Pith. sign in

Paper Citation Record · LEDGER

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation

As of 17 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2509.13907.

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

pith.paper-citation-record.v1
2509.13907 v3

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T16:33:37.289633Z

measured 38 of 38 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

38 of 38 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved38
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation dd5a46dc-231a-42b3-b2ac-9e76fefc10fd · outbound

This paper cites Correlations Are Ruining Your Gradient Descent.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Correlations Are Ruining Your Gradient Descent

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:32.929629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:32.929629Z digest=sha256:deb1265dc60884761ba2c5bf4d3fcc7b48253d788d68a6eb9ba78686deffbcb3

Observation 940e7d51-e15b-4eaf-b788-2f08067532b3 · outbound

This paper cites Re- thinking few-shot 3d point cloud semantic segmentation.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Re- thinking few-shot 3d point cloud semantic segmentation

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:33.077467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:33.077467Z digest=sha256:612ae50c468a740707c234a58e829fadb63b52a2bc2e374778fd45b79eb236bc

Observation 5727f87f-0153-4bf3-94eb-8ca73ca69ea7 · outbound

This paper cites Multimodality helps few-shot 3d point cloud semantic seg- mentation.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Multimodality helps few-shot 3d point cloud semantic seg- mentation

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:33.173429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:33.173429Z digest=sha256:b6807ed35581fe7a7f133b15aeab6ed0cea50f4e5f0318b528dd9a48efe938d2

Observation 20f3e05f-1428-4f79-8196-c6089863f23b · outbound

This paper cites 3d seman- tic parsing of large-scale indoor spaces.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation 3d seman- tic parsing of large-scale indoor spaces

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:33.318847Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:33.318847Z digest=sha256:92b7f3f2a36c535a72ce5b8487d85b064d564af5a7a1bde6bd754848c0716ab6

Observation 57f971ea-ed85-476f-bdf5-8a4278bfe824 · outbound

This paper cites independent components.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation independent components

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:33.477149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:33.477149Z digest=sha256:f8f7380f5ad3dae8c0d87b02f129d155ac9716d0ba42d0998aac3cf84876636a

Observation cf4e6de8-2bea-4c52-b809-51e2db621b31 · outbound

This paper cites Deep learning on 3d semantic segmentation: A detailed review.Remote Sensing, 17(2):298, 2025.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Deep learning on 3d semantic segmentation: A detailed review.Remote Sensing, 17(2):298, 2025

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:33.612160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:33.612160Z digest=sha256:79e2440d663c6e2e8c0a3cf274ebbb3f5735c384cc1731b56185fd7190ab8eca

Observation b2e73c8a-45c7-4ef1-ba6d-38cb22bf8f27 · outbound

This paper cites End-to- end object detection with transformers.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation End-to- end object detection with transformers

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:33.798896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:33.798896Z digest=sha256:13ff048ac27cf04d173672a95d5b144b7fb9e87e17b67b3f0f6f2aaa3c374bf2

Observation 5d3a9c22-da02-42b7-9da9-73737c5c0a29 · outbound

This paper cites Masked-attention mask transformer for universal image segmentation.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Masked-attention mask transformer for universal image segmentation

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:33.952246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:33.952246Z digest=sha256:51f590a27107b583f3eecfb617fdd44633e55c1e33c4198a83c0b4c32f13595b

Observation 9ef1e462-ac9b-4b5f-ab1b-14d50ef09e80 · outbound

This paper cites Scannet: Richly-annotated 3d reconstructions of indoor scenes.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Scannet: Richly-annotated 3d reconstructions of indoor scenes

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:34.090983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:34.090983Z digest=sha256:ea8d63003d277252e53dd74e3c8eb7fd4231b8f3d5200a0e57fad2f2616d2d67

Observation e2a6ffb2-8cb8-4a1e-8247-9eef625206ce · outbound

This paper cites Batch normalization prov- ably avoids ranks collapse for randomly initialised deep net- works.Advances in Neural Information Processing Systems, 33:18387–18398, 2020.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Batch normalization prov- ably avoids ranks collapse for randomly initialised deep net- works.Advances in Neural Information Processing Systems, 33:18387–18398, 2020

