Paper Citation Record · LEDGER

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging

As of 19 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 1 inbound Pith citation observation for arXiv:2506.18135.

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

pith.paper-citation-record.v1
2506.18135 v1

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:59:24.743614Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T13:36:47.810747Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T04:47:38.611690Z

Reference resolution

64 of 64 outbound references displayed

verified exact0
verified fuzzy27
unresolved35
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b881c488-ddc4-44c9-b91c-6420d5ea0c46 · outbound

This paper cites an unresolved cited work.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.527668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95759e88-99e7-467f-ae77-5eda7c1110cb · outbound

This paper cites Remote sensing image scene classification: Benchmark and state of the art.Proceedings of the IEEE, 105(10):1865–1883, 2017.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Remote sensing image scene classification: Benchmark and state of the art.Proceedings of the IEEE, 105(10):1865–1883, 2017

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.531853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a36e8f27-bc50-460f-81de-aea4cde83b2f · outbound

This paper cites On lazy training in differentiable programming.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging On lazy training in differentiable programming

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.625141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a4df86c2-435a-479f-bedf-6cb85260fc69 · outbound

This paper cites Describing textures in the wild.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Describing textures in the wild

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.538975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2ba055a-8ae0-4441-9413-1356a23a846e · outbound

This paper cites Dolan and Chris Brockett.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Dolan and Chris Brockett

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.542597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79899618-308c-4ba2-bc69-bcac54330141 · outbound

This paper cites A survey on ensemble learning.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging A survey on ensemble learning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.605861Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 27d7f53e-874b-4399-8eda-a568dbe19127 · outbound

This paper cites Essentially no barriers in neural network energy landscape.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Essentially no barriers in neural network energy landscape

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.595203Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a5d37f72-ee4b-4618-b1a9-42c5e2003b95 · outbound

This paper cites Parameter competition balancing for model merging.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Parameter competition balancing for model merging

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.584323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2a2c1752-eef2-46b0-90fa-8c7c4fbbbbeb · outbound

This paper cites The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging The Role of Permutation Invariance in Linear Mode Connectivity of Neural Networks

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.555916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f02d37fc-82b8-4eb3-b53e-e679d4bc6f84 · outbound

This paper cites Linear mode connectivity and the lottery ticket hypothesis.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Linear mode connectivity and the lottery ticket hypothesis

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.559521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02f19c16-005c-4bf1-980e-4fadf93f6f40 · outbound

This paper cites Daniel Freeman and Joan Bruna.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Daniel Freeman and Joan Bruna

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.566793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 98cc24bc-730e-4de6-93a6-498489ee55a7 · outbound

This paper cites Loss surfaces, mode connectivity, and fast ensembling of dnns.Advances in neural information processing systems, 31, 2018.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Loss surfaces, mode connectivity, and fast ensembling of dnns.Advances in neural information processing systems, 31, 2018

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.565736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55a6629a-bb25-420c-b454-95421b8fdf52 · outbound

This paper cites The third PASCAL recognizing textual entailment challenge.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging The third PASCAL recognizing textual entailment challenge

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.448806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 91583ea1-f825-4a3f-a401-26b32fb2280e · outbound

This paper cites An empirical evaluation of the t-sne algorithm for data visualization in structural engineering.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging An empirical evaluation of the t-sne algorithm for data visualization in structural engineering

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.572208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f1366bc-a4a3-494d-b0f1-da15624a7d5a · outbound

This paper cites an unresolved cited work.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Unresolved cited work

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.575284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 620820b9-32ad-4d0e-bc49-cc1daecee988 · outbound

This paper cites EMR-merging: Tuning- free high-performance model merging.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging EMR-merging: Tuning- free high-performance model merging

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.578540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3675e1e4-4cf1-41db-aa64-0e4e250008ff · outbound

This paper cites Editing models with task arithmetic.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Editing models with task arithmetic

