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Paper Citation Record · LEDGER

Empowering Segmentation Ability to Multi-modal Large Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2403.14141.

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

pith.paper-citation-record.v1
2403.14141 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:27:18.655378Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T15:09:55.073743Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 61a7ef6b-27f3-4b50-8a02-cc88f72dbcf5 · inbound

Reasoning Segmentation for Images and Videos: A Survey cites this paper.

Reasoning Segmentation for Images and Videos: A Survey Empowering Segmentation Ability to Multi-modal Large Language Models

Reference 98

Resolution
unresolved
no resolver link, observed 2026-08-07T14:27:18.655378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:27:18.655378Z digest=sha256:66c317cd38ce51c8487e4391a14afaca297c8ef4ec26c0e2448442681461c516

Observation 517d6065-62a0-40aa-91b7-816888cdbd26 · inbound

PostAlign: Multimodal Grounding as a Corrective Lens for MLLMs cites this paper.

PostAlign: Multimodal Grounding as a Corrective Lens for MLLMs Empowering Segmentation Ability to Multi-modal Large Language Models

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-06T23:27:19.407889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:27:19.407889Z digest=sha256:586e4adff669de32e0483ec9682fedece6dab58f99e46215e8fcab463509cab3

Observation cbe9196e-3292-48cd-8283-79d7e716a3a3 · inbound

HRSeg: High-Resolution Visual Perception and Enhancement for Reasoning Segmentation cites this paper.

HRSeg: High-Resolution Visual Perception and Enhancement for Reasoning Segmentation Empowering Segmentation Ability to Multi-modal Large Language Models

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-06T16:43:55.434020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:43:55.434020Z digest=sha256:00ddea6791a1922392d8298f66f437a077ec051a9a0d485a539577fab2805b02

Observation 51c78503-c829-4065-ac28-bdf4c5767f0a · inbound

Train the Agent, Not the Expert: Learning to Harness Heterogeneous Experts for Multi-Turn Visual Reasoning cites this paper.

Train the Agent, Not the Expert: Learning to Harness Heterogeneous Experts for Multi-Turn Visual Reasoning Empowering Segmentation Ability to Multi-modal Large Language Models

Reference 38

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T08:53:16.445858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-29T08:34:20.457516Z digest=sha256:7fb269029e4abcce636875fc5850f0c591858ef0c050463b08e8d66be34c9cf4

Observation 974ace4c-7dff-451a-b5ce-44a79973b224 · inbound

From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models cites this paper.

From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models Empowering Segmentation Ability to Multi-modal Large Language Models

Reference 73

Resolution
verified exact
arxiv_id, observed 2026-07-04T15:09:55.075286Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-26T01:50:54.242508Z digest=sha256:ae9f5911115c66f27f32a24cb7a059d49c802d66ef9e60ec966a77405c62f120