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Paper Citation Record · LEDGER

Parallel Scaling Law for Language Models

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2505.10475.

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

pith.paper-citation-record.v1
2505.10475 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:36:33.339509Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T23:35:07.254827Z

Reference resolution

0 of 0 outbound references displayed

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  • verified fuzzy0
  • unresolved0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation d9ef287e-212b-4d88-9dd4-2e3db15b1761 · inbound

System Report for CCL25-Eval Task 10: SRAG-MAV for Fine-Grained Chinese Hate Speech Recognition cites this paper.

System Report for CCL25-Eval Task 10: SRAG-MAV for Fine-Grained Chinese Hate Speech Recognition Parallel Scaling Law for Language Models

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T14:36:33.339509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:36:33.339509Z digest=sha256:fbc8f833717c41ab8ee8a19580491b4537af6f90c3de52e3d08dc00ee4b3705e

Observation 86c53e88-b9b7-4736-9498-c8f3ad700b54 · inbound

Grove MoE: Towards Efficient and Superior MoE LLMs with Adjugate Experts cites this paper.

Grove MoE: Towards Efficient and Superior MoE LLMs with Adjugate Experts Parallel Scaling Law for Language Models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-05T21:55:07.259301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T21:55:07.259301Z digest=sha256:7707e97f15b1d92466470b5dc6dc58d2c066ec7334a7211ecda618d66c47605a

Observation a8464fe0-7b75-4f41-a026-6aa7729b5837 · inbound

ParaThinker: Native Parallel Thinking as a New Paradigm to Scale LLM Test-time Compute cites this paper.

ParaThinker: Native Parallel Thinking as a New Paradigm to Scale LLM Test-time Compute Parallel Scaling Law for Language Models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-05T13:52:03.639253Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T13:52:03.639253Z digest=sha256:94fbc338b549a4ca19e8b31f97b31e152adbaf2e1fec830fe42523ccc9d6839f

Observation f0a77883-5ce6-4769-bffc-67145f1265dc · inbound

Video Parallel Scaling: Aggregating Diverse Frame Subsets for VideoLLMs cites this paper.

Video Parallel Scaling: Aggregating Diverse Frame Subsets for VideoLLMs Parallel Scaling Law for Language Models

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-18T18:36:44.187053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-18T18:35:01.328250Z digest=sha256:0ddff04ea089bd92150b2bcf9b57aed4b9554aaf66e49f1e2b022680b0e26dbc

Observation 44c14fd2-3d28-4dee-ac4d-5e318028687c · inbound

Vec-LUT: Vector Table Lookup for Parallel Ultra-Low-Bit LLM Inference on Edge Devices cites this paper.

Vec-LUT: Vector Table Lookup for Parallel Ultra-Low-Bit LLM Inference on Edge Devices Parallel Scaling Law for Language Models

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-17T00:48:45.809804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-17T00:46:48.862313Z digest=sha256:a2dbc6f264b74754de67447afc0bf47d3168344b0b1bc705144535753969c8d2

Observation 0d7ac0bf-a7ba-4cc8-9980-3c0b2c23d10e · inbound

On the Overscaling Curse of Parallel Thinking: System Efficacy Contradicts Sample Efficiency cites this paper.

On the Overscaling Curse of Parallel Thinking: System Efficacy Contradicts Sample Efficiency Parallel Scaling Law for Language Models

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-16T10:40:51.377730Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-16T10:38:09.875786Z digest=sha256:4224f4434f7fd1181f9c20ace36594602239e0a241c8eee034693dea829f85fc

Observation 85ba890c-f556-41c4-83e5-7bdae37cad36 · inbound

Evaluation-driven Scaling for Scientific Discovery cites this paper.

Evaluation-driven Scaling for Scientific Discovery Parallel Scaling Law for Language Models

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-11T12:26:05.369634Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-10T03:39:52.204043Z digest=sha256:35eb9b5b3aa2c1697b182948fa3eb53530f770cb1a4ec8724c1af0738abb0bb1

Observation 8ba909a7-f7f4-430c-92de-a863fb278ea5 · inbound

Structured Recurrent Mixers for Massively Parallelized Sequence Generation cites this paper.

Structured Recurrent Mixers for Massively Parallelized Sequence Generation Parallel Scaling Law for Language Models

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:56:29.228324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-12T01:28:46.885635Z digest=sha256:4e2c03d287061f522ef76aa77975b1ba8ce34cd1d601183ebee331b31157c2d8

Observation 2daf2c9d-56a2-4a70-adae-eb820af0c9f5 · inbound

Structured Recurrent Mixers for Massively Parallelized Sequence Generation cites this paper.

Structured Recurrent Mixers for Massively Parallelized Sequence Generation Parallel Scaling Law for Language Models

Reference 47

Resolution
verified exact
arxiv_id, observed 2026-05-20T23:29:13.005444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-05-20T23:27:20.754475Z digest=sha256:1d853e5b6528e22356c411bd23f47816f955a99bdf9d55d19c523ce1756f7d40

Observation 7ce67c41-5046-43bd-bc66-016794d337a4 · inbound

Structured Recurrent Mixers for Massively Parallelized Sequence Generation cites this paper.

Structured Recurrent Mixers for Massively Parallelized Sequence Generation Parallel Scaling Law for Language Models

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-06-30T23:35:07.256259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=arxiv_source observed=2026-06-30T23:31:48.469869Z digest=sha256:d0c8e8f45645984726974a3cdcd313d30ddd0d60ac27f0cda405248b583c8bba

Observation f1b2d68f-55bd-40f8-83de-7aa5e11aa1be · inbound

Structured Recurrent Mixers for Massively Parallelized Sequence Generation cites this paper.

Structured Recurrent Mixers for Massively Parallelized Sequence Generation Parallel Scaling Law for Language Models

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-04T05:19:06.400737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T05:19:06.400737Z digest=sha256:7bbf7c39b04d932993fc454085c5a7a70b247712f039bf77b4848cf33d44453d

Observation ad31ccb7-640f-4f04-a05d-cd0f1c3c74cb · inbound

A Readiness-Driven Runtime for Pipeline-Parallel Training under Runtime Variability cites this paper.

A Readiness-Driven Runtime for Pipeline-Parallel Training under Runtime Variability Parallel Scaling Law for Language Models

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-20T07:38:09.462627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

source=pdf_text observed=2026-05-20T07:35:32.225708Z digest=sha256:1a65986b7fa015547ac00b9567bb004897f45d558371432153e6d3f0218403f7

Observation 67f495f4-0cb9-4803-8f3e-888f73ec96ef · inbound

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs cites this paper.

cMoLLM at Scale: Horizontal Scaling Laws for Mixture-of-LLMs Parallel Scaling Law for Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-02T12:12:35.629644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T12:12:35.629644Z digest=sha256:bdbd3800fc41d5906658844485cefb7a2eea9efd6518e339d3cca1748b896827