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Paper Citation Record · LEDGER

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging

As of 7 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 1 inbound Pith citation observation for arXiv:2603.00573.

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

pith.paper-citation-record.v1
2603.00573 v2

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T19:55:06.879029Z

measured 39 of 39 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-11T21:34:44.701020Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

38 of 38 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved37
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b8782ea1-332b-47aa-8de3-aa6098c93a2c · outbound

This paper cites GPT-4 Technical Report.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging GPT-4 Technical Report

Reference 1

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source=arxiv_source observed=2026-08-02T19:55:05.057370Z digest=sha256:251b56480571ceaa9f8049f690a7f27be728a0d6f6d5124255e49fe47dbbe48b

Observation 7bf38c50-94e9-4d2b-b82e-e35a99173249 · outbound

This paper cites an unresolved cited work.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Unresolved cited work

Reference 2

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source=arxiv_source observed=2026-08-02T19:55:05.126176Z digest=sha256:c874636dbe2cc4c8d72f7d8e35f54fb8d5f56d5e93b27013fd82f97cb44c104f

Observation b3cc79c8-cb55-4be8-960f-94e5e716ee83 · outbound

This paper cites an unresolved cited work.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Unresolved cited work

Reference 3

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source=arxiv_source observed=2026-08-02T19:55:05.252879Z digest=sha256:ff9e52d23c4bc2fd0c2cfd2f819ebef2c471cc95d3e7683e9d3abc5095c256c0

Observation 6b87383e-53a7-4429-8631-61d1c0fbcfbf · outbound

This paper cites an unresolved cited work.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Unresolved cited work

Reference 4

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source=arxiv_source observed=2026-08-02T19:55:05.339226Z digest=sha256:1d22f71b9b3ab2af1edbe4553a8faebcacc32c8e299c15397c674b5ff4402aab

Observation ee94f908-14cb-4360-89ed-548310417cd6 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Evaluating Large Language Models Trained on Code

Reference 5

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source=arxiv_source observed=2026-08-02T19:55:05.465009Z digest=sha256:b2a5b518cf37b433a11e3344307a8cad6840eb8ed8b0de266828ca750f218ab2

Observation a039aaa7-28ba-4fc0-b787-a7c4fcacd68b · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Training Verifiers to Solve Math Word Problems

Reference 6

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source=arxiv_source observed=2026-08-02T19:55:05.589430Z digest=sha256:6d9edc8f2a9ca9f626760c89715eaea10ab966758685e3303de7c6098b67d94d

Observation 076e1bad-6acf-4b81-b1b4-dfcde557d036 · outbound

This paper cites LoRAMoE: Alleviate World Knowledge Forgetting in Large Language Models via MoE-Style Plugin.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging LoRAMoE: Alleviate World Knowledge Forgetting in Large Language Models via MoE-Style Plugin

Reference 7

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source=arxiv_source observed=2026-08-02T19:55:05.641686Z digest=sha256:38e3026c97ef406504339cd2422db6077309ea9f0d963d4a1a672b11a83e6089

Observation e80d4de0-900f-4227-ab29-feaffb7d9317 · outbound

This paper cites Higher Layers Need More LoRA Experts.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Higher Layers Need More LoRA Experts

Reference 8

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source=arxiv_source observed=2026-08-02T19:55:05.756275Z digest=sha256:194547234646b6503ffdf4900752cea3212fae507f0c24494afa74a607023661

Observation a07b45e3-cf80-4df8-8d8c-4ab98b08481c · outbound

This paper cites The Llama 3 Herd of Models.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging The Llama 3 Herd of Models

Reference 9

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source=arxiv_source observed=2026-08-02T19:55:05.909319Z digest=sha256:2afafd6c63c84c3c57c83ad0c95eb63ca622b8076099bcd8950bcfa600ec934b

Observation 573a5c76-58f1-4e07-9a12-8afd6c39dfa0 · outbound

This paper cites Towards a Unified View of Parameter-Efficient Transfer Learning.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Towards a Unified View of Parameter-Efficient Transfer Learning

Reference 10

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source=arxiv_source observed=2026-08-02T19:55:06.061113Z digest=sha256:8b59690cc79b6d65e7e190732fbde4a1f8ddf9842bbe3b81c89a053103164ca1

Observation 85b0516e-689b-4ecf-a092-a4e049119794 · outbound

This paper cites an unresolved cited work.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Unresolved cited work

Reference 11

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source=arxiv_source observed=2026-08-02T19:55:06.223400Z digest=sha256:d30ba5d25c9db6d92e99c5705be6ce6e20380bf2618d1b87666f7254a9454dac

Observation b5f8774e-ce2a-4dd5-aebf-4114f64a9ffb · outbound

This paper cites Houlsby, A.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Houlsby, A

Reference 12

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source=arxiv_source observed=2026-08-02T19:55:06.273129Z digest=sha256:561ca0f1c94f6ec4130227d1f6f2d47869095ede482fe3f9abafff14049ebb8c

Observation 05cd9b6a-cda7-40f5-a29b-72e179dc926d · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging LoRA: Low-Rank Adaptation of Large Language Models

Reference 13

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source=arxiv_source observed=2026-08-02T19:55:06.382328Z digest=sha256:c90807199d8a9191afc96cea21743332350ab1049d0cb9f056033f9ad2c38614

Observation 577a8ba4-93a2-48c8-af13-b2f477d4e26a · outbound

This paper cites LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 14

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Observation b644789c-a261-4000-a2e6-64a74d53ab94 · outbound

This paper cites an unresolved cited work.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Unresolved cited work