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.431326Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 930f7eef-bcb4-4046-b0f6-085a6786f187 · outbound

This paper cites Neural tangent kernel: Convergence and generalization in neural networks.Advances in neural information processing systems, 31, 2018.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Neural tangent kernel: Convergence and generalization in neural networks.Advances in neural information processing systems, 31, 2018

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.584835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a1bddece-ad31-4419-b2a8-809c4475a9bc · outbound

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

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Dataless knowledge fusion by merging weights of language models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.587879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a27c4b4d-7c2c-41a4-bc68-fa9698c6b7b9 · outbound

This paper cites Scalable optimal transport methods in machine learning: A contemporary survey.IEEE transactions on pattern analysis and machine intelligence, 2024.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Scalable optimal transport methods in machine learning: A contemporary survey.IEEE transactions on pattern analysis and machine intelligence, 2024

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.405197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7bf8e926-4310-45d6-89c8-3f98a0b0bc84 · outbound

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

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging 3d object representations for fine-grained categorization

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.393823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 93c2c802-2f2e-4037-a17d-9876e58c9999 · outbound

This paper cites Explaining landscape connectivity of low-cost solutions for multilayer nets.Advances in neural information processing systems, 32, 2019.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Explaining landscape connectivity of low-cost solutions for multilayer nets.Advances in neural information processing systems, 32, 2019

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.382483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3a130816-4365-4933-b810-d535d063d68b · outbound

This paper cites The mnist database of handwritten digits.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging The mnist database of handwritten digits

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.604946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3238a063-2f46-4882-8d13-defcae933bf0 · outbound

This paper cites Understanding the loss surface of neural networks for binary classification.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Understanding the loss surface of neural networks for binary classification

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.365692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0fa9cee7-6d3a-4f44-bbd0-0128f46a7a12 · outbound

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

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Twin-merging: Dynamic integration of modular expertise in model merging

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.356011Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f4328586-6868-4471-bbb7-607ecf644bd0 · outbound

This paper cites Merging models with fisher-weighted averaging.Advances in Neural Information Processing Systems, 35:17703–17716, 2022.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Merging models with fisher-weighted averaging.Advances in Neural Information Processing Systems, 35:17703–17716, 2022

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.615123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f98ca31e-9357-4db8-a150-3b074181c84e · outbound

This paper cites an unresolved cited work.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Unresolved cited work

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.618373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 05acc8dd-e4b6-4fad-9b35-91393f4901e0 · outbound

This paper cites On cross-layer alignment for model fusion of heterogeneous neural networks.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging On cross-layer alignment for model fusion of heterogeneous neural networks

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.334007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5217d2b4-7fff-4ed3-8385-31554bc4f7f7 · outbound

This paper cites On connected sublevel sets in deep learning.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging On connected sublevel sets in deep learning

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.324105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9c49b893-0d00-4b3d-ba46-48e9dfd095cc · outbound

This paper cites On the loss landscape of a class of deep neural networks with no bad local valleys.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging On the loss landscape of a class of deep neural networks with no bad local valleys

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.313921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 124f532e-81ec-4004-bc06-3ed555095cf6 · outbound

This paper cites Task arithmetic in the tangent space: Improved editing of pre-trained models.Advances in Neural Information Processing Systems, 36, 2024.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Task arithmetic in the tangent space: Improved editing of pre-trained models.Advances in Neural Information Processing Systems, 36, 2024

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.303927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c070fb0d-0496-43cb-827b-6de4afecd466 · outbound

This paper cites Qwen2.5 technical report, 2025.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Qwen2.5 technical report, 2025

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.634782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dba4a5e3-6162-49bc-a364-103c208f6efd · outbound

This paper cites Language models are unsupervised multitask learners.OpenAI blog, 1(8):9, 2019.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Language models are unsupervised multitask learners.OpenAI blog, 1(8):9, 2019

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.638171Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e18bc5f9-c7e5-4162-8a6c-6a4b21c74ace · outbound

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

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Learning transferable visual models from natural language supervision

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.641591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c5f8bb2-a0ba-4285-bef1-7aeb9540ecc1 · outbound

This paper cites SQuAD: 100,000+ questions for machine comprehension of text.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging SQuAD: 100,000+ questions for machine comprehension of text

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.644819Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aa7354f2-b2c7-4cfe-85b5-d3598e335112 · outbound

This paper cites First quora dataset release: question pairs (2017).

