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Paper Citation Record · LEDGER

Megrez2 Technical Report

As of 17 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 2 inbound Pith citation observations for arXiv:2507.17728.

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

pith.paper-citation-record.v1
2507.17728 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:22:31.573595Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T07:31:30.002413Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T07:43:11.730902Z

Reference resolution

30 of 30 outbound references displayed

  • verified exact0
  • verified fuzzy9
  • unresolved21
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7408cc4d-dd1a-4f3e-b390-6d6a56c17984 · outbound

This paper cites Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs.

Megrez2 Technical Report Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAs

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.423242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.423242Z digest=sha256:34d84f90801fc77d4f790e4bf5d63d0cef0cc6c4ce74efb19e58a65d2f52affb

Observation b24c8a24-0c9a-49a1-907f-8ca01019e7ed · outbound

This paper cites GPT-4 Technical Report.

Megrez2 Technical Report GPT-4 Technical Report

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.429139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.429139Z digest=sha256:76021db065c67759c956ccc6fbcbbe704a8affe98a41cfad5f4f845d71fbfd15

Observation c18bebae-ee4b-4059-8dd5-6ceabad935ef · outbound

This paper cites https://github.com/MoonshotAI/Kimi-K2.

Megrez2 Technical Report https://github.com/MoonshotAI/Kimi-K2

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:32.129952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T18:22:31.433760Z digest=sha256:459003b992cffce40de3c19bc8aa0693523b51fd682d92e125697c2a9bb70eed

Observation a6aabc3e-5c8f-4be6-b691-6b9ef877773a · outbound

This paper cites Program Synthesis with Large Language Models.

Megrez2 Technical Report Program Synthesis with Large Language Models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.439223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.439223Z digest=sha256:74156899df0fbe72d54d17458907a269ffffb186f84114ccb7c4941947feae2a

Observation 5a04d115-6d1a-4161-b026-49befda38162 · outbound

This paper cites Read-ME: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design.

Megrez2 Technical Report Read-ME: Refactorizing LLMs as Router-Decoupled Mixture of Experts with System Co-Design

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:32.114717Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T18:22:31.444259Z digest=sha256:10a99df431dad2bd93cc3d1b6ffd1db0befd889cd259152d0679f0398fe51766

Observation 89f26a69-0768-4100-9501-a3cf1553bea4 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Megrez2 Technical Report Evaluating Large Language Models Trained on Code

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.448585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.448585Z digest=sha256:af100a2a953cf8de33e0ade70ef47069ffdf55f24a71057837fef369c3f661f0

Observation ee2a01a2-7b50-4815-8f52-a9b4fc306acb · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Megrez2 Technical Report Training Verifiers to Solve Math Word Problems

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.453786Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.453786Z digest=sha256:c494286b9f1e224a5141602b97e0b5896000c30f52d6d36d50b319b2ff3b7abb

Observation e88677d7-12a3-459c-88f7-bd0812465610 · outbound

This paper cites DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models.

Megrez2 Technical Report DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.458015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.458015Z digest=sha256:232bbe2e2d8b1f5d1e3e16c71df2b48b3671b6140360abaaa89dd1e6a8bfa63e

Observation bda07f25-80c4-4669-9b8e-bc1e5e3ed92b · outbound

This paper cites Fast Inference of Mixture-of-Experts Language Models with Offloading.

Megrez2 Technical Report Fast Inference of Mixture-of-Experts Language Models with Offloading

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.462458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.462458Z digest=sha256:8991741aed16401e806018e061475e082a79bc9e00308caaff5c7b0fc9e273d6

Observation 2cebd7bb-92c4-4e2e-9c69-7bb59dd7489d · outbound

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

Megrez2 Technical Report DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.466907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.466907Z digest=sha256:e3675461602d2de8d41f5b08f813c1a60c2553d8cdec85656577409abf73c594

Observation 88f33b04-ed93-4b17-a853-c7e168c88766 · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

Megrez2 Technical Report Measuring Mathematical Problem Solving With the MATH Dataset

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.471074Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.471074Z digest=sha256:1e0ee70f0e400b85a7a4f84826163b510ff059309f6acd2e9c90ba00a34e16a0

Observation e0d5a180-a44d-4c07-8ebd-2ee400ca10bd · outbound

This paper cites C-eval: A multi-level multi-discipline chinese evaluation suite for foundation models.

