Paper Citation Record · LEDGER

Multi-Task Model Merging via Adaptive Weight Disentanglement

As of 16 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 12 inbound Pith citation observations for arXiv:2411.18729.

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

pith.paper-citation-record.v1
2411.18729 v2

Coverage vector

measured 49 of 49 reference resolution

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measured 61 of 61 standing notices

One-hop event checks from named stored sources.

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measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:15:10.490081Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:39:51.039526Z

Reference resolution

49 of 49 outbound references displayed

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External citation measurements

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Outbound references

Observation 3ba0308a-b249-4c2e-b3b7-fa5e4b891727 · outbound

This paper cites Git re-basin: Merging models modulo permutation symmetries.

Multi-Task Model Merging via Adaptive Weight Disentanglement Git re-basin: Merging models modulo permutation symmetries

Reference 1

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Observation eb94627c-d951-43d3-b09e-6cb2dfdec307 · outbound

This paper cites Lan- guage models are Homer simpson! safety re-alignment of fine-tuned language models through task arithmetic.

Multi-Task Model Merging via Adaptive Weight Disentanglement Lan- guage models are Homer simpson! safety re-alignment of fine-tuned language models through task arithmetic

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:16.190142Z

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Observation 748dc33e-556f-41cf-bd9f-9f0bfee6cef4 · outbound

This paper cites Remote sens- ing image scene classification: Benchmark and state of the art.

Multi-Task Model Merging via Adaptive Weight Disentanglement Remote sens- ing image scene classification: Benchmark and state of the art

Reference 3

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Observation e8e137d0-4457-42cb-9a81-9fd33415ded7 · outbound

This paper cites Describing textures in the wild.

Multi-Task Model Merging via Adaptive Weight Disentanglement Describing textures in the wild

Reference 4

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Observation 756a8cf6-6a03-4cd7-9699-a5efc383e4b1 · outbound

This paper cites Knowledge neurons in pretrained transform- ers.

Multi-Task Model Merging via Adaptive Weight Disentanglement Knowledge neurons in pretrained transform- ers

Reference 5

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Observation 7625d420-9620-4126-a0a8-41f1ee70dccd · outbound

This paper cites Orthogonal gradient descent for continual learning.

Multi-Task Model Merging via Adaptive Weight Disentanglement Orthogonal gradient descent for continual learning

Reference 6

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Observation 90c690bf-4701-4ae3-a19a-bfc2f2c80a43 · outbound

This paper cites Adaptive orthogonal projection for batch and online contin- ual learning.

Multi-Task Model Merging via Adaptive Weight Disentanglement Adaptive orthogonal projection for batch and online contin- ual learning

Reference 7

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Observation 1132dfe3-017a-4753-b29d-8d08a326ccb5 · outbound

This paper cites Localize-and-stitch: Efficient model merging via sparse task arithmetic.

Multi-Task Model Merging via Adaptive Weight Disentanglement Localize-and-stitch: Efficient model merging via sparse task arithmetic

Reference 8

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Observation cb5e5022-96a1-4c00-ac0e-5ad6ef3dcc6a · outbound

This paper cites Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification.

Multi-Task Model Merging via Adaptive Weight Disentanglement Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification

Reference 9

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Observation 5c55f9cf-b6ae-41ea-a611-7e77a662136c · outbound

This paper cites Editing models with task arithmetic.

Multi-Task Model Merging via Adaptive Weight Disentanglement Editing models with task arithmetic

Reference 10

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Observation 926fc5d7-413a-4f7d-be7a-3a0fc57ecb92 · outbound

This paper cites Dataless knowledge fusion by merging weights of language models.

Multi-Task Model Merging via Adaptive Weight Disentanglement Dataless knowledge fusion by merging weights of language models

Reference 11

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Observation f9a31f4a-7aa1-4eff-bd94-7d3da9d31a15 · outbound

This paper cites REPAIR: REnormalizing permuted activations for interpolation repair.

