Paper Citation Record · LEDGER

Every Sample Matters: Leveraging Mixture-of-Experts and High-Quality Data for Efficient and Accurate Code LLM

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2503.17793.

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

pith.paper-citation-record.v1
2503.17793 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T12:56:35.040847Z

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

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

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

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation f4f61fa8-f3c9-47ad-bb2c-bffcfa3672b4 · inbound

Dream-Coder 7B: An Open Diffusion Language Model for Code cites this paper.

Dream-Coder 7B: An Open Diffusion Language Model for Code Every Sample Matters: Leveraging Mixture-of-Experts and High-Quality Data for Efficient and Accurate Code LLM

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-05T12:56:35.040847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84d50ffe-005a-44d1-9271-ab0a73a543e3 · inbound

Advancing Multimodal Judge Models through a Capability-Oriented Benchmark and MCTS-Driven Data Generation cites this paper.

Advancing Multimodal Judge Models through a Capability-Oriented Benchmark and MCTS-Driven Data Generation Every Sample Matters: Leveraging Mixture-of-Experts and High-Quality Data for Efficient and Accurate Code LLM

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-02T19:56:27.990155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9213a1f5-3f4f-423b-acea-69a2bb73ec41 · inbound

Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code cites this paper.

Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code Every Sample Matters: Leveraging Mixture-of-Experts and High-Quality Data for Efficient and Accurate Code LLM

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:26:04.703342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0f06bdca-9c44-4454-ad85-746b14832041 · inbound

Mellum2 Technical Report cites this paper.

Mellum2 Technical Report Every Sample Matters: Leveraging Mixture-of-Experts and High-Quality Data for Efficient and Accurate Code LLM

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-06-28T23:02:46.535912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 251ae597-c517-472a-9542-a0f003eb6bd0 · inbound

Attention Amnesia in Hybrid LLMs: When CoT Fine-Tuning Breaks Long-Range Recall, and How to Fix It cites this paper.

Attention Amnesia in Hybrid LLMs: When CoT Fine-Tuning Breaks Long-Range Recall, and How to Fix It Every Sample Matters: Leveraging Mixture-of-Experts and High-Quality Data for Efficient and Accurate Code LLM

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-06-27T13:10:55.933972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b5700c8a-e968-402c-9d3e-b082d264a273 · inbound

From Trainee to Trainer: LLM-Designed Training Environment for RL with Multi-Agent Reasoning cites this paper.

From Trainee to Trainer: LLM-Designed Training Environment for RL with Multi-Agent Reasoning Every Sample Matters: Leveraging Mixture-of-Experts and High-Quality Data for Efficient and Accurate Code LLM

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-06-27T01:00:19.853426Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.