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Paper Citation Record · LEDGER

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training

As of 10 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 7 inbound Pith citation observations for arXiv:2507.17634.

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

pith.paper-citation-record.v1
2507.17634 v2

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T14:49:40.374840Z

measured 77 of 77 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T08:04:06.432613Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T16:48:39.719025Z

Reference resolution

70 of 70 outbound references displayed

  • verified exact1
  • verified fuzzy24
  • unresolved43
  • parse uncertain0
  • malformed identifier2
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b40b8c51-98bd-4592-9a8a-ea78cbd8178f · outbound

This paper cites write newline.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training write newline

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.161054Z digest=sha256:e0e6e106572d47cef289cd8425cec51e6205db7caf9bcf90c74cdc7e39ab1c6c

Observation e5c0682f-0a66-4e98-9e9f-94ecc31f50b9 · outbound

This paper cites Command A: An Enterprise-Ready Large Language Model.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Command A: An Enterprise-Ready Large Language Model

Reference 2

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no resolver link, observed 2026-08-06T14:49:40.164771Z

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source=arxiv_source observed=2026-08-06T14:49:40.164771Z digest=sha256:ef329492e78c2e7dbbb53d3ba7c5b6709775701abfb47b5ecbc8cf19f9561b29

Observation af7cc77a-cbd0-4bf7-8520-8567d0c59a48 · outbound

This paper cites GQA: training generalized multi-query transformer models from multi-head checkpoints.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training GQA: training generalized multi-query transformer models from multi-head checkpoints

Reference 3

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no resolver link, observed 2026-08-06T14:49:40.168634Z

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source=arxiv_source observed=2026-08-06T14:49:40.168634Z digest=sha256:a3645b2f2d50f03b4487c2e59059d7ce6976cad497c8ea6737749a6e06dc631f

Observation 7653a452-a6eb-4708-9b21-6b8f59e459ad · outbound

This paper cites Singular value decomposition for genome-wide expression data processing and modeling.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Singular value decomposition for genome-wide expression data processing and modeling

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.951863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.171452Z digest=sha256:1ac00e11d20453dfd66ecfdf6c33a09874ca4851d604b9b91038dbac502befc3

Observation bf4ac10f-53f1-4cd0-96a7-47579c692fe4 · outbound

This paper cites Efficient Training of Language Models to Fill in the Middle.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Efficient Training of Language Models to Fill in the Middle

Reference 5

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source=arxiv_source observed=2026-08-06T14:49:40.174037Z digest=sha256:20aa95d80ec5ee9868fa9e900d053fc00754d78e26ed3fc09b5ac033474eed65

Observation 1d0af229-8979-4c47-833e-111f69af968c · outbound

This paper cites Think you have Solved Direct-Answer Question Answering? Try ARC-DA, the Direct-Answer AI2 Reasoning Challenge.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Think you have Solved Direct-Answer Question Answering? Try ARC-DA, the Direct-Answer AI2 Reasoning Challenge

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.177307Z digest=sha256:37313d4a7502c57d2282520e66626358f0faddf13f5d4964bcccf315a5b0c207

Observation 4c452095-68dd-4574-9f1b-931eb1cd1d41 · outbound

This paper cites PIQA: reasoning about physical commonsense in natural language.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training PIQA: reasoning about physical commonsense in natural language

Reference 7

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no resolver link, observed 2026-08-06T14:49:40.180214Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.180214Z digest=sha256:0bc871e7e63784b7daa353c964def08bd3d54ae04c64a3f5d7bbe8a5e3f0c55e

Observation 44ed7f98-a06d-4b5e-bf2e-b71b4ef485e4 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Evaluating Large Language Models Trained on Code

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.183110Z digest=sha256:a45577142425771cdab6c57f9a8ece0688687d75f864ad9175effd8eca2a251b

Observation 48ff99f4-5945-4f0f-93bd-03462c4a5d28 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Training Verifiers to Solve Math Word Problems