Multi-Task Model Merging via Adaptive Weight Disentanglement REPAIR: REnormalizing permuted activations for interpolation repair

Reference 12

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Observation 49dd3519-ebb2-44a8-8590-5c19eb484245 · outbound

This paper cites 3d object representations for fine-grained categorization.

Multi-Task Model Merging via Adaptive Weight Disentanglement 3d object representations for fine-grained categorization

Reference 13

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Observation f52d46d5-3131-4a63-a45c-681318db10f0 · outbound

This paper cites The mnist database of handwritten digits.

Multi-Task Model Merging via Adaptive Weight Disentanglement The mnist database of handwritten digits

Reference 14

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Observation 274f761c-3e2b-4929-9b41-560869602b52 · outbound

This paper cites Towards continual learning desiderata via hsic-bottleneck orthogonalization and equian- gular embedding.

Multi-Task Model Merging via Adaptive Weight Disentanglement Towards continual learning desiderata via hsic-bottleneck orthogonalization and equian- gular embedding

Reference 15

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Observation fbd606ef-e6a9-4934-b4d5-893c55731d2c · outbound

This paper cites Model-protected multi-task learning.

Multi-Task Model Merging via Adaptive Weight Disentanglement Model-protected multi-task learning

Reference 16

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Observation c81a6616-2e4e-404d-a6b2-0b562a83d2ad · outbound

This paper cites Roberta: A robustly optimized bert pretraining approach.

Multi-Task Model Merging via Adaptive Weight Disentanglement Roberta: A robustly optimized bert pretraining approach

Reference 17

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Observation c33b4422-edf7-4c4a-894e-f5c9e5e04e45 · outbound

This paper cites Twin-merging: Dynamic integration of modular expertise in model merging.

Multi-Task Model Merging via Adaptive Weight Disentanglement Twin-merging: Dynamic integration of modular expertise in model merging

Reference 18

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Observation 4dbb69c8-be78-4b35-8419-b05e8b8a2eb5 · outbound

This paper cites Merging models with fisher-weighted averaging.

Multi-Task Model Merging via Adaptive Weight Disentanglement Merging models with fisher-weighted averaging

Reference 19

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Observation aa0a2762-76c1-4d4f-94f4-488922d2de3c · outbound

This paper cites Learning to route among specialized experts for zero- shot generalization.

Multi-Task Model Merging via Adaptive Weight Disentanglement Learning to route among specialized experts for zero- shot generalization

Reference 20

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Observation a108a3af-8432-4f6d-8b34-5a9c35e2569c · outbound

This paper cites Task arithmetic in the tangent space: Improved editing of pre-trained models.

Multi-Task Model Merging via Adaptive Weight Disentanglement Task arithmetic in the tangent space: Improved editing of pre-trained models

Reference 21

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Observation 63849d2d-52a6-4bd9-a9e8-1b5bf957c652 · outbound

This paper cites Learning transferable visual models from natural language supervision.

Multi-Task Model Merging via Adaptive Weight Disentanglement Learning transferable visual models from natural language supervision

Reference 22

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Multi-Task Model Merging via Adaptive Weight Disentanglement Unresolved cited work

Reference 23

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Observation 09fd2d29-1b5d-4dc5-a42b-8cfdf3e7b71f · outbound

This paper cites Continual learning with scaled gradient projection.

Multi-Task Model Merging via Adaptive Weight Disentanglement Continual learning with scaled gradient projection

Reference 24

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Observation b780059e-5c0d-4315-8cfe-1fea2a8f538f · outbound

This paper cites Multitask prompted training enables zero-shot task general- ization.

Multi-Task Model Merging via Adaptive Weight Disentanglement Multitask prompted training enables zero-shot task general- ization

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:15.994466Z

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Observation 8634cacb-64f0-461e-bc70-a2fc649636a7 · outbound

This paper cites The german traffic sign recognition bench- mark: a multi-class classification competition.