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging First quora dataset release: question pairs (2017)

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.275226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d96ca076-e201-479c-8798-54920558dc8f · outbound

This paper cites Outrageously large neural networks: The sparsely-gated mixture-of-experts layer.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Outrageously large neural networks: The sparsely-gated mixture-of-experts layer

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.652254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ffb3708-88f4-460e-ab1e-1b512b025316 · outbound

This paper cites Relative entropic optimal transport: a (prior-aware) matching perspective to (unbalanced) classification.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Relative entropic optimal transport: a (prior-aware) matching perspective to (unbalanced) classification

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.259133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 960d79c0-939b-4bab-b3ff-a01b9a59aab1 · outbound

This paper cites OT-CLIP: Understanding and generalizing CLIP via optimal transport.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging OT-CLIP: Understanding and generalizing CLIP via optimal transport

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.248641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e8dbb5c3-884c-42b1-b89e-71f1abaf5e1c · outbound

This paper cites Double-bounded optimal transport for advanced clustering and classification.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Double-bounded optimal transport for advanced clustering and classification

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.238240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b47be9d5-0f29-465c-9fc3-07b453f42ca4 · outbound

This paper cites Model fusion via optimal transport.Advances in Neural Information Processing Systems, 33:22045–22055, 2020.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Model fusion via optimal transport.Advances in Neural Information Processing Systems, 33:22045–22055, 2020

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.666038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49b1bd9c-067a-4ca5-b747-071341072eaf · outbound

This paper cites Manning, Andrew Ng, and Christopher Potts.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Manning, Andrew Ng, and Christopher Potts

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.669606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c37e3549-64c8-4707-88da-f5124a3d9d52 · outbound

This paper cites The german traffic sign recognition benchmark: A multi-class classification competition.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging The german traffic sign recognition benchmark: A multi-class classification competition

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.673011Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53e7439d-e5f5-4b56-8622-bd7c9fee9a66 · outbound

This paper cites Fusionbench: A comprehensive benchmark of deep model fusion, 2024.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Fusionbench: A comprehensive benchmark of deep model fusion, 2024

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.216089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1de962a3-63ba-4403-92b9-7d542d511a68 · outbound

This paper cites Merging multi-task models via weight-ensembling mixture of experts.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Merging multi-task models via weight-ensembling mixture of experts

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.680190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 628a2ddb-1d74-432b-9fb8-874e4f4dc30a · outbound

This paper cites Bandeira, and Joan Bruna.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Bandeira, and Joan Bruna

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.199848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e2d681ce-c0b2-49f0-909e-35c2bb5bdad9 · outbound

This paper cites Springer, 2008.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Springer, 2008

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.687088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6b0d53ae-240e-447f-a96f-f29945935ffe · outbound

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

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging GLUE: A multi-task benchmark and analysis platform for natural language understanding

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.690489Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 28f36ade-510c-41c0-ae2f-0d492f6c861e · outbound

This paper cites Mergenas: Merge operations into one for differentiable architecture search.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Mergenas: Merge operations into one for differentiable architecture search

Reference 49

Resolution: malformed identifier; no resolver link, observed 2026-08-15T18:59:24.693690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ab539a9-5310-410d-8e68-248ebb896322 · outbound

This paper cites an unresolved cited work.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Unresolved cited work

Reference 50

Resolution: malformed identifier; no resolver link, observed 2026-08-15T18:59:24.697070Z

