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Paper Citation Record · LEDGER

Domain-Adaptive Small Language Models for Structured Tax Code Prediction

As of 16 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2507.10880.

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

pith.paper-citation-record.v1
2507.10880 v2

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:25:03.020705Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

15 of 15 outbound references displayed

  • verified exact0
  • verified fuzzy7
  • unresolved8
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c58a8b58-bdc3-4bf2-b0ec-152c261eb674 · outbound

This paper cites Harmonized system (hs) nomenclature, 2023.

Domain-Adaptive Small Language Models for Structured Tax Code Prediction Harmonized system (hs) nomenclature, 2023

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:25:04.349410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T17:25:01.847075Z digest=sha256:649a2e0abf30a7881a4e9e7ac6800808ff239b7944230a0496de5bfb70768aee

Observation dc2c3193-ceff-4237-a120-4f82a35cfdf8 · outbound

This paper cites Classification of goods, 2023.

Domain-Adaptive Small Language Models for Structured Tax Code Prediction Classification of goods, 2023

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:25:04.214633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T17:25:01.898333Z digest=sha256:e0408576aeed6b3c79bf0be4060155588fe54eec4ba914662a9baf1f95eadac5

Observation a2383f70-e63d-4e20-90a9-4cd17f26ac63 · outbound

This paper cites It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners.

Domain-Adaptive Small Language Models for Structured Tax Code Prediction It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T17:25:01.969087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:25:01.969087Z digest=sha256:bb0b62674bde27c1e8d6c14bce88143ef07d5d9cde0e0f49e02e37de7124e666

Observation 8b7b80c2-2b86-4043-8b2e-6decadb1267c · outbound

This paper cites Small Language Models are the Future of Agentic AI.

Domain-Adaptive Small Language Models for Structured Tax Code Prediction Small Language Models are the Future of Agentic AI

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T17:25:02.020373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:25:02.020373Z digest=sha256:66fc0c176d36e403c575b02690c7dc628c02fc3028b166c824695a4b8cc485fe

Observation eb2c8444-5885-4cc0-afe1-24c9dd60dba5 · outbound

This paper cites Neural Machine Translation by Jointly Learning to Align and Translate.

Domain-Adaptive Small Language Models for Structured Tax Code Prediction Neural Machine Translation by Jointly Learning to Align and Translate

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T17:25:02.128125Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:25:02.128125Z digest=sha256:9cd2c2c0e221890a000d53311845e1a30fac6ae73fb0c1bd26e6ec7be3aa0838

Observation 326b08ce-d75f-425e-b731-84ae37d675db · outbound

This paper cites Rapidfuzz.

Domain-Adaptive Small Language Models for Structured Tax Code Prediction Rapidfuzz

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:25:04.058172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T17:25:02.225124Z digest=sha256:6892732da7f8908eb45a7db438dbd83ff2d3361967aa993f080e8adcfcc13d94

Observation 02aaa07c-4a19-4bc1-a866-10322c0a0781 · outbound

This paper cites Neural machine translation of rare words with subword units, 2015.

Domain-Adaptive Small Language Models for Structured Tax Code Prediction Neural machine translation of rare words with subword units, 2015

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:25:03.949382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T17:25:02.340538Z digest=sha256:7da4b56395d6b966949c632dcc41c61c85cf909cddf80ace4ffafb6e3baa0db0

Observation 2a09c3e2-55e7-479c-847a-a76f33f6cd7a · outbound

This paper cites an unresolved cited work.

Domain-Adaptive Small Language Models for Structured Tax Code Prediction Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:25:03.849506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T17:25:02.431849Z digest=sha256:ea39f9b4991a98bddc320c87bbf303cbabafea2c593daab7417748d5b3ce1be3

Observation 160ccb11-7cbe-4406-9112-9efcdcb0744d · outbound

This paper cites Gomez, Łukasz Kaiser, and Illia Polosukhin.

Domain-Adaptive Small Language Models for Structured Tax Code Prediction Gomez, Łukasz Kaiser, and Illia Polosukhin

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:25:03.701938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T17:25:02.522142Z digest=sha256:e4f6efdcec4b59d8cb2b9d86bc0778a6d837b8d46c36d674ec2088a1f71f2965

Observation 34c38958-cea2-4d7e-9070-2f3b3d470bb8 · outbound

This paper cites A Short Study on Compressing Decoder-Based Language Models.

Domain-Adaptive Small Language Models for Structured Tax Code Prediction A Short Study on Compressing Decoder-Based Language Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T17:25:02.582307Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:25:02.582307Z digest=sha256:452d1af26e08a00f82c5f1b817b77e23e182cfd7ca2fa0c21ccbf0ff60b0a262

Observation 40b911c0-06db-4e3a-ad3f-fbf02503e0d3 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding, 2018.

Domain-Adaptive Small Language Models for Structured Tax Code Prediction Bert: Pre-training of deep bidirectional transformers for language understanding, 2018

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:25:03.588800Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T17:25:02.684996Z digest=sha256:9d9ad2d75f9d86e8d14752c7437043dfffbf37dd0302b5d4b742015c217c49ed

Observation 871cb4dc-0624-421a-a463-999c0e842a54 · outbound

This paper cites an unresolved cited work.

Domain-Adaptive Small Language Models for Structured Tax Code Prediction Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-06T17:25:03.478068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T17:25:02.776627Z digest=sha256:fed31994944d94819160f29ef866bc109b3b25d929be1ca97b7abdf2ea9abb20

Observation 0f85d43e-5aea-4a64-871f-89e3826681a2 · outbound

This paper cites Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.

Domain-Adaptive Small Language Models for Structured Tax Code Prediction Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T17:25:02.884623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:25:02.884623Z digest=sha256:eb12fea7c2764f39f67c2287268310e8c89fbafe25586a215dda181f63164da4

Observation 213f2062-78c2-411b-8edd-13cfc3efb355 · outbound

This paper cites Language to Logical Form with Neural Attention.

Domain-Adaptive Small Language Models for Structured Tax Code Prediction Language to Logical Form with Neural Attention

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T17:25:02.953713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:25:02.953713Z digest=sha256:5c5dcf7047b6ca0ae3dffea139710fcc10fc57cdf0610f1f983a92eeba4a246a

Observation 17484eef-2bfc-4893-abb7-8e78a6e88bd7 · outbound

This paper cites Show, attend and tell: Neural image caption generation with visual attention.

Domain-Adaptive Small Language Models for Structured Tax Code Prediction Show, attend and tell: Neural image caption generation with visual attention

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:25:03.331901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T17:25:03.020705Z digest=sha256:492600b1eb18da1606be42a3b6f22c9118ccd3b27d10373fa1dac3e990e7f33a

Pith citing papers

No inbound Pith citation observations are available.