Reference 9

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source=arxiv_source observed=2026-08-06T14:49:40.186163Z digest=sha256:af8a74762ecc62f84b2d1f6b280a4facb5da243cd8bb7a28a8ca08d969180b9b

Observation 1ddb38eb-9df7-4a41-b576-9e4050683a22 · outbound

This paper cites DeepSeek-V3 Technical Report.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training DeepSeek-V3 Technical Report

Reference 10

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source=arxiv_source observed=2026-08-06T14:49:40.189875Z digest=sha256:2f39bd9a839d906961ec73bd925707d846b980143c9f077072207dce8457f61c

Observation 9f23933e-377f-4d5a-812e-ac93845b4613 · outbound

This paper cites Optimal Linear Decay Learning Rate Schedules and Further Refinements.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Optimal Linear Decay Learning Rate Schedules and Further Refinements

Reference 11

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source=arxiv_source observed=2026-08-06T14:49:40.192955Z digest=sha256:94f50a26ac1343d81faa825b04b1a82ac319a23dd41a3c4c28146db48d26adf2

Observation 203545ba-b5b0-4689-8d7b-921ea7f367f0 · outbound

This paper cites The road less scheduled.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training The road less scheduled

Reference 12

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raw_fallback, observed 2026-08-06T14:49:40.944051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.195837Z digest=sha256:e4eab63eda0ca249d62e15658abcf52beac80393a7a9a3b585b85b45dba4dcc8

Observation 86616692-7305-4c4c-a24b-b033ff50d23a · outbound

This paper cites Ernie 4.5 technical report, 2025.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Ernie 4.5 technical report, 2025

Reference 13

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raw_fallback, observed 2026-08-06T14:49:40.936385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.198545Z digest=sha256:21a821b67c3320d05c82f8760c41fd681491c4f49487f5e04c7e8e5cbfe0dc8a

Observation eb8d68e8-e2b1-440e-8eb8-c05cad23f7a8 · outbound

This paper cites A closer look at deep learning heuristics: Learning rate restarts, warmup and distillation.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training A closer look at deep learning heuristics: Learning rate restarts, warmup and distillation

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.929541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.201212Z digest=sha256:50f789e94859c7719436b8ef37e828d901f604e9d204a306bcaf6200499f56ae

Observation 4a9488bd-2143-49cf-83f2-7c3034dbff2c · outbound

This paper cites The Llama 3 Herd of Models.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training The Llama 3 Herd of Models

Reference 15

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source=arxiv_source observed=2026-08-06T14:49:40.203886Z digest=sha256:f1766d72669e0ebe70f24b80686e13d7f1c643a0de2600a31b59cbc8dfe7c916

Observation 8e031a19-d770-4c7a-bbdc-97905fb8be40 · outbound

This paper cites Cruxeval: A benchmark for code reasoning, understanding and execution.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Cruxeval: A benchmark for code reasoning, understanding and execution

Reference 16

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verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.921888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.206838Z digest=sha256:f9aa67dc2f25bb55d0c26bfc66d6efb99fcaba09ff65282cfb1094275ccd4a1f

Observation 767a9476-fe71-4897-b757-2b355ffabbef · outbound

This paper cites Measuring massive multitask language understanding.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Measuring massive multitask language understanding

Reference 17

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raw_fallback, observed 2026-08-06T14:49:40.914354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.209532Z digest=sha256:826d5bce6ad618c837a5c72a8690132339e522d1bd81031fc61e7a23ebc94ff1

Observation 600bdd67-00bd-445c-8465-8d0366ce6c02 · outbound

This paper cites Measuring mathematical problem solving with the MATH dataset.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Measuring mathematical problem solving with the MATH dataset

Reference 18

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raw_fallback, observed 2026-08-06T14:49:40.906979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.212327Z digest=sha256:1e503a1cfc1569e554b732c1608b81b3d868b99d1086d4998828cfa39659e2f4

