knowledge of Large Language Models.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:05:06.267674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6b5c9720-e68a-46cf-bc55-0d48936487e6 · outbound

This paper cites Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:05:06.232013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 35092af6-e19a-4ae8-ab4a-8e6c62d962d0 · outbound

This paper cites GLM-5: from Vibe Coding to Agentic Engineering.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs GLM-5: from Vibe Coding to Agentic Engineering

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-06-30T22:05:06.273336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 11b7da4f-097d-4665-8e6b-77ae0349ab19 · outbound

This paper cites FinEval: A Chinese Financial Domain Knowledge Evaluation Benchmark for Large Language Models.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs FinEval: A Chinese Financial Domain Knowledge Evaluation Benchmark for Large Language Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:05:06.270530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ae5a787b-f5f4-462f-b606-4219ed525b8e · outbound

This paper cites OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-06-30T22:05:06.258526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 064bf44d-3472-49f1-a73d-c0c9b7dc857c · outbound

This paper cites Serving heterogeneous LoRA adapters in distributed LLM inference systems.arXiv preprint arXiv:2511.22880.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Serving heterogeneous LoRA adapters in distributed LLM inference systems.arXiv preprint arXiv:2511.22880

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:05:06.261362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation eee9e76b-2881-4555-b1f6-e0ef53f5bb4a · outbound

This paper cites Kimi K2.5: Visual Agentic Intelligence.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Kimi K2.5: Visual Agentic Intelligence

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-06-30T22:05:06.264127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e3d5a71b-7ca2-4dfc-aa3c-28853f592df5 · outbound

This paper cites Every step evolves: Scaling reinforcement learning for trillion-scale thinking model.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Every step evolves: Scaling reinforcement learning for trillion-scale thinking model

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:05:06.255704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 86b7867d-79e2-4e16-a395-24e6f652fc68 · outbound

This paper cites Every step evolves: Scaling reinforcement learning for trillion-scale thinking model.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Every step evolves: Scaling reinforcement learning for trillion-scale thinking model

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T21:55:05.347389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5035dd83-694b-4543-83fb-7efadcc1363a · outbound

This paper cites FinGPT: Democratizing Internet-scale Data for Financial Large Language Models.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs FinGPT: Democratizing Internet-scale Data for Financial Large Language Models

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T22:05:06.276244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 89425270-de2f-4ebe-9752-889af9d40e47 · outbound

This paper cites Stabilizing MoE Reinforcement Learning by Aligning Training and Inference Routers.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Stabilizing MoE Reinforcement Learning by Aligning Training and Inference Routers

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-07-01T14:15:47.691891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation adccec86-6fd1-43c5-8647-c137d9b0f227 · outbound

This paper cites 2024 american invitational mathematics examination.https://maa.org/ maa-invitational-competitions/.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs 2024 american invitational mathematics examination.https://maa.org/ maa-invitational-competitions/

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:03:57.996044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ab92ec14-d6f1-437f-919e-e46dfa1f7bcd · outbound

This paper cites Mind Lab.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Mind Lab

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:03:57.994193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4c01e680-d671-42fb-be38-15eb63df5d37 · outbound

This paper cites Kimi K2: Open Agentic Intelligence.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Kimi K2: Open Agentic Intelligence

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-06-30T22:05:06.243648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6e36caa8-443b-4866-aae1-05fa647ea518 · outbound

This paper cites Kimi K2: Open Agentic Intelligence.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Kimi K2: Open Agentic Intelligence

Reference 19

Resolution: metadata mismatch; local_arxiv, observed 2026-06-30T21:55:05.344677Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 66d0774e-14e5-4333-ad20-0313dfe62708 · outbound

This paper cites Efficient Large-Scale Language Model Training on GPU Clusters Using Megatron-LM.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Efficient Large-Scale Language Model Training on GPU Clusters Using Megatron-LM

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:05:06.246888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation bde969c4-dc46-473a-96bb-3cd53382a600 · outbound

This paper cites an unresolved cited work.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-07-07T16:03:57.999413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 899154d4-fdd6-40d0-890c-1af55d0dc941 · outbound

This paper cites OpenTinker: Separating Concerns in Agentic Reinforcement Learning.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs OpenTinker: Separating Concerns in Agentic Reinforcement Learning

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-07T03:18:52.285192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d59a2065-e529-43f0-808f-6d836b9dec7f · outbound

This paper cites Qwen3 Technical Report.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Qwen3 Technical Report

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-06-30T22:05:06.204262Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d3883fcd-ce87-47c9-b7a6-66485aa578b8 · outbound

This paper cites Qwen3 Technical Report.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Qwen3 Technical Report

