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Paper Citation Record · LEDGER

Bridging the Generalization Gap in Adverse Weather Segmentation: A Training Recipe Perspective

As of 10 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2605.27962.

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

pith.paper-citation-record.v1
2605.27962 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T13:33:21.071580Z

measured 14 of 14 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

14 of 14 outbound references displayed

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  • verified fuzzy0
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  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f06ea1fe-55ce-4e5a-ae72-2ee46730f2d2 · outbound

This paper cites AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition.

Bridging the Generalization Gap in Adverse Weather Segmentation: A Training Recipe Perspective AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition

Reference 1

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verified exact
arxiv_id, observed 2026-06-29T13:33:27.627831Z

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.

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Observation 3b22b670-28e9-4cd6-8c2d-316ae976e58d · outbound

This paper cites Adapting semantic seg- mentation models via structured domain adaptation.

Bridging the Generalization Gap in Adverse Weather Segmentation: A Training Recipe Perspective Adapting semantic seg- mentation models via structured domain adaptation

Reference 2

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Unavailable: canonical work link unavailable.

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Observation c4cc9444-567f-4720-b1b1-881bc8fbef20 · outbound

This paper cites Mmsegmentation: Openmm- lab semantic segmentation toolbox and benchmark.

Bridging the Generalization Gap in Adverse Weather Segmentation: A Training Recipe Perspective Mmsegmentation: Openmm- lab semantic segmentation toolbox and benchmark

Reference 3

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Observation f8d310bc-0090-4000-b979-92536ef4a793 · outbound

This paper cites Segman: Omni-scale context modeling with state space models and local attention for semantic segmentation.

Bridging the Generalization Gap in Adverse Weather Segmentation: A Training Recipe Perspective Segman: Omni-scale context modeling with state space models and local attention for semantic segmentation

Reference 4

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no resolver link, observed 2026-06-29T13:33:21.071580Z

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Observation 47ab44d8-cc0f-4706-b3de-8d0efd06cdc7 · outbound

This paper cites All-weather deep outdoor lighting estima- tion.

Bridging the Generalization Gap in Adverse Weather Segmentation: A Training Recipe Perspective All-weather deep outdoor lighting estima- tion

Reference 5

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Observation 91a3a33f-8c7e-403f-a149-b2c2e687819a · outbound

This paper cites Cycada: Cycle-consistent adversarial domain adaptation.

Bridging the Generalization Gap in Adverse Weather Segmentation: A Training Recipe Perspective Cycada: Cycle-consistent adversarial domain adaptation

Reference 6

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Unavailable: canonical work link unavailable.

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Observation 7af7c3e0-46b0-4296-b97b-0dc4839c464d · outbound

This paper cites Parameter-efficient transfer learning for nlp.

Bridging the Generalization Gap in Adverse Weather Segmentation: A Training Recipe Perspective Parameter-efficient transfer learning for nlp

Reference 7

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-29T13:33:21.071580Z digest=sha256:31499ba701ece13648fe99f3fb1041eff31b5d42505221e24e0b03e0a1bb9ca2

Observation 29dba9b9-d61c-427b-b3c3-d8759e233926 · outbound

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

Bridging the Generalization Gap in Adverse Weather Segmentation: A Training Recipe Perspective LoRA: Low-Rank Adaptation of Large Language Models

Reference 8

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local_arxiv, observed 2026-06-29T13:33:27.623994Z

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.

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Observation c86fe141-30fe-4401-b6d2-0b4232415555 · outbound

This paper cites The Power of Scale for Parameter-Efficient Prompt Tuning.

Bridging the Generalization Gap in Adverse Weather Segmentation: A Training Recipe Perspective The Power of Scale for Parameter-Efficient Prompt Tuning

Reference 9

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verified exact
local_arxiv, observed 2026-06-29T13:33:27.621224Z

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.

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Observation a1bd37e1-104f-4166-bf6e-896ef8a10abc · outbound

This paper cites VMamba: Visual State Space Model.

Bridging the Generalization Gap in Adverse Weather Segmentation: A Training Recipe Perspective VMamba: Visual State Space Model

Reference 10

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verified exact
local_arxiv, observed 2026-06-29T13:33:27.624394Z

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.

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Observation cd83e220-0250-45ae-9e82-c619c8902988 · outbound

This paper cites Foggy cityscapes: Semantic segmentation of foggy images.

Bridging the Generalization Gap in Adverse Weather Segmentation: A Training Recipe Perspective Foggy cityscapes: Semantic segmentation of foggy images

Reference 11

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Unavailable: canonical work link unavailable.

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Observation b3a87b50-8099-482a-8ab2-dedf140ffaf4 · outbound

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

Bridging the Generalization Gap in Adverse Weather Segmentation: A Training Recipe Perspective Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time

Reference 12

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-29T13:33:21.071580Z digest=sha256:32ad69ff1dd994364257b65b37e46865ff58d414bc6139a7767b6e30c67aedf5

Observation 545babb8-3e55-4361-a376-ef499ec9f2e1 · outbound

This paper cites Segformer: Simple and effi- cient design for semantic segmentation with transformers.

Bridging the Generalization Gap in Adverse Weather Segmentation: A Training Recipe Perspective Segformer: Simple and effi- cient design for semantic segmentation with transformers

Reference 13

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unresolved
no resolver link, observed 2026-06-29T13:33:21.071580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1ae4bc6e-8530-45f4-83b9-d0a50c011119 · outbound

This paper cites Scene parsing through ade20k dataset.

Bridging the Generalization Gap in Adverse Weather Segmentation: A Training Recipe Perspective Scene parsing through ade20k dataset

Reference 14

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unresolved
no resolver link, observed 2026-06-29T13:33:21.071580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.