Multi-Task Model Merging via Adaptive Weight Disentanglement The german traffic sign recognition bench- mark: a multi-class classification competition

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:15.985029Z

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Observation a6a29392-ac25-4eb3-962f-53645fed2011 · outbound

This paper cites Parameter-efficient multi-task model fusion with partial linearization.

Multi-Task Model Merging via Adaptive Weight Disentanglement Parameter-efficient multi-task model fusion with partial linearization

Reference 27

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Observation f10b6767-7886-4582-9249-f6b0d9234e7e · outbound

This paper cites Parameter-efficient multi-task model fusion with partial linearization.

Multi-Task Model Merging via Adaptive Weight Disentanglement Parameter-efficient multi-task model fusion with partial linearization

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:15.967950Z

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This paper cites Tran, Xavier Garcia, Jason Wei, Xuezhi Wang, Hyung Won Chung, Dara Bahri, Tal Schuster, Steven Zheng, Denny Zhou, Neil Houlsby, and Donald Metzler.

Multi-Task Model Merging via Adaptive Weight Disentanglement Tran, Xavier Garcia, Jason Wei, Xuezhi Wang, Hyung Won Chung, Dara Bahri, Tal Schuster, Steven Zheng, Denny Zhou, Neil Houlsby, and Donald Metzler

Reference 29

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Observation 8071ed3f-2cca-4cc5-a9c8-e31ca6e40f63 · outbound

This paper cites Is fine-tuning needed? pre-trained language models are near perfect for out-of-domain detection.

Multi-Task Model Merging via Adaptive Weight Disentanglement Is fine-tuning needed? pre-trained language models are near perfect for out-of-domain detection

Reference 30

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Observation 2f186ccb-a036-42e0-a94e-cee678121f4d · outbound

This paper cites Knowledge fusion of large language models.

Multi-Task Model Merging via Adaptive Weight Disentanglement Knowledge fusion of large language models

Reference 31

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Observation 7e9355b6-f48c-42f1-9f87-9380eb45540b · outbound

This paper cites GLUE: A multi-task benchmark and analysis platform for natural language un- derstanding.

Multi-Task Model Merging via Adaptive Weight Disentanglement GLUE: A multi-task benchmark and analysis platform for natural language un- derstanding

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:15.934290Z

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Observation 4fa5ecba-90bf-4999-8cd0-e65ca882f84f · outbound

This paper cites Localizing task infor- mation for improved model merging and compression.

Multi-Task Model Merging via Adaptive Weight Disentanglement Localizing task infor- mation for improved model merging and compression

Reference 33

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Observation 476aded7-1294-491a-8ffb-a2aad3004b7e · outbound

This paper cites A comprehensive survey of continual learning: Theory, method and application.

Multi-Task Model Merging via Adaptive Weight Disentanglement A comprehensive survey of continual learning: Theory, method and application

Reference 34

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Observation d2346e32-efe7-4a97-b37e-16f1d86260b9 · outbound

This paper cites Orthogonal Subspace Learning for Language Model Continual Learning.

Multi-Task Model Merging via Adaptive Weight Disentanglement Orthogonal Subspace Learning for Language Model Continual Learning

Reference 35

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This paper cites Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time.

Multi-Task Model Merging via Adaptive Weight Disentanglement Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:15.908891Z

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Observation 03f0f4d6-5d96-471a-ab9f-3732801c1b84 · outbound

This paper cites Sun database: Exploring a large col- lection of scene categories.

Multi-Task Model Merging via Adaptive Weight Disentanglement Sun database: Exploring a large col- lection of scene categories

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:15.899950Z

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Observation 99547a45-8b53-40da-b787-03d50f44c5c2 · outbound

This paper cites Active finetuning: Exploiting an- notation budget in the pretraining-finetuning paradigm.

Multi-Task Model Merging via Adaptive Weight Disentanglement Active finetuning: Exploiting an- notation budget in the pretraining-finetuning paradigm

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:15.891306Z

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This paper cites Ties-merging: resolving interfer- ence when merging models.