Source-reported events for the cited work

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Observation ac05b909-1de4-4a64-9481-e0eecc005ca7 · outbound

This paper cites A broad-coverage challenge corpus for sentence understanding through inference.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging A broad-coverage challenge corpus for sentence understanding through inference

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.183554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c4fd0917-ec4e-4ec0-9319-b0b3e4bfa806 · outbound

This paper cites an unresolved cited work.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Unresolved cited work

Reference 52

Resolution: unresolved; raw_fallback, observed 2026-08-15T18:59:25.172906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 95f34d87-00ba-4747-922c-3c5c73c48ee0 · outbound

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

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Model soups: aver- aging weights of multiple fine-tuned models improves accuracy without increasing inference time

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.711326Z

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Observation be0a9048-2b57-4e72-b47c-feeea43a2d42 · outbound

This paper cites Ehinger, James Hays, Antonio Torralba, and Aude Oliva.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Ehinger, James Hays, Antonio Torralba, and Aude Oliva

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.714561Z

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Observation df0c1fb6-0e7a-4a39-ae48-7019069ee1dc · outbound

This paper cites Training-free Heterogeneous Model Merging.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Training-free Heterogeneous Model Merging

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.718726Z

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Observation 332c599e-8d5e-49ce-8b2c-c40a9e109276 · outbound

This paper cites Ties-merging: Resolving interference when merging models.Advances in Neural Information Processing Systems, 36, 2024.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Ties-merging: Resolving interference when merging models.Advances in Neural Information Processing Systems, 36, 2024

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.722389Z

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Observation 924afdca-3a89-4ac9-959b-c0c49f9c2f98 · outbound

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

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Representation surgery for multi-task model merging

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.149787Z

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Observation ae5116f5-69cd-4af7-9b53-07b5da037469 · outbound

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

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Adamerging: Adaptive model merging for multi-task learning

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.729445Z

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Observation 78ccc813-3344-4565-9454-22ea93d8f198 · outbound

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

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Language models are super mario: Absorbing abilities from homologous models as a free lunch

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.132208Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6daa6cd5-4674-47f2-8cb4-13a2ec432f37 · outbound

This paper cites Model Assembly Learning with Heterogeneous Layer Weight Merging.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Model Assembly Learning with Heterogeneous Layer Weight Merging

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.736489Z

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Observation 2129cb01-a8e7-4d91-8a25-f4be83e7204d · outbound

This paper cites Going beyond linear mode connectivity: The layerwise linear feature connectivity.Advances in Neural Information Processing Systems, 36:60853–60877, 2023.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Going beyond linear mode connectivity: The layerwise linear feature connectivity.Advances in Neural Information Processing Systems, 36:60853–60877, 2023

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.121244Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 63cc0a1c-0b0d-424b-a5f4-4bfdf016fc0c · outbound

This paper cites On the emergence of cross-task linearity in pretraining-finetuning paradigm.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging On the emergence of cross-task linearity in pretraining-finetuning paradigm

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T18:59:25.110202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e130a388-9edd-4a2f-9e7d-798675f731d9 · outbound

This paper cites an unresolved cited work.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging Unresolved cited work

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.598047Z

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Observation 1b205b03-9dd3-451d-8df9-2d872f0a8ba5 · outbound

This paper cites doi: 10.18653/v1/N18-1101.

SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging doi: 10.18653/v1/N18-1101

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-15T18:59:24.704429Z

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Pith citing papers

Observation b8d9fdf6-92c9-493f-9bff-8c8876983455 · inbound

SSR-Merge: Subspace Signal Routing for Training-Free LoRA Merging in Diffusion Models cites this paper.

SSR-Merge: Subspace Signal Routing for Training-Free LoRA Merging in Diffusion Models SE-Merging: A Self-Enhanced Approach for Dynamic Model Merging

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-03T04:47:38.613093Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.