Megrez2 Technical Report C-eval: A multi-level multi-discipline chinese evaluation suite for foundation models

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:32.098712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T18:22:31.476293Z digest=sha256:0f3dac116df510eac9663ce7ce1c14cc1abcafd83b96f5ebf0a1a719f848956c

Observation ae1f1fdb-6c18-4bdc-9e89-27077b32701a · outbound

This paper cites Pre-gated moe: An algorithm-system co-design for fast and scalable mixture-of-expert inference.

Megrez2 Technical Report Pre-gated moe: An algorithm-system co-design for fast and scalable mixture-of-expert inference

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:32.080637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T18:22:31.483727Z digest=sha256:ca4cc1a0bb104af5a510568acdba8cf76163384e00f25867bad48af849d7a73a

Observation 1a48f460-0aec-47f7-b8ab-f84b9ef3929f · outbound

This paper cites Gemma 3 Technical Report.

Megrez2 Technical Report Gemma 3 Technical Report

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.489869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.489869Z digest=sha256:5a8cb20bc9ff653bfd18b7210c65721e0f6b977623db78cd85285560d6447053

Observation 61cf7f48-7b74-4b88-b97c-389fd402cc26 · outbound

This paper cites Megrez-Omni Technical Report.

Megrez2 Technical Report Megrez-Omni Technical Report

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.495411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.495411Z digest=sha256:f012b99f2a815704607522a97e2d50b59f841ec59d7722d5732559594fffcd25

Observation 607186a0-6097-44fd-aa0d-8d349315e6d4 · outbound

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

Megrez2 Technical Report DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.500853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.500853Z digest=sha256:3c5bd23db6eb142a75256694cfc5b24d3a0e2fb62f865a8328d2de7ab0f5f6ce

Observation d261e4ae-c571-471f-9d59-1acb1440e4a6 · outbound

This paper cites https://ai.

Megrez2 Technical Report https://ai

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:32.062735Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T18:22:31.506223Z digest=sha256:37967e6c3dd6cbbc6ea6fb9149602ada8831de6d1d71d5c67ee2dd4c7c3e0398

Observation aa1a5e49-3bb0-42d2-8705-1de0005d8fca · outbound

This paper cites OpenAI blog post.

Megrez2 Technical Report OpenAI blog post

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:32.047015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T18:22:31.511618Z digest=sha256:8c9f6a611d77e4f0a4c05600f4f1904122bb954b0c5d6a0ef22a505e8a2a07de

Observation 4488eef3-f5e7-4545-97b3-215ca830edb3 · outbound

This paper cites 2025.URL: https://openai.com/index/introducing-o3- and-o4-mini/.

Megrez2 Technical Report 2025.URL: https://openai.com/index/introducing-o3- and-o4-mini/

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:32.031128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T18:22:31.517751Z digest=sha256:86b7438e91b171d4b5668ad2ea754d58bc62365f557db2eefb45dbb839f26010

Observation f35391cf-7bfe-43bf-a253-bf9f8bbb173f · outbound

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

Megrez2 Technical Report High-Dimensional Continuous Control Using Generalized Advantage Estimation

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.523116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.523116Z digest=sha256:4b49cb98be08858b7c6bc0697da05ee92b55cd2c5c0a5a8b72008d8201fd1287

Observation de308f28-18c9-4fb6-8c1f-053ba5cbd31a · outbound

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

Megrez2 Technical Report DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.528917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.528917Z digest=sha256:4a4ca122d52d69db4bbe8c7b1d82bb38c4aa6a1c26358dc753977c32728fec55

Observation ca65bfeb-c9ee-44ad-a050-c73e7e285444 · outbound

This paper cites Roformer: Enhanced trans- former with rotary position embedding.

Megrez2 Technical Report Roformer: Enhanced trans- former with rotary position embedding

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:32.015811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T18:22:31.534150Z digest=sha256:25026c213c1b78c2bcb5e52f18bae31d623f8a0cd0ece691e571e700e7541fb2

Observation ec23250f-0d0f-4bb3-912b-6e14fbf2daae · outbound

This paper cites Dai, Anja Hauth, Katie Millican, et al.Gemini: A Family of Highly Capable Multimodal Models.

