Paper Citation Record · LEDGER

Deep Model Fusion: A Survey

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:2309.15698.

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

pith.paper-citation-record.v1
2309.15698 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T21:40:12.850105Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T23:39:03.999810Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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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 aba745d4-75c5-4566-a528-eccb5aeef5c4 · 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 Deep Model Fusion: A Survey

Reference 127

Resolution: verified exact; arxiv_id, observed 2026-05-17T22:16:04.515522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 075aff62-1952-44f4-bea2-96c0b9cf2789 · inbound

No Task Left Behind: Isotropic Model Merging with Common and Task-Specific Subspaces cites this paper.

No Task Left Behind: Isotropic Model Merging with Common and Task-Specific Subspaces Deep Model Fusion: A Survey

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-08T20:55:14.205607Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a575a5b-d925-4bb3-b96b-6b35a02c3964 · inbound

Model Fusion via Neuron Transplantation cites this paper.

Model Fusion via Neuron Transplantation Deep Model Fusion: A Survey

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-08T21:40:12.850105Z

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Observation 6d2c95c2-08b8-48b1-84b6-3de5d7c99595 · inbound

SeWA: Selective Weight Average via Probabilistic Masking cites this paper.

SeWA: Selective Weight Average via Probabilistic Masking Deep Model Fusion: A Survey

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T19:24:43.113821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 001b5d8a-0b71-407f-9b32-d52c141a150b · inbound

Model Merging is Secretly Certifiable: Non-Vacuous Generalisation Bounds for Low-Shot Learning cites this paper.

Model Merging is Secretly Certifiable: Non-Vacuous Generalisation Bounds for Low-Shot Learning Deep Model Fusion: A Survey

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T15:18:31.823158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f6daf25-4f50-437f-8787-27b32bbab15c · inbound

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition cites this paper.

FCOS: A Two-Stage Recoverable Model Pruning Framework for Automatic Modulation Recognition Deep Model Fusion: A Survey

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-07T13:50:56.276806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 249ffc4c-a126-4cd1-a807-7fe1b1ad2ca0 · inbound

Assembly of Experts: Linear-time construction of the Chimera LLM variants with emergent and adaptable behaviors cites this paper.

Assembly of Experts: Linear-time construction of the Chimera LLM variants with emergent and adaptable behaviors Deep Model Fusion: A Survey

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T12:05:09.563505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 441d0559-8928-43c9-a974-f4360e20a9da · inbound

Graft: Integrating the Domain Knowledge via Efficient Parameter Synergy for MLLMs cites this paper.

Graft: Integrating the Domain Knowledge via Efficient Parameter Synergy for MLLMs Deep Model Fusion: A Survey

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T21:32:23.768843Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d918ef93-2996-450f-8931-6fef25cf3232 · inbound

Forgetting of task-specific knowledge in model merging-based continual learning cites this paper.

Forgetting of task-specific knowledge in model merging-based continual learning Deep Model Fusion: A Survey

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T10:55:30.414042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df2f29bd-326e-4756-80c1-3eeb01b0cd26 · inbound

ICM-Fusion: In-Context Meta-Optimized LoRA Fusion for Multi-Task Adaptation cites this paper.

ICM-Fusion: In-Context Meta-Optimized LoRA Fusion for Multi-Task Adaptation Deep Model Fusion: A Survey

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-06T00:55:58.036466Z

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Unavailable: canonical work link unavailable.

Observation db081153-0b95-475e-bc93-1a313d40268c · inbound

PSO-Merging: Merging Models Based on Particle Swarm Optimization cites this paper.

PSO-Merging: Merging Models Based on Particle Swarm Optimization Deep Model Fusion: A Survey

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-05T15:30:25.086213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 494bc12a-4278-4a1c-ba7a-8a72d0e03ad6 · inbound

Model Unmerging: Making Your Models Unmergeable for Secure Model Sharing cites this paper.