Observation dd226e5d-e9d6-4aec-9d45-36a5b290fe05 · outbound

This paper cites Training Compute-Optimal Large Language Models.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Training Compute-Optimal Large Language Models

Reference 19

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no resolver link, observed 2026-08-06T14:49:40.215478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.215478Z digest=sha256:dcc9d22be233217c79c904a5cddce602d63e034dd31c6aa4a89988e414c4d825

Observation 316f645f-0a47-4f65-80f9-6fdbbba51394 · outbound

This paper cites WorldSense: Evaluating Real-world Omnimodal Understanding for Multimodal LLMs.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training WorldSense: Evaluating Real-world Omnimodal Understanding for Multimodal LLMs

Reference 20

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no resolver link, observed 2026-08-06T14:49:40.219276Z

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source=arxiv_source observed=2026-08-06T14:49:40.219276Z digest=sha256:e8f117b1fd839294c0da2ad0dbf82ee850d2e0d457e9f1582319f3c56383f02e

Observation 5e736d96-9b1f-406d-b8ca-ef0cc1f07da7 · outbound

This paper cites MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Reference 21

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source=arxiv_source observed=2026-08-06T14:49:40.223058Z digest=sha256:2105f9b9dafd2cbc3a8a72fd17ab415caa7cc9fb37233bc367124c1c0f3ba2a9

Observation a8ee7ec0-676a-472c-852a-bd82e31f2d90 · outbound

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

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training C-eval: A multi-level multi-discipline chinese evaluation suite for foundation models

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.899199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.226927Z digest=sha256:a7b0154bfa99782946b32df23db4f8bd3c5ebd779ec3492b7c489b0ddcd7e658

Observation e78238f1-43f9-48f5-929f-c3c107944b12 · outbound

This paper cites Richter, Quentin Gregory Anthony, Eugene Belilovsky, Timoth \' e e Lesort, and Irina Rish.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Richter, Quentin Gregory Anthony, Eugene Belilovsky, Timoth \' e e Lesort, and Irina Rish

Reference 23

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raw_fallback, observed 2026-08-06T14:49:40.891363Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.229513Z digest=sha256:d9ac2919b761b256c1811259bb6a9ee37492ae906924ba2e9b583324e084cb36

Observation 26fc44d2-0d2a-4f90-96d8-e09ce6d05f58 · outbound

This paper cites Vetrov, and Andrew Gordon Wilson.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Vetrov, and Andrew Gordon Wilson

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.883249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.232083Z digest=sha256:3af7a84243bbfe625072b18040643950f5a8e8249048e8d0eec01537a559730f

Observation 97bc146a-f747-4825-ad5a-187d111e6a86 · outbound

This paper cites Livecodebench: Holistic and contamination free evaluation of large language models for code.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Livecodebench: Holistic and contamination free evaluation of large language models for code

Reference 25

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source=arxiv_source observed=2026-08-06T14:49:40.235282Z digest=sha256:e6213a89e183381504b3c8e5d92c564add1edcc6cde79a6c48f567818bfca00c

Observation 3c8a01b1-70b3-4eab-9769-b3b40af967c0 · outbound

This paper cites Rethinking learning rate tuning in the era of large language models.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Rethinking learning rate tuning in the era of large language models

Reference 26

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verified exact
raw_fallback, observed 2026-08-06T14:49:40.718320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.237678Z digest=sha256:68da6059bd956648d31c97ab9ae10b0bcd55aeae949537b40c25ddef886c22f2

Observation fe181627-fec2-42d5-a385-46f2f81ed036 · outbound

This paper cites Weld, and Luke Zettlemoyer.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Weld, and Luke Zettlemoyer

Reference 27

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source=arxiv_source observed=2026-08-06T14:49:40.241618Z digest=sha256:8fee1f0748b847e1c8502e40309b3cafae2f436378e13c9b2bc088eba12d14e2

