Paper Citation Record · LEDGER

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom

As of 21 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2504.20000.

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

pith.paper-citation-record.v1
2504.20000 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:41:06.351916Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

27 of 27 outbound references displayed

verified exact2
verified fuzzy13
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ce4be93e-e539-45ef-b3a4-0d6d94a7ff12 · outbound

This paper cites Observations on LLMs for telecom domain: capabilities and limitations,.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom Observations on LLMs for telecom domain: capabilities and limitations,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:41:06.700303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7f6b6bec-c47b-4de3-8999-6d1f9e3c12aa · outbound

This paper cites Understanding telecom language through large language models,.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom Understanding telecom language through large language models,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:41:06.688345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation c1235348-cc2d-4a47-9a55-21a710aa7e61 · outbound

This paper cites Evaluation of RAG metrics for question answering in the telecom domain,.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom Evaluation of RAG metrics for question answering in the telecom domain,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:41:06.676648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 74933620-c198-49ea-bf6c-362f6ac102c6 · outbound

This paper cites Using large language models to understand telecom standards,.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom Using large language models to understand telecom standards,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:41:06.664498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation faaa06f1-0573-4c4f-9569-c25fa37a0bb8 · outbound

This paper cites TelecomGPT: A Framework to Build Telecom-Specfic Large Language Models.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom TelecomGPT: A Framework to Build Telecom-Specfic Large Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-16T05:41:06.256621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 387f58e5-c982-4ac1-9525-41fb516e1beb · outbound

This paper cites Telecom Language Models: Must They Be Large?.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom Telecom Language Models: Must They Be Large?

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-16T05:41:06.261213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8b66153-0fd0-4c5d-acbb-afb9729ead11 · outbound

This paper cites Large language models for telecom: Forthcoming impact on the industry,.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom Large language models for telecom: Forthcoming impact on the industry,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:41:06.651379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 40d8cc7c-45f6-4fe9-8f2a-14fc28ba6624 · outbound

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

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom It's Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T05:41:06.270090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3dee4ea3-775b-4da3-9a78-b3538ea7fcf2 · outbound

This paper cites Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM Inference?.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom Revisiting Block-based Quantisation: What is Important for Sub-8-bit LLM Inference?

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-08-16T05:41:06.470472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9c2fb5fa-a2eb-4081-bf58-d37d100f95cc · outbound

This paper cites Llm-pruner: On the structural pruning of large language models,.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom Llm-pruner: On the structural pruning of large language models,

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T05:41:06.278603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4e60668-501a-4073-b7ed-80f0a84fc7b6 · outbound

This paper cites Knowledge distillation: A survey,.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom Knowledge distillation: A survey,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-16T05:41:06.282324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71a00a89-0091-4094-9ece-d910bc37a13f · outbound

This paper cites A Survey on Knowledge Distillation of Large Language Models.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom A Survey on Knowledge Distillation of Large Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-16T05:41:06.286374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86dde50d-1cd2-4b8e-9319-59b112219ef1 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom Distilling the Knowledge in a Neural Network

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T05:41:06.291398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1394e6f2-a632-4676-aff6-b7521f57061c · outbound

This paper cites Attention is all you need,.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom Attention is all you need,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T05:41:06.295593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cffa0e8-5805-4c27-82c5-edd42716f02d · outbound

This paper cites Knowledge Distillation of Russian Language Models with Reduction of Vocabulary.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom Knowledge Distillation of Russian Language Models with Reduction of Vocabulary

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-16T05:41:06.428279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 855eeff2-175e-4217-96ec-d2d2b6969517 · outbound

This paper cites Knowledge distillation from internal representa- tions,.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom Knowledge distillation from internal representa- tions,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:41:06.616830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 93a21158-e688-4b0c-b7c0-6eb16aab82b5 · outbound

This paper cites Dual-space knowledge distillation for large language models,.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom Dual-space knowledge distillation for large language models,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:41:06.603862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation cb3ca38d-3456-44f4-9388-af4757d9e60e · outbound

This paper cites Evalullm: Llm assisted evaluation of gen- erative outputs,.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom Evalullm: Llm assisted evaluation of gen- erative outputs,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:41:06.592462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1e305c0a-03c9-437d-bad9-7f047844ee0f · outbound

This paper cites On the evaluation of neural code summarization,.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom On the evaluation of neural code summarization,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:41:06.579946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 747e0253-fdbd-422a-942a-ee2a5765f3b4 · outbound

This paper cites ROUGE: A package for automatic evaluation of summaries,.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom ROUGE: A package for automatic evaluation of summaries,

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T05:41:06.321259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f0b23993-1160-4630-90d1-a59a7d746df4 · outbound

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

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T05:41:06.325407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e757f8d-1935-4058-9f10-12ef62f64842 · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom BERTScore: Evaluating Text Generation with BERT

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-16T05:41:06.329731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 012c20f0-3f93-4892-9471-35a5d5d99725 · outbound

This paper cites Ragas: Automated evaluation of retrieval augmented generation,.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom Ragas: Automated evaluation of retrieval augmented generation,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:41:06.561210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 07676dc7-273c-48fa-b3fb-eb37d986f98f · outbound

This paper cites TeleQuAD: A suite of question answering datasets for the telecom domain,.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom TeleQuAD: A suite of question answering datasets for the telecom domain,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:41:06.549331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 408ffd28-ab80-4ba8-be09-cd82b1378950 · outbound

This paper cites A generalized wilcoxon test for comparing arbitrarily singly-censored samples,.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom A generalized wilcoxon test for comparing arbitrarily singly-censored samples,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:41:06.535357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b86f8966-2365-4422-b568-1522109dd1eb · outbound

This paper cites 3GPP release 15,.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom 3GPP release 15,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T05:41:06.522571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 007db79b-7654-4753-8a4c-7ef483fe0c31 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Knowledge Distillation of Domain-adapted LLMs for Question-Answering in Telecom LoRA: Low-Rank Adaptation of Large Language Models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T05:41:06.351916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.