Multi-Task Model Merging via Adaptive Weight Disentanglement Ties-merging: resolving interfer- ence when merging models

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:15.882820Z

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Observation 23c3e567-92ec-45dc-a7a7-1d2bec4e41ed · outbound

This paper cites Model merging in llms, mllms, and beyond: Methods, theories, applications and opportunities.

Multi-Task Model Merging via Adaptive Weight Disentanglement Model merging in llms, mllms, and beyond: Methods, theories, applications and opportunities

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:15.874340Z

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Observation 394efd8c-99a5-43f6-ab57-b08696bc1452 · outbound

This paper cites Representation 10 surgery for multi-task model merging.

Multi-Task Model Merging via Adaptive Weight Disentanglement Representation 10 surgery for multi-task model merging

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:15.865557Z

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Observation a4fa28ee-1dee-44b9-9bdd-d2ddf5e9a8f4 · outbound

This paper cites Adamerging: Adap- tive model merging for multi-task learning.

Multi-Task Model Merging via Adaptive Weight Disentanglement Adamerging: Adap- tive model merging for multi-task learning

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:15.857125Z

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Observation 8bd2782c-9ed4-498f-8b7a-8d8d852a89bc · outbound

This paper cites On the dimensionality of word embedding.

Multi-Task Model Merging via Adaptive Weight Disentanglement On the dimensionality of word embedding

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:15.848020Z

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Observation 52020132-4fed-4cc9-8bdd-d79d59abd6ec · outbound

This paper cites Language models are super mario: Absorbing abilities from homologous models as a free lunch.

Multi-Task Model Merging via Adaptive Weight Disentanglement Language models are super mario: Absorbing abilities from homologous models as a free lunch

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:15.838718Z

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Observation 0aae24c6-4228-40f1-a7d3-a5cf9a7f48f8 · outbound

This paper cites Reading digits in natural images with unsuper- vised feature learning.

Multi-Task Model Merging via Adaptive Weight Disentanglement Reading digits in natural images with unsuper- vised feature learning

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:15.829571Z

Source-reported events for the cited work

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Observation 95dd5c97-f0f3-4849-90ba-d10f533dc947 · outbound

This paper cites Contin- ual learning of context-dependent processing in neural net- works.

Multi-Task Model Merging via Adaptive Weight Disentanglement Contin- ual learning of context-dependent processing in neural net- works

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:15.820392Z

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Observation 5caf2ea4-d398-46db-955a-35dc8ae1ab95 · outbound

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Multi-Task Model Merging via Adaptive Weight Disentanglement Unresolved cited work

Reference 47

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Observation 18aeaa59-1e62-44cf-a40c-af9883895962 · outbound

This paper cites Calculate Resources and Environment.

Multi-Task Model Merging via Adaptive Weight Disentanglement Calculate Resources and Environment

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T11:05:15.802414Z

Source-reported events for the cited work

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Observation 54a865bd-4fbc-4917-af57-2dc5535dd32e · outbound

This paper cites Performance on ViT-B/16 Table 4 presents the performance of various merging meth- ods applied to ViT-B/16.

Multi-Task Model Merging via Adaptive Weight Disentanglement Performance on ViT-B/16 Table 4 presents the performance of various merging meth- ods applied to ViT-B/16

Reference 49

Resolution: malformed identifier; raw_fallback, observed 2026-08-12T11:05:15.792878Z

Source-reported events for the cited work

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

Pith citing papers

Observation b9abf6f2-7360-4e2c-8a5e-ce60f2a4984c · 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 Multi-Task Model Merging via Adaptive Weight Disentanglement

Reference 260

Resolution: verified exact; arxiv_id, observed 2026-05-17T22:16:04.783864Z

Source-reported events for the cited work

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

Observation f6381a1a-1a8c-423a-8b4f-d76154386d0d · inbound

How to Merge Your Multimodal Models Over Time? cites this paper.

