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Paper Citation Record · LEDGER

Learning to generalize to new compositions in image understanding

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1608.07639.

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

pith.paper-citation-record.v1
1608.07639 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:19:05.847231Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T22:40:36.185437Z

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 3088cb28-022b-4e70-93d0-6677337c2e62 · inbound

Learning Clustering-based Prototypes for Compositional Zero-shot Learning cites this paper.

Learning Clustering-based Prototypes for Compositional Zero-shot Learning Learning to generalize to new compositions in image understanding

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-08T15:19:05.847231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:19:05.847231Z digest=sha256:e750525f6e913588d564da8968ec89d830a3025f8c4391b6e19eb885d9f22e6a

Observation 9884a507-ffe6-4bd5-96ed-1a36dbf6ef64 · inbound

EVA: Mixture-of-Experts Semantic Variant Alignment for Compositional Zero-Shot Learning cites this paper.

EVA: Mixture-of-Experts Semantic Variant Alignment for Compositional Zero-Shot Learning Learning to generalize to new compositions in image understanding

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:40:36.189187Z

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=2026-08-06T22:40:33.079614Z digest=sha256:693aec119b2f023229a8b8d62ab6376e8bb06c3257f2882e0d19365ef522beea