Observation 3c208857-404e-4fda-86fe-b1e9232e2a17 · outbound

This paper cites Stop Wasting My Time! Saving Days of ImageNet and BERT Training with Latest Weight Averaging.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Stop Wasting My Time! Saving Days of ImageNet and BERT Training with Latest Weight Averaging

Reference 28

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no resolver link, observed 2026-08-06T14:49:40.244546Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.244546Z digest=sha256:56349b16f127d4e6dc1ae0f1743fa50ccfd2495287979ce137b1f85573e4e7ef

Observation e6f4d678-8373-4e81-9269-194552a071d2 · outbound

This paper cites Scaling Laws for Neural Language Models.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Scaling Laws for Neural Language Models

Reference 29

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no resolver link, observed 2026-08-06T14:49:40.247566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.247566Z digest=sha256:6085d18827ddd5036d4b78aa532f5da01c19841afed0557e9da0b1f2b65ac963

Observation 0986341d-8cb4-4960-a89a-78a9fe9f17a7 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Adam: A Method for Stochastic Optimization

Reference 30

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no resolver link, observed 2026-08-06T14:49:40.250757Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.250757Z digest=sha256:ccf15b16f6382f27fefb07ed515d364ecbfa7f112ae00ea33464c03ffe8dc70a

Observation b6b156b9-734c-46c3-bc7d-79d25f64b4f4 · outbound

This paper cites Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming - Wei Chang, Andrew M.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming - Wei Chang, Andrew M

Reference 31

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-06T14:49:40.255037Z digest=sha256:30c06b50eaf9f50fb19db49c9945070b8433771775f52b211578d2874c015cae

Observation c2d43276-78d1-4e4d-80d5-111c6b495cec · outbound

This paper cites an unresolved cited work.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Unresolved cited work

Reference 32

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no resolver link, observed 2026-08-06T14:49:40.258558Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.258558Z digest=sha256:ef268240bc89a3bcbc566f1a676314a30228777e5b30922bb91bc44daf848b50

Observation 92810c51-2ae3-4353-a885-12bdda675a2d · outbound

This paper cites CMMLU: measuring massive multitask language understanding in chinese.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training CMMLU: measuring massive multitask language understanding in chinese

Reference 33

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no resolver link, observed 2026-08-06T14:49:40.261471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.261471Z digest=sha256:557b4cac5bf4cfb8918e420604298bd62a63d4c549e56c7bec58b36e1cdbfb1e

Observation 80457c3f-2016-4f98-a019-eb28e5a8d60f · outbound

This paper cites Gsm-plus: A comprehensive benchmark for evaluating the robustness of llms as mathematical problem solvers.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Gsm-plus: A comprehensive benchmark for evaluating the robustness of llms as mathematical problem solvers

Reference 34

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no resolver link, observed 2026-08-06T14:49:40.264278Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.264278Z digest=sha256:7e8a2e43d8c38eee9b282ebde488a0426182fef12e88d84e00c448b40c9f834a

Observation ff6b0366-0353-4801-b059-198f28d01ab6 · outbound

This paper cites Trainable weight averaging: Efficient training by optimizing historical solutions.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Trainable weight averaging: Efficient training by optimizing historical solutions

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.871354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.267452Z digest=sha256:ec33025e7d2cea525ffea2078ba53acc1727c26793f4aefe60e2721b76ff8aac

Observation b01d7e69-effd-4359-869c-aaa6507bee03 · outbound

This paper cites Model Merging in Pre-training of Large Language Models.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Model Merging in Pre-training of Large Language Models

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.270904Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.270904Z digest=sha256:a37323a866cd13455b4422d6166bb9afc756724f2f70ad2fb02317c1862c7fb3

Observation 7393a6f6-d761-4dd3-a0c7-e5030d5fad5a · outbound

This paper cites Every FLOP Counts: Scaling a 300B Mixture-of-Experts LING LLM without Premium GPUs.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Every FLOP Counts: Scaling a 300B Mixture-of-Experts LING LLM without Premium GPUs