Model Unmerging: Making Your Models Unmergeable for Secure Model Sharing Deep Model Fusion: A Survey

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-05T12:34:51.230083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3afed03b-54ec-4048-a723-2a0e02fc70e6 · inbound

Semantic-guided LoRA Parameters Generation cites this paper.

Semantic-guided LoRA Parameters Generation Deep Model Fusion: A Survey

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T05:37:06.252859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 018a4723-edef-4e04-a9ee-67f6f3095c34 · inbound

Efficient and Accurate Method for Separating Variant Components from Invariant Background and Component Model Fusion for Fast RFIC Design Space Exploration cites this paper.

Efficient and Accurate Method for Separating Variant Components from Invariant Background and Component Model Fusion for Fast RFIC Design Space Exploration Deep Model Fusion: A Survey

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T21:09:28.363858Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4b14c5a-f9b4-457b-abcb-fbbb4343c5a3 · inbound

Can Heterogeneous Language Models Be Fused? cites this paper.

Can Heterogeneous Language Models Be Fused? Deep Model Fusion: A Survey

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-21T11:00:02.158877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c1eaddbc-45c2-40a3-9dfb-7999186a3abf · inbound

UIPress: Bringing Optical Token Compression to UI-to-Code Generation cites this paper.

UIPress: Bringing Optical Token Compression to UI-to-Code Generation Deep Model Fusion: A Survey

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:00:59.409149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 42bf4e07-bf2d-4d0d-b212-4fe1ec86f032 · inbound

Good Agentic Friends Do Not Just Give Verbal Advice: They Can Update Your Weights cites this paper.

Good Agentic Friends Do Not Just Give Verbal Advice: They Can Update Your Weights Deep Model Fusion: A Survey

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:02:50.241526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 131afb8f-b5df-4dbf-bb11-ac6575af0cd0 · inbound

Unlocking the Potential of Continual Model Merging: An ODE Perspective cites this paper.

Unlocking the Potential of Continual Model Merging: An ODE Perspective Deep Model Fusion: A Survey

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:38:09.352868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d18b25db-e022-44c3-b574-07689f432aa4 · inbound

Unlocking the Potential of Continual Model Merging: An ODE Perspective cites this paper.

Unlocking the Potential of Continual Model Merging: An ODE Perspective Deep Model Fusion: A Survey

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-21T08:34:05.542182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 88e998d6-9341-4121-bfd0-984ec2292bcb · inbound

Unlocking the Potential of Continual Model Merging: An ODE Perspective cites this paper.

Unlocking the Potential of Continual Model Merging: An ODE Perspective Deep Model Fusion: A Survey

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-06-30T18:04:58.448402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 22b97396-d274-4de6-87ad-581d4482ceb8 · inbound

DLLG: Dynamic Logit-Level Gating of LLM Experts cites this paper.

DLLG: Dynamic Logit-Level Gating of LLM Experts Deep Model Fusion: A Survey

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T07:36:45.081192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9163e3de-e959-41cc-8fc5-5f407245045a · inbound

PACT: Preserving Anchored Cores in Task-vectors for Model Merging cites this paper.

PACT: Preserving Anchored Cores in Task-vectors for Model Merging Deep Model Fusion: A Survey

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-03T23:39:04.002756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5b9808da-7d7b-4d4e-a7d9-1e9bd15ce4c7 · inbound

Model Merging as Probabilistic Inference in Fine-Tuning Parameter Space cites this paper.

Model Merging as Probabilistic Inference in Fine-Tuning Parameter Space Deep Model Fusion: A Survey

Reference 58

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T17:58:46.807720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b436762a-c77c-4d07-9711-ea9840ab17ca · inbound

Personalized Image Aesthetic Assessment via Preference-rich Sample Mining and Cohort Merging cites this paper.

Personalized Image Aesthetic Assessment via Preference-rich Sample Mining and Cohort Merging Deep Model Fusion: A Survey

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-01T22:28:24.374751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b20e4f6-8b79-4467-b31f-5c236c4a2124 · inbound

Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs cites this paper.

Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Deep Model Fusion: A Survey

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-01T06:05:56.106373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.