Reference 15

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Observation 777d3904-db0d-4a03-a8f8-d4ca1b0e0bb9 · outbound

This paper cites an unresolved cited work.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Unresolved cited work

Reference 16

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Observation 54ad279b-4694-486b-9cf8-cfe60cfe620a · outbound

This paper cites an unresolved cited work.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Unresolved cited work

Reference 17

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Observation ec339317-7ab7-422d-9b93-165a5a389485 · outbound

This paper cites TeamLoRA: Boosting Low-Rank Adaptation with Expert Collaboration and Competition.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging TeamLoRA: Boosting Low-Rank Adaptation with Expert Collaboration and Competition

Reference 18

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Observation 67d2d0f2-af7d-411d-bbe1-114093ec684a · outbound

This paper cites Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems

Reference 19

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Observation 14851ee0-4189-46f9-885c-715ff9f9a035 · outbound

This paper cites an unresolved cited work.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Unresolved cited work

Reference 20

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Observation aa14951d-eed7-4c3f-b580-faa416d73f57 · outbound

This paper cites AdaMoLE: Fine-Tuning Large Language Models with Adaptive Mixture of Low-Rank Adaptation Experts.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging AdaMoLE: Fine-Tuning Large Language Models with Adaptive Mixture of Low-Rank Adaptation Experts

Reference 21

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Observation d2e80be4-b240-443c-8fe1-3251e5c44b3f · outbound

This paper cites MoELoRA: Contrastive Learning Guided Mixture of Experts on Parameter-Efficient Fine-Tuning for Large Language Models.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging MoELoRA: Contrastive Learning Guided Mixture of Experts on Parameter-Efficient Fine-Tuning for Large Language Models

Reference 22

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Observation f0fe0136-8039-47e9-aa5f-d897dec7e09e · outbound

This paper cites DenseLoRA: Dense Low-Rank Adaptation of Large Language Models.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging DenseLoRA: Dense Low-Rank Adaptation of Large Language Models

Reference 23

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source=arxiv_source observed=2026-08-02T19:55:06.811327Z digest=sha256:1488c9f45f6f95d650392dbff35585752086a6d3d918131e843bff6dcf1cc799

Observation 0004893e-f39d-48d5-8a1e-593809a6a2e4 · outbound

This paper cites Soft Merging of Experts with Adaptive Routing.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Soft Merging of Experts with Adaptive Routing

Reference 24

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Observation 5c8e0a35-a3b0-4a2d-aa86-b9f3aa9c39cc · outbound

This paper cites Accurate and efficient low-rank model merging in core space.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Accurate and efficient low-rank model merging in core space

Reference 25

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Observation 64212d36-aece-4495-87f8-27fee01f3eff · outbound

This paper cites Are NLP Models really able to Solve Simple Math Word Problems?.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Are NLP Models really able to Solve Simple Math Word Problems?

Reference 26

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Observation af91ea5d-8326-4ea5-a807-9ec87487b17d · outbound

This paper cites Solving General Arithmetic Word Problems.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Solving General Arithmetic Word Problems

Reference 27

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Observation 2305a981-b27a-4183-8e5b-ba2251c98edd · outbound

This paper cites Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Reference 28

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Observation 3fc7a3b5-9cc6-42ff-a02b-f2737f39a2f9 · outbound

This paper cites HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging HydraLoRA: An Asymmetric LoRA Architecture for Efficient Fine-Tuning

Reference 29

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Observation b6d0244e-5ad2-4417-be5e-33a8b04ba2db · outbound

This paper cites an unresolved cited work.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Unresolved cited work

Reference 30

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation f9fa49b9-23b5-4019-a803-4b8a9efe6608 · outbound

This paper cites an unresolved cited work.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Unresolved cited work

Reference 31

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Observation 6f6f95ba-69e1-47e0-bb8b-626c70c2b2a8 · outbound

This paper cites Mixture of LoRA Experts.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Mixture of LoRA Experts

Reference 32

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Observation 49adcdd3-0f6b-4f98-8355-6abb8c184967 · outbound

This paper cites Qwen3 Technical Report.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Qwen3 Technical Report

Reference 33

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Observation b4b74f0d-11a8-41c8-b54a-5c498aa59604 · outbound

This paper cites Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction Tuning

Reference 34

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Observation 063e802f-4606-4611-9e9b-492613ab5831 · outbound

This paper cites SiRA: Sparse Mixture of Low Rank Adaptation.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging SiRA: Sparse Mixture of Low Rank Adaptation

Reference 35

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source=arxiv_source observed=2026-08-02T19:55:06.864884Z digest=sha256:51d79451cf7c0176a764afd52928f103505302fef0af602fd1fd8569518244c0

Observation b63a3d0c-ba9a-4dd7-ac75-1ea15380c8cd · outbound

This paper cites Flylora: Boosting task decoupling and parameter efficiency via implicit rank-wise mixture-of-experts.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging Flylora: Boosting task decoupling and parameter efficiency via implicit rank-wise mixture-of-experts

Reference 36

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Observation 1b0909cf-d89e-4014-a314-544b5ed40e5e · outbound

This paper cites online" 'onlinestring :=.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging online" 'onlinestring :=

Reference 37

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Observation 358673c6-5e8f-423c-86de-4886757ac12e · outbound

This paper cites write newline.

CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging write newline

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Parametric Memory Decoding for Zero-Shot Routing in LoRA-Based External Parametric Memory cites this paper.

Parametric Memory Decoding for Zero-Shot Routing in LoRA-Based External Parametric Memory CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging

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