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:34.237787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:34.237787Z digest=sha256:3ffc542a9190028a740910abcf692f31fc4a2b3591e6d46373dfee7b478395cf

Observation 80a894d0-1683-4483-b0fe-6ca433dfc9c8 · outbound

This paper cites Attention is not all you need: Pure attention loses rank dou- bly exponentially with depth.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Attention is not all you need: Pure attention loses rank dou- bly exponentially with depth

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:34.399585Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:34.399585Z digest=sha256:924ffa7634186f015f696cad1c41c628c5db1916f17f1054abc084a285898d26

Observation 91d68125-1c2f-4f52-bf35-5c1fc4d604dc · outbound

This paper cites Self- support few-shot semantic segmentation.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Self- support few-shot semantic segmentation

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:34.570045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:34.570045Z digest=sha256:904c266ac8101dc794744df234d14cf39f25c82fa9bdcac5e274bff98792a197

Observation 524db85c-df3f-4177-a508-cd0c2dad9952 · outbound

This paper cites Prototype adaption and projection for few- and zero-shot 3d point cloud semantic segmentation.IEEE Transactions on Image Processing, 2023.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Prototype adaption and projection for few- and zero-shot 3d point cloud semantic segmentation.IEEE Transactions on Image Processing, 2023

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:34.693860Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:34.693860Z digest=sha256:8eb24f4f025f0744b1e497d32a496b0faf017dc025a8acfadb60af487c00d2c2

Observation 4b412d98-4e1d-452b-b06d-ca09299f1b86 · outbound

This paper cites Decorre- lated batch normalization.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Decorre- lated batch normalization

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:34.861539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:34.861539Z digest=sha256:50bdedad2c14a0d71e17e8f2f66cac62baa5f4abe9a6d2c43c38ea83b421dba1

Observation e14cbe90-5a3e-4e33-8e93-0bc15c8b934a · outbound

This paper cites Revealing the Dark Secrets of BERT.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Revealing the Dark Secrets of BERT

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:35.024528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:35.024528Z digest=sha256:097aad00e1ce2d249f230cc8e71dbe9bea7baebf9f0800fb9a0b7f1955f97a58

Observation 4278e6d7-a031-4c0c-9edd-d05e11df5a3a · outbound

This paper cites Stratified trans- former for 3d point cloud segmentation.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Stratified trans- former for 3d point cloud segmentation

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:35.123831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:35.123831Z digest=sha256:12697ee468d1f64b2d17527995180ac9f50a4141e0772923747f4ecdba79bc72

Observation c936d96d-b918-419d-81bf-4733db7c206c · outbound

This paper cites Samplenet: Differentiable point cloud sampling.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Samplenet: Differentiable point cloud sampling

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:35.246908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:35.246908Z digest=sha256:800a6d8ed6193134a0fc8d40d60d770a6416f30ef5723b772584e7bf5a13abce

Observation b395ea1a-94d3-4a09-9cb6-2b4ad3d491ff · outbound

This paper cites Activating self- attention for multi-scene absolute pose regression.Advances in Neural Information Processing Systems, 37:38508–38529,.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Activating self- attention for multi-scene absolute pose regression.Advances in Neural Information Processing Systems, 37:38508–38529,

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:35.407940Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:35.407940Z digest=sha256:1a8b7764019abc3aac7ea439fe3a3ff6bacfb19335af5725f9698fc5362129a9

Observation 4bec39e7-8d49-4221-870a-b05b2a0a1971 · outbound

This paper cites Temporal alignment-free video matching for few- shot action recognition.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Temporal alignment-free video matching for few- shot action recognition

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:35.512960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:35.512960Z digest=sha256:3b97fe364cd0cd020a60bdc29fe38dd737f29baca2eb8e77b3fe2299b957967d