Megrez2 Technical Report Dai, Anja Hauth, Katie Millican, et al.Gemini: A Family of Highly Capable Multimodal Models

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:22:31.996187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T18:22:31.538958Z digest=sha256:962d0b3116ac69cd734ec2795ebacf8031d00c749ebf8c0df23851ba459591d5

Observation 5d0f71e9-6386-4161-b27c-bf74e4006ed6 · outbound

This paper cites Auxiliary-Loss-Free Load Balancing Strategy for Mixture-of-Experts.

Megrez2 Technical Report Auxiliary-Loss-Free Load Balancing Strategy for Mixture-of-Experts

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.548915Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.548915Z digest=sha256:250e474a878f7793026fb3f2c1bd9d4f4cbf9a53cf231e8581e6648b84978617

Observation 7aa166cd-942a-413e-97d1-7b772eefca7c · outbound

This paper cites MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark.

Megrez2 Technical Report MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.553751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.553751Z digest=sha256:c9e72921a9124c78086b52203451f6050df8a17c690d060e28518ae9cfc70938

Observation d4d98c11-b027-47a4-9f96-0e925258a363 · outbound

This paper cites Skywork-MoE: A Deep Dive into Training Techniques for Mixture-of-Experts Language Models.

Megrez2 Technical Report Skywork-MoE: A Deep Dive into Training Techniques for Mixture-of-Experts Language Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.558747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.558747Z digest=sha256:ccb1c6b929c6f549bc6985ad04fbf2c6b5b1f8f7c073836ad81abe7b3a3c54fc

Observation 5b44c9ab-69f7-4b8c-bf3a-d6efd81fb4b7 · outbound

This paper cites Qwen3 Technical Report.

Megrez2 Technical Report Qwen3 Technical Report

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.563892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.563892Z digest=sha256:873ea8b14fcb1c3ffdef7d07c7a076e23ecb220a8f37b8cbba7e157be1a0c384

Observation b79c4425-af2a-4cf3-adf0-0a47d0a5bc1f · outbound

This paper cites Qwen2.5 Technical Report.

Megrez2 Technical Report Qwen2.5 Technical Report

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.568825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.568825Z digest=sha256:d7fdf1bf771a4698df3bdaba8250bb473f3e8cb5caadae158a416994bc05418b

Observation 53b9c0dd-613e-4c51-9e7c-d8f74f8c8806 · outbound

This paper cites Instruction-Following Evaluation for Large Language Models.

Megrez2 Technical Report Instruction-Following Evaluation for Large Language Models

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.573595Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.573595Z digest=sha256:e405c64e271d5066aa9213ae080a98905e08c5546815bbf4e67aced1086b54c1

Observation 2aae55a4-2ece-49fa-86a2-ce8e4f371296 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Megrez2 Technical Report Gemini: A Family of Highly Capable Multimodal Models

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-15T18:22:31.543753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:22:31.543753Z digest=sha256:03a88d4977a15cd5863682f94a0d9f99f7f96f3696cf76b0919d908246d3083f

Pith citing papers

Observation d2458f03-1b65-42e4-b243-d34a5dbec593 · inbound

Scaling Latent Reasoning via Looped Language Models cites this paper.

Scaling Latent Reasoning via Looped Language Models Megrez2 Technical Report

Reference 26

Resolution
verified exact
arxiv_id, observed 2026-05-15T07:43:11.733057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-05-15T07:43:11.620446Z digest=sha256:b278cdf72a33aa2585bb2cb269b269f73840c14662b60d8bf512a4c24cc34341

Observation 664b41ab-d79e-41f6-b34f-f8b47399cc55 · inbound

Scaling Latent Reasoning via Looped Language Models cites this paper.

Scaling Latent Reasoning via Looped Language Models Megrez2 Technical Report

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-04T07:31:30.002413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T07:31:30.002413Z digest=sha256:043bf85a57d66e8a9cf044dfbef755e4e2bee783c926c4745418c416f4b7c312