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Paper Citation Record · LEDGER

Semantic Instance Segmentation with a Discriminative Loss Function

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:1708.02551.

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

pith.paper-citation-record.v1
1708.02551 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:05:31.520314Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

24
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation ff26ee59-dc6f-4598-9b96-45d10eacc0c3 · inbound

In defense of OSVOS cites this paper.

In defense of OSVOS Semantic Instance Segmentation with a Discriminative Loss Function

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-14T12:40:45.203057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:40:45.203057Z digest=sha256:9c4f3d5d734e6119a10117919efcf501cf8641cea57476b2a7fde861cf7a988d

Observation 626cfecc-7d27-42ba-a9b8-50eaffede629 · inbound

SSAP: Single-Shot Instance Segmentation With Affinity Pyramid cites this paper.

SSAP: Single-Shot Instance Segmentation With Affinity Pyramid Semantic Instance Segmentation with a Discriminative Loss Function

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-14T05:16:58.692925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T05:16:58.692925Z digest=sha256:a5ed52370598f1d587b4026219fd352244298d44603c5c740392689485a86e40

Observation ca60acc4-3f30-4523-9894-7d67de1bed38 · inbound

Pseudo-Label Quality Decoupling and Correction for Semi-Supervised Instance Segmentation cites this paper.

Pseudo-Label Quality Decoupling and Correction for Semi-Supervised Instance Segmentation Semantic Instance Segmentation with a Discriminative Loss Function

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-15T21:05:31.520314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:05:31.520314Z digest=sha256:c3eda9999f0d6c46f74b6db9fab86937b47ba26884b3e4d0f9d696edd6ce7de2

Observation 2fff6eee-28b9-44b6-89bc-604962ff092d · inbound

gen2seg: Generative Models Enable Generalizable Instance Segmentation cites this paper.

gen2seg: Generative Models Enable Generalizable Instance Segmentation Semantic Instance Segmentation with a Discriminative Loss Function

Reference 7

Resolution
metadata mismatch
local_arxiv, observed 2026-05-22T14:31:40.455449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-11T11:50:26.030339Z digest=sha256:fa2257a6c5617e6e60befe5c663aaa3cb070e2e6ec4da1fe57504beb1c0db726

Observation 82c802e7-9622-4842-b82a-36072dfc7e1d · inbound

Open-Set LiDAR Panoptic Segmentation Guided by Uncertainty-Aware Learning cites this paper.

Open-Set LiDAR Panoptic Segmentation Guided by Uncertainty-Aware Learning Semantic Instance Segmentation with a Discriminative Loss Function

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-07T00:41:08.612768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:41:08.612768Z digest=sha256:587b9846b711f65803dbe17829f39fb8ac035a305287563116204033614efd8d

Observation d1c76758-fbe5-4438-9adc-73293337a6be · inbound

GVCCS: A Dataset for Contrail Identification and Tracking on Visible Whole Sky Camera Sequences cites this paper.

GVCCS: A Dataset for Contrail Identification and Tracking on Visible Whole Sky Camera Sequences Semantic Instance Segmentation with a Discriminative Loss Function

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T14:37:32.071995Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:37:32.071995Z digest=sha256:4ae8270ad1722f656949dab69a26bbb09c73624ec69b2eaa06b5805e29ce6d7e

Observation c0a6fe54-2524-4d25-b574-996860b33793 · inbound

MapRF: Weakly Supervised Online HD Map Construction via NeRF-Guided Self-Training cites this paper.

MapRF: Weakly Supervised Online HD Map Construction via NeRF-Guided Self-Training Semantic Instance Segmentation with a Discriminative Loss Function

Reference 46

Resolution
verified exact
local_arxiv, observed 2026-05-17T06:49:11.509078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-17T06:47:55.820535Z digest=sha256:040334ac67714f10a06e911699121d538e648b0cd4d15ca5dcdcb6b38a29c154

Observation 327e26c3-81f1-4bc0-8ef2-9132f67cfad0 · inbound

Evaluation of Embedding-Based and Generative Methods for LLM-Driven Document Classification: Opportunities and Challenges cites this paper.

Evaluation of Embedding-Based and Generative Methods for LLM-Driven Document Classification: Opportunities and Challenges Semantic Instance Segmentation with a Discriminative Loss Function

Reference 2

Resolution
unresolved
no resolver link, observed 2026-07-13T10:23:38.252227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T10:23:38.252227Z digest=sha256:33b59fde6af97a0b4663044700c3293f1a8cc95436ac821198022543f6a5519b

Observation 9fa213d5-884f-4513-8702-6cf69c026dee · inbound

Neural Collapse by Design: Learning Class Prototypes on the Hypersphere cites this paper.

Neural Collapse by Design: Learning Class Prototypes on the Hypersphere Semantic Instance Segmentation with a Discriminative Loss Function

Reference 69

Resolution
metadata mismatch
local_arxiv, observed 2026-05-21T07:34:48.042400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-21T07:34:23.657217Z digest=sha256:b0483ad24ba56b536c3fe21bd4d3a9e4b39d47ff114c07d5175c77738d69d559

Observation d108c9d6-40c9-456a-817a-2313b08b3b91 · inbound

Neural Collapse by Design: Learning Class Prototypes on the Hypersphere cites this paper.

Neural Collapse by Design: Learning Class Prototypes on the Hypersphere Semantic Instance Segmentation with a Discriminative Loss Function

Reference 69

Resolution
metadata mismatch
local_arxiv, observed 2026-05-22T09:51:21.829449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-22T09:48:55.074560Z digest=sha256:d160568edfc0d58bfcb2fd0b61da59d7ff6c277b3b86453a1cfe39048b27832d