Reference 37

Resolution
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no resolver link, observed 2026-08-06T14:49:40.275301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.275301Z digest=sha256:afb74765dd364d576c0541d6c975aaece539689d41f7c2d9ce8eb0e6f1430c41

Observation 04763bb9-e42d-4b7d-98ae-5d4af2c4573e · outbound

This paper cites Checkpoint Merging via Bayesian Optimization in LLM Pretraining.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Checkpoint Merging via Bayesian Optimization in LLM Pretraining

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.278771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.278771Z digest=sha256:e013653009a1aba8fbd7f9509a7ad81313f322a0de3e349d53bf76d2b860e458

Observation fdd15129-6fde-4231-b630-e247e463f365 · outbound

This paper cites Mathbench: Evaluating the theory and application proficiency of llms with a hierarchical mathematics benchmark.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Mathbench: Evaluating the theory and application proficiency of llms with a hierarchical mathematics benchmark

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.282544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.282544Z digest=sha256:6dc2d5c9b43d3b48a7a3f47434fa193c70218d650cfdd13e5b31b16dc716984b

Observation 6aaa4fbe-0b1f-4f4d-bdd9-5eb9434c5cd2 · outbound

This paper cites Is your code generated by chatgpt really correct? rigorous evaluation of large language models for code generation.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Is your code generated by chatgpt really correct? rigorous evaluation of large language models for code generation

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.859947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.285010Z digest=sha256:c42960b832ff414b77e7d221e5761537ff6d3dd6678148264a9cd908e7bfd82b

Observation 00bf9dac-1894-4206-ae92-115eddcfa730 · outbound

This paper cites Muon is Scalable for LLM Training.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Muon is Scalable for LLM Training

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.287585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.287585Z digest=sha256:9e1e53855d0ebdde51963463b887c40ba9b05315f0869c488702fb6448b07d7f

Observation 49a61f1f-3ff0-4842-8d7e-6258c9900bd3 · outbound

This paper cites Decoupled weight decay regularization.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Decoupled weight decay regularization

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.852087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.290756Z digest=sha256:ae4dabb0011994b60857ecf75633719e1833263b3798fa6fc9713786b4b717e5

Observation ad685db0-d7e0-46b9-8969-896301d0f5ea · outbound

This paper cites Kor-bench: Benchmarking language models on knowledge-orthogonal reasoning tasks.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Kor-bench: Benchmarking language models on knowledge-orthogonal reasoning tasks

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.844328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.293880Z digest=sha256:e4790b66b5ea220708d8e00789a6d09e213bbd5aef7b7e577efb62ea06bc8fef

Observation 80ef4eb8-0795-49b4-9394-ebe5812f7620 · outbound

This paper cites Can a suit of armor conduct electricity? A new dataset for open book question answering.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Can a suit of armor conduct electricity? A new dataset for open book question answering

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.296436Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.296436Z digest=sha256:a735e67c22076cfa39eabf39fce7069b44244740a3c2193dae0eaa7182fd58e4

Observation fd8ca48f-a9e5-4982-bb70-25a8150f586e · outbound

This paper cites Humaneval-xl: A multilingual code generation benchmark for cross-lingual natural language generalization.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Humaneval-xl: A multilingual code generation benchmark for cross-lingual natural language generalization

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.836404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.298941Z digest=sha256:6bf4e4e55b5407fbd32f706a393dc3d94a2d41e59294798c053f8bde8f51a767

Observation d441faa6-5beb-4307-b58b-e070c24e151c · outbound

This paper cites Acceleration of stochastic approximation by averaging.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Acceleration of stochastic approximation by averaging

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.302393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.302393Z digest=sha256:f924555f328dab8dd71f086f14abdebd2a75515ecb90894a4b02c5cd4e556752

Observation 6b2617c9-22da-4f45-a52e-e38e97ebe2cf · outbound

This paper cites Know what you don't know: Unanswerable questions for squad.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Know what you don't know: Unanswerable questions for squad

