Pith. sign in

Paper Citation Record · LEDGER

Deep Model Fusion: A Survey

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 27 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 27 of 27 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 27 of 27 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T04:20:37.639405Z

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
  • unresolved0
  • parse uncertain0
  • 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 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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-17T22:16:04.386706Z digest=sha256:67df02f8b8edf67c0108fe200e3746c64fe2a807460e66ae29f719bb27fc085d

Observation db70bbcc-cf4a-42a1-87dc-c12f63fd3890 · inbound

Beyond the Permutation Symmetry of Transformers: The Role of Rotation for Model Fusion cites this paper.

Beyond the Permutation Symmetry of Transformers: The Role of Rotation for Model Fusion Deep Model Fusion: A Survey

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-09T19:44:20.797091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T19:44:20.797091Z digest=sha256:022e5c15d676cf78e6f2776f90a40b1c3f181791616cfb4e55dd4d2ab07432e3

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.

source=pdf_text observed=2026-08-08T20:55:14.205607Z digest=sha256:3302c19d5fb0708ab9210f2d1314a1d1d58ef73813df8e316eb1ab96a2dff726

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T21:40:12.850105Z digest=sha256:4f9405c3c8d558ca78d8ba08d896292f36812c027f9411f0c2d4d0a890c1db95

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.

source=arxiv_source observed=2026-08-07T19:24:43.113821Z digest=sha256:91cef59849ece22c1c16e48afb97dc23fe7771cb5adc4f5fa56c7ff1bc055774

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.

source=pdf_text observed=2026-08-07T15:18:31.823158Z digest=sha256:51ee6702aac52ea977751f70ea937cfcd9172c2552221ff5624b6c09bafb5f2d

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.

source=pdf_text observed=2026-08-07T13:50:56.276806Z digest=sha256:7775c3020ec6d5ecc648413776a2b39b2022e93ad972370d99ffd31f01c81368

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.

source=pdf_text observed=2026-08-07T12:05:09.563505Z digest=sha256:2c26891117d14937de82fbd9b765fd59e98520e995653e2583233f3e12444b1a

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.

source=pdf_text observed=2026-08-06T21:32:23.768843Z digest=sha256:afb93f7b1839d6072a293f0f0081f052f36bfdd69b9792960f65d950bf860ae7

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.

source=arxiv_source observed=2026-08-06T10:55:30.414042Z digest=sha256:adcf69c554e7a787771febe1936a094209e12118b20666643815e898d2a95025

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T00:55:58.036466Z digest=sha256:2731520ee0e3b07941bb9f3db48a284c3efcd6e01f7c867db785ff4cdb1b2613

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.

source=pdf_text observed=2026-08-05T15:30:25.086213Z digest=sha256:0209906641baea1986be3174d7daf2afee8e011d5654139a73142d88b7bfce56

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.

source=arxiv_source observed=2026-08-05T12:34:51.230083Z digest=sha256:ec6c0f2188ebcb307496282026db5e6f6ebeac065048392f0adfe29038892191

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.

source=pdf_text observed=2026-08-05T05:37:06.252859Z digest=sha256:c6806d55975cf6aa0e7bbae20d4ac4c27126889256bfd5f11f2603f835b73c47

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.

source=pdf_text observed=2026-08-02T21:09:28.363858Z digest=sha256:25606b48a0c539eabc64aff83d8ddc665c32c99fb4d5709e1b890dbaaf2ac942

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-21T10:57:01.529364Z digest=sha256:661cc86abc18ff46a22b6701428c039498af301841011a9c26c51dcd1daef072

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-10T17:21:32.024105Z digest=sha256:7d7be54f3b896e10c9f79617913e25e6a37a46644b026e2a8cb5ef7ff883de02

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-14T19:01:09.224050Z digest=sha256:68edeeffb89391a05671ad4f2af91fa929af7fb5f4d91db39137b036bb6eef2f

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-20T07:36:04.114811Z digest=sha256:103338fafd60d0ab70e356e82d201a02b93ad070248269e1936f4a0ca5d4dd2a

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-21T08:32:04.249711Z digest=sha256:906fdb312fe1b3140d2940b7ee9cc3a9f9dbc75efebd56ec0fe1e92aa54bf71b

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-30T17:55:17.067856Z digest=sha256:2628d75c1f7b48fc040334dd299566df9904a0b57e44b75ae65d18790ff0fde4

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T06:50:32.988192Z digest=sha256:5f52bb7700fd5511f093fbceb85d4ac519101be8099a7bf3b7881e687b85b53e

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-26T21:57:07.546038Z digest=sha256:abfd1f80e6d475a736bd71578be4b87e54b548b683f1eb2f3cc9d44172d089df

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-07-03T17:51:43.100153Z digest=sha256:86d82e5e3b67bf1ee44e980c8d894ff56bf29872aed433a63f607a5bcce0ebbc

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.

source=pdf_text observed=2026-08-01T22:28:24.374751Z digest=sha256:d5443ac69ef131ec1311d1c5c65bff862d6c1becb47fcaddaa4dda000c4e549c

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.

source=arxiv_source observed=2026-08-01T06:05:56.106373Z digest=sha256:242eee50b0f793df9dd5979eff55a96c3357362472a543bc5749ca0fac04a03d

Observation e131c470-6399-4207-b102-8a0e936c0a43 · inbound

Automated item evaluation: Predicting item acceptance and rejection using LLM-generated critiques cites this paper.

Automated item evaluation: Predicting item acceptance and rejection using LLM-generated critiques Deep Model Fusion: A Survey

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-10T04:20:37.639405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T04:20:37.639405Z digest=sha256:8747a3a8e950824a73343f38592d2001762622fda923c11219866e31aff336d6