How to Merge Your Multimodal Models Over Time? Multi-Task Model Merging via Adaptive Weight Disentanglement

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-11T19:24:43.601245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb2dadad-3c63-4805-be1a-e310fa9c060c · inbound

Modeling Multi-Task Model Merging as Adaptive Projective Gradient Descent cites this paper.

Modeling Multi-Task Model Merging as Adaptive Projective Gradient Descent Multi-Task Model Merging via Adaptive Weight Disentanglement

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-10T22:38:48.743220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd60ba66-56bf-4a1b-bbb3-67faf2827888 · inbound

Merging Models on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging cites this paper.

Merging Models on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging Multi-Task Model Merging via Adaptive Weight Disentanglement

Reference 2010

Resolution: unresolved; no resolver link, observed 2026-08-10T20:03:11.230419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77dde7e8-deb1-4bc6-88a9-c84577022529 · inbound

Decouple and Orthogonalize: A Data-Free Framework for LoRA Merging cites this paper.

Decouple and Orthogonalize: A Data-Free Framework for LoRA Merging Multi-Task Model Merging via Adaptive Weight Disentanglement

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-07T15:18:16.048377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02e018f8-4f26-4546-ac24-136f8cb24e7e · inbound

Understanding and Enforcing Weight Disentanglement in Task Arithmetic cites this paper.

Understanding and Enforcing Weight Disentanglement in Task Arithmetic Multi-Task Model Merging via Adaptive Weight Disentanglement

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:36:36.485713Z

Source-reported events for the cited work

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

Observation 9f303378-2cb1-4b38-963e-0601f83672e0 · inbound

Memory Grafting: Scaling Language Model Pre-training via Offline Conditional Memory cites this paper.

Memory Grafting: Scaling Language Model Pre-training via Offline Conditional Memory Multi-Task Model Merging via Adaptive Weight Disentanglement

Reference 52

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:49:40.735723Z

Source-reported events for the cited work

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

Observation 2dcf83e3-7f94-4e42-89ed-bc396851a153 · inbound

When Model Merging Breaks Routing: Training-Free Calibration for MoE cites this paper.

When Model Merging Breaks Routing: Training-Free Calibration for MoE Multi-Task Model Merging via Adaptive Weight Disentanglement

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T01:36:25.372527Z

Source-reported events for the cited work

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

Observation a1fe8fdc-893d-4e6b-b3aa-c286f19ac7b3 · inbound

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

PACT: Preserving Anchored Cores in Task-vectors for Model Merging Multi-Task Model Merging via Adaptive Weight Disentanglement

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-07-03T23:39:03.964781Z

Source-reported events for the cited work

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

Observation 95aab0c1-624a-4763-831c-ca5b9b057b08 · inbound

Learning to Recover Task Experts from a Multi-Task Merged Model cites this paper.

Learning to Recover Task Experts from a Multi-Task Merged Model Multi-Task Model Merging via Adaptive Weight Disentanglement

Reference 97

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T13:39:51.041245Z

Source-reported events for the cited work

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

Observation 3b058864-c054-496e-9cb3-a9b4248e25b2 · inbound

SAFE-Merge: Data-Free Continual Model Merging with General Knowledge Preservation cites this paper.

SAFE-Merge: Data-Free Continual Model Merging with General Knowledge Preservation Multi-Task Model Merging via Adaptive Weight Disentanglement

Reference 230

Resolution: unresolved; no resolver link, observed 2026-08-06T00:32:46.610154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 067e8b91-3bc9-4868-9b9f-a9a3a26a9bb7 · inbound

CABS+: Efficient and Scalable Model Merging via Conflict-Aware Sparsification and Adaptive Weight Allocation cites this paper.

CABS+: Efficient and Scalable Model Merging via Conflict-Aware Sparsification and Adaptive Weight Allocation Multi-Task Model Merging via Adaptive Weight Disentanglement

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T22:15:10.490081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.