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.305913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.305913Z digest=sha256:b43a8c599725a1e64378293d6b9502d52dcbf9bd0be08035e0f136eb7d5d5220

Observation f45b4229-3401-43fd-821a-02d59d43cf5c · outbound

This paper cites WARP: On the Benefits of Weight Averaged Rewarded Policies.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training WARP: On the Benefits of Weight Averaged Rewarded Policies

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.309508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.309508Z digest=sha256:b4aed6856005554c012828676587007bf0a0d5e6bd7174807cc8cf2fe1e17284

Observation c88fe0e4-73e4-4e04-aed1-ba08bb7f98bd · outbound

This paper cites GPQA: A Graduate-Level Google-Proof Q&A Benchmark.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training GPQA: A Graduate-Level Google-Proof Q&A Benchmark

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.313269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.313269Z digest=sha256:c85cee6ef8345d452366bf585b7620838060d0c32f2272cccb5669fb84905e1d

Observation 8e4937d0-9314-4a55-84ac-e2315a2e4758 · outbound

This paper cites The effective rank: A measure of effective dimensionality.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training The effective rank: A measure of effective dimensionality

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.823812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.317041Z digest=sha256:828542322e3037f75d209ff75acdb6152a1ca2c1333a4b73641227b9b63b7b0d

Observation 55aeede7-6672-4f15-a676-ca48906940a7 · outbound

This paper cites Winogrande: an adversarial winograd schema challenge at scale.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Winogrande: an adversarial winograd schema challenge at scale

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.319980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.319980Z digest=sha256:a51bdd0aecd8d601c5e1658d675806a2c81fc04e6326e89d6407a8f4f5775f3c

Observation 9f1d570c-bd0e-43dd-801f-db8643107920 · outbound

This paper cites Training trajectories, mini-batch losses and the curious role of the learning rate.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Training trajectories, mini-batch losses and the curious role of the learning rate

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.322544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.322544Z digest=sha256:6fd9f88e923a3d4af72c71efd3341b286738ebc938461920a01b695c90d2f511

Observation 73da079d-8e71-47cf-b9bd-b020e6655d68 · outbound

This paper cites Early Weight Averaging meets High Learning Rates for LLM Pre-training.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Early Weight Averaging meets High Learning Rates for LLM Pre-training

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.325724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.325724Z digest=sha256:40a4f0792994ab07f3f168fc2bfb3770df5405946c0c59a0be536ed242a7313d

Observation 7c6ee47d-7fbd-47c8-86ba-445a33954511 · outbound

This paper cites Language models are multilingual chain-of-thought reasoners.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Language models are multilingual chain-of-thought reasoners

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.816226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.329489Z digest=sha256:96e6c28d2c52c17834f8288ac79b221e8e9b6053e04febf4b7dbaf50310f9960

Observation 1cce468c-e7dd-4ef1-9218-fe5adff6e048 · outbound

This paper cites Through the river: Understanding the benefit of schedule-free methods for language model training.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Through the river: Understanding the benefit of schedule-free methods for language model training

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.808956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.333234Z digest=sha256:add5a3061a1a9e76ac4e6ff040c7c33d5f58a3cd60bdf5b1e7314db15e676b2e

Observation 4204b1e0-83ec-411d-9f30-1c2abe880c2b · outbound

This paper cites an unresolved cited work.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Unresolved cited work

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.335742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.335742Z digest=sha256:c34322d49efcce7d8092bae56b2f72bc7f7b48761b1ebc497804e26f81ddd395

Observation ea764802-3135-4306-af8b-8d21c68ddba5 · outbound

This paper cites Le, Ed H.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Le, Ed H

Reference 57

Resolution
malformed identifier
no resolver link, observed 2026-08-06T14:49:40.338371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.338371Z digest=sha256:a0c311d99230b997feb756209dd8e2cc040863c9c9f25ddd7f635cc3eeb475a5

Observation f812d33d-5413-472e-b7fc-955f835f8f3b · outbound

This paper cites Mathscale: Scaling instruction tuning for mathematical reasoning.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Mathscale: Scaling instruction tuning for mathematical reasoning

