Paper Citation Record · LEDGER

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation

As of 10 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2507.16736.

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

pith.paper-citation-record.v1
2507.16736 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:08:17.062076Z

measured 30 of 30 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

30 of 30 outbound references displayed

verified exact1
verified fuzzy22
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c81ad1ff-5d05-430b-831d-18f36a29a7f0 · outbound

This paper cites Fully convolutional networks for semantic segmentation,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Fully convolutional networks for semantic segmentation,

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:13.650371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f1a48b6-22f6-464d-a953-6e1ab154c8e1 · outbound

This paper cites Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Deeplab: Semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected crfs,

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:13.710978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7445a60f-14c8-40c7-b6a6-7d94435bd7e7 · outbound

This paper cites Ssformer: A lightweight transformer for semantic segmentation,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Ssformer: A lightweight transformer for semantic segmentation,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:21.731144Z

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.

Observation 8c2e478f-fe36-4d36-bfae-a9e426f5907e · outbound

This paper cites Prior guided feature enrichment network for few-shot segmentation,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Prior guided feature enrichment network for few-shot segmentation,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:21.461648Z

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.

Observation c9d6a438-8bee-4f96-bab4-5ed10c3801eb · outbound

This paper cites Hypercorrelation squeeze for few-shot segmentation,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Hypercorrelation squeeze for few-shot segmentation,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:21.207291Z

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.

Observation 470a9116-505c-4523-bf54-037aa2094cd4 · outbound

This paper cites Adapt before comparison: A new perspective on cross- domain few-shot segmentation,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Adapt before comparison: A new perspective on cross- domain few-shot segmentation,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:20.988459Z

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.

Observation 68a25660-8804-4a7f-bc11-c25dedfdf8fa · outbound

This paper cites Rethinking the correlation in few- shot segmentation: A buoys view,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Rethinking the correlation in few- shot segmentation: A buoys view,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:20.749193Z

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.

Observation c3e09568-7497-4f64-b70a-62ee276b9deb · outbound

This paper cites Relevant intrinsic feature enhancement network for few-shot semantic segmentation,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Relevant intrinsic feature enhancement network for few-shot semantic segmentation,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:20.515983Z

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.

Observation 24ec6da4-3dde-4fb2-8b7f-fe448f3c0776 · outbound

This paper cites Label-efficient few-shot semantic segmentation with unsupervised meta-training,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Label-efficient few-shot semantic segmentation with unsupervised meta-training,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:20.292879Z

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.

Observation ce1e5c57-8eda-4b14-afee-4ba662b06a54 · outbound

This paper cites Image segmentation using text and image prompts,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Image segmentation using text and image prompts,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:20.106833Z

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.

Observation 10846909-b4e5-4999-bad8-e9f861f9bac3 · outbound

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

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Learning transferable visual models from natural language supervision,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:14.484205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d34ab52-ae44-42c1-bd88-83bf2c3c55ff · outbound

This paper cites Extending segment anything model into auditory and temporal dimensions for audio- visual segmentation,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Extending segment anything model into auditory and temporal dimensions for audio- visual segmentation,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:19.928543Z

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.

Observation 64224bdd-3677-410a-a68a-6f13362f48b2 · outbound

This paper cites Segment anything,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Segment anything,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:14.746427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 817f5cab-4d7c-4433-8a6c-f43d3453af16 · outbound

This paper cites Languagebind: Extending video-language pretraining to n-modality by language-based semantic alignment,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Languagebind: Extending video-language pretraining to n-modality by language-based semantic alignment,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:19.789293Z

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.

Observation 7e493dcf-e4c6-4cab-9f80-cdbd46493a3d · outbound

This paper cites Panet: Few-shot image semantic segmentation with prototype alignment,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Panet: Few-shot image semantic segmentation with prototype alignment,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:19.626557Z

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.

Observation 094be2a5-984c-445e-a3a7-05fa1126b17e · outbound

This paper cites Vrp-sam: Sam with visual reference prompt,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Vrp-sam: Sam with visual reference prompt,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:19.420953Z

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.

Observation b64705f3-03f0-47b7-b223-fe8a2fc3f08d · outbound

This paper cites Matcher: Segment anything with one shot using all-purpose feature matching,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Matcher: Segment anything with one shot using all-purpose feature matching,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:19.233849Z

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.

Observation 7cc33210-c1d3-4c43-bd31-07e76f1ea9e7 · outbound

This paper cites Foreground-Covering Prototype Generation and Matching for SAM-Aided Few-Shot Segmentation.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Foreground-Covering Prototype Generation and Matching for SAM-Aided Few-Shot Segmentation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:15.309550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b8ab2bb-eaad-494b-bcda-5798a1348355 · outbound

This paper cites AudioLDM: Text-to-audio generation with latent diffusion models,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation AudioLDM: Text-to-audio generation with latent diffusion models,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:19.122718Z

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.

Observation 379df023-fa87-4537-a21e-3279786dba02 · outbound

This paper cites One-shot learning for semantic segmentation,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation One-shot learning for semantic segmentation,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:18.933211Z

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.

Observation d8ae89ae-740d-4fb2-af15-6fb78fe345e8 · outbound

This paper cites Adaptive fss: A novel few-shot segmentation framework via prototype enhancement,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Adaptive fss: A novel few-shot segmentation framework via prototype enhancement,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:18.706366Z

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.

Observation 30ec30bb-e68c-465b-a559-032603e47932 · outbound

This paper cites Holistic prototype activation for few- shot segmentation,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Holistic prototype activation for few- shot segmentation,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:18.504102Z

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.

Observation 8827c5f7-6ed4-4c79-b112-7e1733cf91eb · outbound

This paper cites Few-shot segmentation via divide-and-conquer proxies,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Few-shot segmentation via divide-and-conquer proxies,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:18.315985Z

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.

Observation 24df40e7-387e-4ba2-9fe8-9cfc109e5ccf · outbound

This paper cites The pascal visual object classes (voc) challenge,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation The pascal visual object classes (voc) challenge,

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:16.133439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71080359-fc5b-4aed-bd29-3cf45bc78890 · outbound

This paper cites Semantic contours from inverse detectors,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Semantic contours from inverse detectors,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:18.110611Z

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.

Observation 3d1d6a99-33ea-4b0f-9fa2-b9257cd0c837 · outbound

This paper cites DeepSeek-V3 Technical Report.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation DeepSeek-V3 Technical Report

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-06T15:08:16.429174Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fc785cd-ea2f-467d-a54c-e58056dfe73f · outbound

This paper cites Prompting segmentation with sound is generalizable audio-visual source localizer,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Prompting segmentation with sound is generalizable audio-visual source localizer,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:17.951139Z

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.

Observation 4109579b-079f-4198-a5e0-a67c24700786 · outbound

This paper cites Audio-visual segmentation,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Audio-visual segmentation,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:17.694873Z

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.

Observation 6a2c7880-38cc-4276-a322-e1dcd709ac30 · outbound

This paper cites Audio-visual segmentation with semantics,.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation Audio-visual segmentation with semantics,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T15:08:17.566417Z

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.

Observation a88f623c-48e8-465d-aa97-1869e8388663 · outbound

This paper cites AVESFormer: Efficient Transformer Design for Real-Time Audio-Visual Segmentation.

DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation AVESFormer: Efficient Transformer Design for Real-Time Audio-Visual Segmentation

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-08-06T15:08:17.303096Z

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.

Pith citing papers

No inbound Pith citation observations are available.