Observation 96b6d606-8b7f-4034-b03b-8222c3e3a08d · outbound

This paper cites Localization and expansion: A decoupled frame- work for point cloud few-shot semantic segmentation.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Localization and expansion: A decoupled frame- work for point cloud few-shot semantic segmentation

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:35.612715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:35.612715Z digest=sha256:b82d89bb8d6e63a0ba966b1d64a00a27da320f6e43be6ce0c8c66e154b47e280

Observation 0e53844c-1166-4142-a7a6-96beda73203a · outbound

This paper cites Masked dis- crimination for self-supervised learning on point clouds.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Masked dis- crimination for self-supervised learning on point clouds

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:35.726838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:35.726838Z digest=sha256:3f1a616d8217e429ca1b6b91b09c286a05a4a48ac228c2f5b311642330f42491

Observation 43c2feb5-fd85-4283-8340-b8e58fd394fb · outbound

This paper cites Part-aware prototype network for few-shot semantic segmentation.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Part-aware prototype network for few-shot semantic segmentation

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:35.897857Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:35.897857Z digest=sha256:e674dbbbeef0524ae2cbda28dbaa359619c5dfa917394dc5fce8b4d3fb8442cb

Observation 089ac701-0232-47d3-90cc-4b964b00a0dd · outbound

This paper cites An end-to- end transformer model for 3d object detection.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation An end-to- end transformer model for 3d object detection

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:36.075986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:36.075986Z digest=sha256:c026e7d005f6dabe8c765ee674579eb7f8496a3ad93e8fe8c99d605e3b1523a9

Observation 2fdf0b76-a385-4ae7-bc33-6b800379d5d0 · outbound

This paper cites Boosting few-shot 3d point cloud segmentation via query-guided enhancement.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Boosting few-shot 3d point cloud segmentation via query-guided enhancement

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:36.233462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:36.233462Z digest=sha256:3aa772d0e737b3807862c94c5bb0df67904d9e657e6f72a5f5cb38fcb0512041

Observation d5f4d46a-b1d7-4c65-a1fa-562bd99eec3b · outbound

This paper cites How does batch normalization help optimiza- tion?Advances in neural information processing systems, 31, 2018.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation How does batch normalization help optimiza- tion?Advances in neural information processing systems, 31, 2018

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:36.387594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:36.387594Z digest=sha256:f660f24b3a6c9e003def4f66ef44f0150c4f3c0eb40efa3b6fb7d01b0063c9ac

Observation 8d00d220-cff9-449b-986e-9bcdb3d99f76 · outbound

This paper cites Mask3D: Mask Transformer for 3D Semantic Instance Segmentation.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Mask3D: Mask Transformer for 3D Semantic Instance Segmentation

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:36.439735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:36.439735Z digest=sha256:e61c79b62809377bbfba0aa43973540a6b64c3dd293d08fe1596928e14011af9

Observation f6cc9774-fde1-407b-9141-9390c2fcc189 · outbound

This paper cites Prototypical networks for few-shot learning.Advances in neural informa- tion processing systems, 30, 2017.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Prototypical networks for few-shot learning.Advances in neural informa- tion processing systems, 30, 2017

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:36.504744Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:36.504744Z digest=sha256:1f59c98e2fe097d2a1893ce3580497f052990cbe6a4548ca564bba8304961426

Observation 9a10b29c-5212-4ae8-9d5d-0b0866e0e23a · outbound

This paper cites Attention is all you need.Advances in neural information processing systems, 30, 2017.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Attention is all you need.Advances in neural information processing systems, 30, 2017

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:36.600509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:36.600509Z digest=sha256:d7cfaf11e0450ab99f432b5203a4661ad2e782fe1e778a08337647a0d571b853

Observation deba0e3a-9981-45a0-a79d-9960ec0228f8 · outbound

This paper cites Matching networks for one shot learning.Ad- vances in neural information processing systems, 29, 2016.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Matching networks for one shot learning.Ad- vances in neural information processing systems, 29, 2016

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:36.666903Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:36.666903Z digest=sha256:a231723345b1ffc3cc7158261a249a95836e1467d45f2695c60c755925861f95