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.801334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.341316Z digest=sha256:8ebf7f3da142385245131adaa64d352c8de3e7b652a80be941ef85e325c3490c

Observation f4ea028c-ef97-4992-9152-210cc5ee25d2 · outbound

This paper cites Enhancing program synthesis with large language models using many-objective grammar-guided genetic programming.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Enhancing program synthesis with large language models using many-objective grammar-guided genetic programming

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.344028Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.344028Z digest=sha256:456e94eafb1c0b75720e2b743d39239ee081d37f59f9368b47b11d569af1e7ab

Observation 0027e135-283e-4e1f-9a36-87ef21193dba · outbound

This paper cites SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training SuperGPQA: Scaling LLM Evaluation across 285 Graduate Disciplines

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.346687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.346687Z digest=sha256:f467abb84bb57033081a33f9924f7c1d7cc64617f575fa4bb8eb9507d0cadb68

Observation d294a735-8dde-4bab-99cb-21384f5ecf60 · outbound

This paper cites Visualizing data using t-SNE.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Visualizing data using t-SNE

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.793666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.349777Z digest=sha256:dff17435f5fbec13841f59037aae77ecb77109e0663b063056fb371888dba4a5

Observation f28e7aef-5bda-4e5e-9835-af7e705c1959 · outbound

This paper cites Mmlu-pro: A more robust and challenging multi-task language understanding benchmark.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Mmlu-pro: A more robust and challenging multi-task language understanding benchmark

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.786032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.352418Z digest=sha256:afbb46020857322168569905b335680faff6e0e42c5b6da01d633061424dee9f

Observation e3538294-b9c8-4b01-8041-8c5902f68996 · outbound

This paper cites CMATH: Can Your Language Model Pass Chinese Elementary School Math Test?.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training CMATH: Can Your Language Model Pass Chinese Elementary School Math Test?

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.355079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.355079Z digest=sha256:fc2b3e0343ebbe28740207a3be87c85b49333de93004c6989136f625979c5bcf

Observation 448880cd-8952-4b5d-af44-e21859de42a6 · outbound

This paper cites Understanding Warmup-Stable-Decay Learning Rates: A River Valley Loss Landscape Perspective.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Understanding Warmup-Stable-Decay Learning Rates: A River Valley Loss Landscape Perspective

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.357950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.357950Z digest=sha256:b7dac657315a94a4579350856d7cff444e9116f0e351f828e78b779a549bb1a0

Observation 4900d096-1dbc-4dbe-a105-665d9c9757d0 · outbound

This paper cites Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, and Ludwig Schmidt.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, and Ludwig Schmidt

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.778343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.360788Z digest=sha256:ae6e52f4fa99f1e0405945b0bc6563809c4f25cb93cda5b5b44142539b329efa

Observation 99940e47-70b3-4835-96e4-0630566f407a · outbound

This paper cites Hellaswag: Can a machine really finish your sentence? In Anna Korhonen, David R.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Hellaswag: Can a machine really finish your sentence? In Anna Korhonen, David R

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.363376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.363376Z digest=sha256:a9327a7303120301b0048f0c2c009580cac864330bf515d8299e08188dcda501

Observation 1ae4fb1b-a952-4491-b770-84f014fa9064 · outbound

This paper cites Foster, and Sham M.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Foster, and Sham M

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.771043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.366670Z digest=sha256:c8a9add1ec444f658c2fa39d385923d5c36784d918d0d06ab77d6ec42d6c9bc9

Observation 3075dbd0-d7ad-43e0-bed6-b43256ac86dd · outbound

This paper cites Why gradient clipping accelerates training: A theoretical justification for adaptivity.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Why gradient clipping accelerates training: A theoretical justification for adaptivity

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T14:49:40.763979Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-06T14:49:40.369002Z digest=sha256:21b84e72c2be281a57f7f6d4a6ad18dbb55ea74c668f301937045eb46d39a6c0