Reference 24

Resolution: metadata mismatch; local_arxiv, observed 2026-06-30T21:55:05.341578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ef7c15c7-bfd1-433b-9de2-97eb260cf5b7 · outbound

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

MinT: Managed Infrastructure for Training and Serving Millions of LLMs ZeRO: Memory Optimizations Toward Training Trillion Parameter Models

Reference 25

Resolution: metadata mismatch; local_arxiv, observed 2026-06-30T22:05:06.210018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 884a07e3-0ce2-459d-b434-52d7660279fd · outbound

This paper cites Relax: An Asynchronous Reinforcement Learning Engine for Omni-Modal Post-Training at Scale.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Relax: An Asynchronous Reinforcement Learning Engine for Omni-Modal Post-Training at Scale

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-06-30T22:05:06.192120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation aec0d447-6c0e-4166-ac67-953196d85ec7 · outbound

This paper cites Gerald Shen et al.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Gerald Shen et al

Reference 27

Resolution: malformed identifier; doi_truncated, observed 2026-06-30T21:55:05.336039Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c22c7b3c-63e5-4d52-9734-fe6227322ee1 · outbound

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

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Hybridflow: A flexible and efficient rlhf framework

Reference 28

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T21:55:05.338813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a34724d8-7443-4fa5-af4d-31c62aed044c · outbound

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

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

Reference 29

Resolution: verified exact; local_arxiv, observed 2026-06-30T22:05:06.195437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a02ac867-ad09-47fb-b21a-ffadada4b0ee · outbound

This paper cites AnnouncingTinker.https://thinkingmachines.ai/blog/announcing-tinker/, 2025a.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs AnnouncingTinker.https://thinkingmachines.ai/blog/announcing-tinker/, 2025a

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:03:58.003731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a06db02a-2946-46d3-8269-938b208dd82f · outbound

This paper cites Jet-RL: Enabling on-policy FP8 reinforcement learning with unified training and rollout precision flow.arXiv preprint arXiv:2601.14243.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Jet-RL: Enabling on-policy FP8 reinforcement learning with unified training and rollout precision flow.arXiv preprint arXiv:2601.14243

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:05:06.240717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a68be558-dbc6-4877-81bb-31b97a25a9d7 · outbound

This paper cites On the rollout-training mismatch in modern RL systems.NeurIPS 2025 Workshop on Efficient Reasoning.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs On the rollout-training mismatch in modern RL systems.NeurIPS 2025 Workshop on Efficient Reasoning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-07-07T16:03:58.001089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 203ac591-74c3-4105-9bf2-2a83e0b4db5f · outbound

This paper cites mLoRA: Fine-Tuning LoRA Adapters via Highly-Efficient Pipeline Parallelism in Multiple GPUs.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs mLoRA: Fine-Tuning LoRA Adapters via Highly-Efficient Pipeline Parallelism in Multiple GPUs

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:05:06.237423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9980b588-d301-4673-af44-6c390837a1b1 · outbound

This paper cites Improving the Serving Performance of Multi-LoRA Large Language Models via Efficient LoRA and KV Cache Management.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs Improving the Serving Performance of Multi-LoRA Large Language Models via Efficient LoRA and KV Cache Management

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-06-30T22:05:06.252808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 63484d9a-1eed-4b75-9259-2a443a169d6b · outbound

This paper cites AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-06-30T22:05:06.230947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 26889423-25af-4e2b-b9cd-61018848f47d · outbound

This paper cites The unique- adapter rows remove this locality and measure how many distinct adapters can become cached near one engine before the run stops being a clean warm-path claim.

MinT: Managed Infrastructure for Training and Serving Millions of LLMs The unique- adapter rows remove this locality and measure how many distinct adapters can become cached near one engine before the run stops being a clean warm-path claim

Reference 36

Resolution: malformed identifier; raw_fallback, observed 2026-07-07T16:03:58.005679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Pith citing papers

Observation b1adeb83-441b-4d3d-ae08-cab81d099f99 · inbound

On the Scaling of PEFT: Towards Million Personal Models of Trillion Parameters cites this paper.

On the Scaling of PEFT: Towards Million Personal Models of Trillion Parameters MinT: Managed Infrastructure for Training and Serving Millions of LLMs

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-07-01T22:16:16.703022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 72af155f-da62-4b38-a210-c83e387af58d · inbound

JoyNexus: Service-Oriented Multi-Tenant Post-Training for VLA Models cites this paper.

JoyNexus: Service-Oriented Multi-Tenant Post-Training for VLA Models MinT: Managed Infrastructure for Training and Serving Millions of LLMs

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T21:32:04.139639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.