Observation d69a029e-ff12-4a2b-bcdc-60740cbac56c · outbound

This paper cites Detr3d: 3d ob- ject detection from multi-view images via 3d-to-2d queries.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Detr3d: 3d ob- ject detection from multi-view images via 3d-to-2d queries

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:36.720556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:36.720556Z digest=sha256:573898cde7ca4bbe6d783d4457f54f154b084033952dd30574aa632670dccb1c

Observation 7948e0bc-6c73-404b-a43b-1b0aecb57067 · outbound

This paper cites Unsupervised point cloud rep- resentation learning with deep neural networks: A survey.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Unsupervised point cloud rep- resentation learning with deep neural networks: A survey

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:36.783228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:36.783228Z digest=sha256:9bda6fd48547e3f178f238909bd9a98ac06d6d00cad5f523372b8827f78ccde5

Observation d2192f11-1968-4a61-9ca2-5d0b7c9b9f4e · outbound

This paper cites Pixel-aligned recurrent queries for multi-view 3d object detection.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Pixel-aligned recurrent queries for multi-view 3d object detection

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:36.875009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:36.875009Z digest=sha256:d29f30619ae87a5939f92dede59f08f54608b767380f7f405765b55af4bd697a

Observation 2dd9e018-f32b-4262-b559-afd52f9f428a · outbound

This paper cites Stabilizing transformer training by pre- venting attention entropy collapse.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Stabilizing transformer training by pre- venting attention entropy collapse

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:36.946663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:36.946663Z digest=sha256:2ed8830b961f253e01f4e53b0da5c45d2e3559efb31109b7bb4bb29f6735213d

Observation 893fbcbf-f83a-4ccc-86c2-8e95b1b158df · outbound

This paper cites Feature- proxy transformer for few-shot segmentation.Advances in neural information processing systems, 35:6575–6588,.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Feature- proxy transformer for few-shot segmentation.Advances in neural information processing systems, 35:6575–6588,

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:37.011021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:37.011021Z digest=sha256:65e3082f6431b4e32788e43d5b648c8782046529b1cc11fc9788537d686ef86b

Observation 4055cd02-5629-42c4-9d33-fae34db64b19 · outbound

This paper cites Threshold-Consistent Margin Loss for Open-World Deep Metric Learning.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Threshold-Consistent Margin Loss for Open-World Deep Metric Learning

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:37.127175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:37.127175Z digest=sha256:3e98bbec3d1cbe617cc422f7217450cf9dc123bb815230e1bd37d5e34c5fdff3

Observation 0dc3bab5-9617-46a5-958b-20c57bc9e15b · outbound

This paper cites Few-shot 3d point cloud semantic segmentation.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Few-shot 3d point cloud semantic segmentation

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:37.190156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:37.190156Z digest=sha256:113a086cf42f68d02fb9cf15d6bce48407146fe72eefd657f114e0c65843c591

Observation 0b51bcfc-1365-42f2-aa3e-ae9193c2f2fd · outbound

This paper cites Dynamic adapter meets prompt tuning: Parameter-efficient transfer learning for point cloud analysis.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation Dynamic adapter meets prompt tuning: Parameter-efficient transfer learning for point cloud analysis

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:37.237715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:37.237715Z digest=sha256:16fea25664e89a1ca7cda4302683c53d3e5e025bd755c9ede8366166e9043186

Observation e493f401-6835-42b5-ab7b-6b4c10461295 · outbound

This paper cites No time to train: Empowering non-parametric net- works for few-shot 3d scene segmentation.

White Aggregation and Restoration for Few-shot 3D Point Cloud Semantic Segmentation No time to train: Empowering non-parametric net- works for few-shot 3d scene segmentation

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-04T16:33:37.289633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:33:37.289633Z digest=sha256:11bc6fb5a64dbc833098ab0d808118665cc9e1d51daf5a434dd8563214196acb

Pith citing papers

No inbound Pith citation observations are available.