Observation 9435e165-90f4-4332-b5e9-359316fbaa19 · outbound

This paper cites Evaluating the Performance of Large Language Models on GAOKAO Benchmark.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.371463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.371463Z digest=sha256:00d816c46d094112e8cf8825d00496e1156480c52e4f4fea1df33905ac35e086

Observation f730784f-86c2-46b1-9910-f09757b42636 · outbound

This paper cites Agieval: A human-centric benchmark for evaluating foundation models.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Agieval: A human-centric benchmark for evaluating foundation models

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-06T14:49:40.374840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:49:40.374840Z digest=sha256:56c28f096a87fcd03411bedab3a1547e5fe1c30a632703674dc91854125fbb09

Pith citing papers

Observation e5a9069d-4f1c-40a3-96cc-fe6071bece89 · inbound

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities cites this paper.

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training

Reference 222

Resolution
verified exact
arxiv_id, observed 2026-05-17T22:16:04.630970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-17T22:16:04.386706Z digest=sha256:f459130bc7ce9241b377cf7d57eb44f0a2386101cad2c7573f672a21f7ae8dc8

Observation 28d0e392-e39a-4e9d-97eb-ce31a2ebb1e0 · inbound

LLaDA2.0: Scaling Up Diffusion Language Models to 100B cites this paper.

LLaDA2.0: Scaling Up Diffusion Language Models to 100B WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-14T18:53:21.153791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-14T18:53:20.911374Z digest=sha256:ef270953d67f27811e30961aa24a6ee4bf38a3b19e6030876329232ab74dc45b

Observation 9a673bd1-0782-431b-b822-ae5f7cfa19aa · inbound

Low-rank Optimization Trajectories Modeling for LLM RLVR Acceleration cites this paper.

Low-rank Optimization Trajectories Modeling for LLM RLVR Acceleration WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training

Reference 30

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T09:16:04.606637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T16:07:20.180349Z digest=sha256:2f1094e58e658666ae2ccb8a40ea67f51fd53648f1a721d1637869b48df9782f

Observation da5f2e47-57cc-4cf2-96e2-cf75387d6980 · inbound

Nucleus-Image: Sparse MoE for Image Generation cites this paper.

Nucleus-Image: Sparse MoE for Image Generation WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training

Reference 33

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T10:26:00.500863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T15:30:46.994872Z digest=sha256:ff62c8e0c9d5ac0bbbd62bbedec137284c18748d11428778101ab9a874948368

Observation 03f0c8e7-2dbf-42b5-9192-ee498d954630 · inbound

Predictable Scaling Laws of Optimal Hyperparameters for LLM Continued Pre-training cites this paper.

Predictable Scaling Laws of Optimal Hyperparameters for LLM Continued Pre-training WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training

Reference 26

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T12:46:56.726091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T01:53:04.715108Z digest=sha256:e7d1071b736406267c1a8782aef6170242b030e87cecad12577bf735cdabef67

Observation faf207a2-565d-44f8-93f8-594a43b59c56 · inbound

Optimizing Visual Generative Models via Distribution-wise Rewards cites this paper.

Optimizing Visual Generative Models via Distribution-wise Rewards WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training

Reference 30

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T16:48:39.720432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-07-03T16:39:12.711424Z digest=sha256:dbc7025d9d9f2c8e4213c483843eaa3e9bba8b1c965e65fa1239fbe58a77fe05

Observation 946f17a8-297a-41de-843e-b5edf6e0d030 · inbound

WSqD: A Horizon-Free Learning Rate Schedule for Large Model Training cites this paper.

WSqD: A Horizon-Free Learning Rate Schedule for Large Model Training WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training

Reference 50

Resolution
unresolved
no resolver link, observed 2026-07-14T08:04:06.432613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T08:04:06.432613Z digest=sha256:311d2650139b1a804ef81dd03dd1b2bab857759ff7f3283ea36c6f45794afd0d