Paper Citation Record · LEDGER

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care

As of 22 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2506.04389.

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

pith.paper-citation-record.v1
2506.04389 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:47:35.923159Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

18 of 18 outbound references displayed

verified exact0
verified fuzzy12
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 0c9cb463-1458-4649-8ae4-377d7beaaa90 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T10:47:34.533917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40b89bd0-92ad-4ece-84cb-e9edbd05e08c · outbound

This paper cites 4171–4186, Minneapolis, Minnesota, (June 2019).

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care 4171–4186, Minneapolis, Minnesota, (June 2019)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:47:37.947345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c00c27e9-8e12-4ff8-8ad5-257cf5d7dbf8 · outbound

This paper cites Language-agnostic BERT Sentence Embedding.

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care Language-agnostic BERT Sentence Embedding

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T10:47:34.673853Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58e31b3e-e53f-4495-b026-f521b20802d3 · outbound

This paper cites 3904–3913, Hong Kong, China, (November 2019).

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care 3904–3913, Hong Kong, China, (November 2019)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:47:37.771287Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3a29507b-4700-43ff-aeae-1fdc6ebecfd0 · outbound

This paper cites 305–313, Online, (August 2021).

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care 305–313, Online, (August 2021)

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:47:37.664668Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 298ae760-f59d-4b86-8f0c-ab844f00d864 · outbound

This paper cites Smith, ‘Don’t stop pretraining: Adapt language models to domains and tasks’, in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp.

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care Smith, ‘Don’t stop pretraining: Adapt language models to domains and tasks’, in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:47:37.560190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 63cda3e2-fada-48ef-adef-022b27e98993 · outbound

This paper cites 5392– 5404, Florence, Italy, (July 2019).

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care 5392– 5404, Florence, Italy, (July 2019)

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:47:37.396201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b1273d74-f56d-43f1-8f07-afb531e9a6a7 · outbound

This paper cites Kingma and Jimmy Ba.

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care Kingma and Jimmy Ba

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T10:47:35.129600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f799583-6f5c-4361-b750-8093d23d32be · outbound

This paper cites 1209–1218, Online, (November 2020).

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care 1209–1218, Online, (November 2020)

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:47:37.262867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 20cc8b28-6fb4-433a-b2b9-329869b97c51 · outbound

This paper cites 172–182, Online, (November 2020).

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care 172–182, Online, (November 2020)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:47:37.056109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1520993d-00b0-464e-a882-d50aa67788be · outbound

This paper cites Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation.

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T10:47:35.331537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5d7feb1-ada7-4d9b-9427-c7316880c9f1 · outbound

This paper cites Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter, 2020.

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter, 2020

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T10:47:35.431879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5a1b3d5-3918-4b34-9875-70873cfd0a9e · outbound

This paper cites Torres, Arantza Pozo, and Raquel Justo, ‘Topic classifier for customer service dialog systems’, pp.

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care Torres, Arantza Pozo, and Raquel Justo, ‘Topic classifier for customer service dialog systems’, pp

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:47:36.871104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation d99c693b-7eb4-49e7-873d-ce0b681525f0 · outbound

This paper cites Generating representative samples for few-shot classification, 2022.

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care Generating representative samples for few-shot classification, 2022

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:47:36.702091Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 3193ade5-d253-46e4-a533-9a61ff3ba9a3 · outbound

This paper cites 4618–4625.

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care 4618–4625

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:47:36.548546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6f59e94e-a436-4cf3-baa1-ce24798c4e3f · outbound

This paper cites an unresolved cited work.

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care Unresolved cited work

Reference 16

Resolution: unresolved; raw_fallback, observed 2026-08-07T10:47:36.362901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation af60d8b8-f59e-4da3-96ab-2c140ba47118 · outbound

This paper cites Lam, ‘Effectiveness of pre-training for few-shot intent classification’, in Findings of the Association for Computational Linguistics: EMNLP 2021, pp.

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care Lam, ‘Effectiveness of pre-training for few-shot intent classification’, in Findings of the Association for Computational Linguistics: EMNLP 2021, pp

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:47:36.252507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation b7c7ff51-c4a6-42db-9ed4-217e47ff3d47 · outbound

This paper cites 5064– 5082, Online, (November 2020).

Building a Few-Shot Cross-Domain Multilingual NLU Model for Customer Care 5064– 5082, Online, (November 2020)

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:47:36.089392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

No inbound Pith citation observations are available.