Pith. sign in

Paper Citation Record · LEDGER

eP-ALM: Efficient Perceptual Augmentation of Language Models

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2303.11403.

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

pith.paper-citation-record.v1
2303.11403 v4

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 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T04:35:52.011699Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T00:42:44.565571Z

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 6b280f1a-f7ee-4211-8a88-65c6165f75af · inbound

MLLM-SUL: Multimodal Large Language Model for Semantic Scene Understanding and Localization in Traffic Scenarios cites this paper.

MLLM-SUL: Multimodal Large Language Model for Semantic Scene Understanding and Localization in Traffic Scenarios eP-ALM: Efficient Perceptual Augmentation of Language Models

Reference 25

Resolution
verified exact
local_arxiv, observed 2026-08-11T00:42:44.572557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-11T00:42:44.264746Z digest=sha256:7b44789690d3d5e8a15287b8bb7c13b6d58aeb128fb49611696f476bee4dd5da

Observation 82796b67-3aff-47aa-a003-6e80e645d566 · inbound

VADER: Adaptive Debiasing for Hallucination Mitigation in Video Large Language Models cites this paper.

VADER: Adaptive Debiasing for Hallucination Mitigation in Video Large Language Models eP-ALM: Efficient Perceptual Augmentation of Language Models

Reference 207

Resolution
unresolved
no resolver link, observed 2026-08-14T04:35:52.011699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T04:35:52.011699Z digest=sha256:4ef17327ca76e9d44a06dce4e4ce7dd03e3cbc54e123c069848452b0cbec2aa6