Pith. sign in

Paper Citation Record · LEDGER

DLIP: Distilling Language-Image Pre-training

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2308.12956.

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

pith.paper-citation-record.v1
2308.12956 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T14:59:19.556141Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-08T16:45:07.684747Z

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 4db68fbb-6f5d-4286-a80e-ee3e8ea8dc23 · inbound

MobileCLIP2: Improving Multi-Modal Reinforced Training cites this paper.

MobileCLIP2: Improving Multi-Modal Reinforced Training DLIP: Distilling Language-Image Pre-training

Reference 2014

Resolution
unresolved
no resolver link, observed 2026-08-05T14:59:19.556141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:59:19.556141Z digest=sha256:2ff3fb1104b1d8a0a54af50a50fc568bea43261ee9d14dd0bcfbe3359271ccee

Observation dc1c7fd1-f2a1-42b7-8d6c-70c35142d45f · inbound

PVCap: Towards Accurate 3D Dense Captioning via PseudoCap and VoxelCapNet cites this paper.

PVCap: Towards Accurate 3D Dense Captioning via PseudoCap and VoxelCapNet DLIP: Distilling Language-Image Pre-training

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-07-08T16:45:07.686511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-07-08T16:39:53.448383Z digest=sha256:11d8f36538a5cf4310798fcab6fed74dd4e3720ba27d6daacdb7bc375dc890b9