Pith. sign in

Paper Citation Record · LEDGER

Continual Pre-Training is (not) What You Need in Domain Adaption

As of 19 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 1 inbound Pith citation observation for arXiv:2504.13603.

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

pith.paper-citation-record.v1
2504.13603 v1

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:07:46.894477Z

measured 44 of 44 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T05:53:58.324895Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-16T05:53:59.037632Z

Reference resolution

43 of 43 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved42
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bfb75b32-ae8f-4546-afeb-bcae694bfe63 · outbound

This paper cites Almeida, José Luiz Nunes, Neele Engelmann, Alex Wiegmann, and Marcelo de Araújo.

Continual Pre-Training is (not) What You Need in Domain Adaption Almeida, José Luiz Nunes, Neele Engelmann, Alex Wiegmann, and Marcelo de Araújo

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.658072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.658072Z digest=sha256:52bc5513a16834ccb08569815ee096397521e6a93624cd64b88ece47d990ece3

Observation f47f350b-c7bb-4191-a770-c8904a34e775 · outbound

This paper cites an unresolved cited work.

Continual Pre-Training is (not) What You Need in Domain Adaption Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-08-16T12:07:47.907906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T12:07:46.664306Z digest=sha256:dc56e62c3cefe2df34776b133b56949629d921de6f84d9269220c391adf6c3f2

Observation ea92bc43-0ccc-448c-b371-ee0fa8752ee7 · outbound

This paper cites an unresolved cited work.

Continual Pre-Training is (not) What You Need in Domain Adaption Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-16T12:07:47.891264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T12:07:46.672013Z digest=sha256:ca5c3f490ddcd08f5f3ce6cf2c032a8e31656ac222586d25d75c1d725e4ba95b

Observation 2e11ef73-70cc-4b55-870a-77b33a432eca · outbound

This paper cites an unresolved cited work.

Continual Pre-Training is (not) What You Need in Domain Adaption Unresolved cited work

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.677391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.677391Z digest=sha256:9b6c5637b9261d29e2dba0152896213257bb5464ea7d2ec6d2041ebf41dd5ac4

Observation 5072ac94-3bc7-462f-9682-b929782b6944 · outbound

This paper cites Adapting Large Language Models to Domains via Reading Comprehension.

Continual Pre-Training is (not) What You Need in Domain Adaption Adapting Large Language Models to Domains via Reading Comprehension

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.682614Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.682614Z digest=sha256:d04ab8fded06aadbedf0dcb5f64e202f51e05f93aa7bc00a10f2172094a597ad

Observation 3d0f1b55-155b-4641-b443-626c16a004e1 · outbound

This paper cites SaulLM-54B & SaulLM-141B: Scaling Up Domain Adaptation for the Legal Domain.

Continual Pre-Training is (not) What You Need in Domain Adaption SaulLM-54B & SaulLM-141B: Scaling Up Domain Adaptation for the Legal Domain

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.688348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.688348Z digest=sha256:514feb18575eede65f387ce21f648cba039e296d9d5333fa0c16589d2152b364

Observation faedcb08-8246-4775-a5c9-de20b6472fd2 · outbound

This paper cites Efficient and Effective Text Encoding for Chinese LLaMA and Alpaca.

Continual Pre-Training is (not) What You Need in Domain Adaption Efficient and Effective Text Encoding for Chinese LLaMA and Alpaca

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.695033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.695033Z digest=sha256:66475f12d5fd136190239a5616b42f53cb02470e5cf5d9697b545f972bc1878c

Observation 8bb49165-520a-4e34-b3d1-4040909936c7 · outbound

This paper cites LAiW: A Chinese Legal Large Language Models Benchmark.

Continual Pre-Training is (not) What You Need in Domain Adaption LAiW: A Chinese Legal Large Language Models Benchmark

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.700606Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.700606Z digest=sha256:915613e4fcb006b016a727d8df766aa463cbde4f3af102579c2abc51f415072e

Observation ad14254e-1ee4-4a00-9fe9-9d4180ded20d · outbound

This paper cites LawBench: Benchmarking Legal Knowledge of Large Language Models.

Continual Pre-Training is (not) What You Need in Domain Adaption LawBench: Benchmarking Legal Knowledge of Large Language Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.705908Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.705908Z digest=sha256:71878c30e6107c2092622c0cde025e9dfc4db3d6f34b56938a2c75bad015b992

Observation b151d27a-efbd-42e8-9df8-1d564b6bd4a5 · outbound

This paper cites an unresolved cited work.

Continual Pre-Training is (not) What You Need in Domain Adaption Unresolved cited work

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.710991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.710991Z digest=sha256:c59a6277b732465f68f2bb20f88f86b8e52d5cb518e4dc3b37ff9bfe677161d9

Observation 88b76c17-53f9-4a4b-b8e7-537b9807d8ea · outbound

This paper cites LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models.

Continual Pre-Training is (not) What You Need in Domain Adaption LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.716010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.716010Z digest=sha256:ee0dfa3092a117af7bc77d4c36bfca0c8a77725f126a032c6332b9f3c83de5bc

Observation e06a5416-10fe-4b06-99c1-55d734ef36ac · outbound

This paper cites Continuous Training and Fine-tuning for Domain-Specific Language Models in Medical Question Answering.

Continual Pre-Training is (not) What You Need in Domain Adaption Continuous Training and Fine-tuning for Domain-Specific Language Models in Medical Question Answering

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-08-16T12:07:47.598266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T12:07:46.721977Z digest=sha256:71f563041f957b58cde7277a0c15f4a9d7772a950aa71a797a1a518e2893ba6d

Observation bc90990b-bd22-43bb-a31f-2305dd609b4b · outbound

This paper cites an unresolved cited work.

Continual Pre-Training is (not) What You Need in Domain Adaption Unresolved cited work

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.727374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.727374Z digest=sha256:0f371194826b338c54588f9ee0ae935ace184be619aa8788e258fa3dc86323de

Observation 83bb8bf6-7c8d-4894-95f7-991d7efeccab · outbound

This paper cites an unresolved cited work.

Continual Pre-Training is (not) What You Need in Domain Adaption Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-08-16T12:07:47.874226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T12:07:46.732353Z digest=sha256:9763b7dbff95c26d2531c30034952bcdcd991bff47db5f86d5c0c3d3c39d0912

Observation 6b448ff0-b0b6-42ff-8740-f8d051a25bde · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Continual Pre-Training is (not) What You Need in Domain Adaption Measuring Massive Multitask Language Understanding

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.737250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.737250Z digest=sha256:0bba20da72e15a21fa655d8dc019a6eaa1f9071a31853f74885b5310390d4bae

Observation 3eb77d51-5739-4ae5-81c9-e816643453df · outbound

This paper cites ORPO: Monolithic Preference Optimization without Reference Model.

Continual Pre-Training is (not) What You Need in Domain Adaption ORPO: Monolithic Preference Optimization without Reference Model

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.742185Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.742185Z digest=sha256:b0c5cd5118d2b2ccf02b1aa559a35118c87def7c6bad20d6c11cdb4b71a58146

Observation 44c650de-2ea6-4a2b-965e-0ffefadbdeff · outbound

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

Continual Pre-Training is (not) What You Need in Domain Adaption LoRA: Low-Rank Adaptation of Large Language Models

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.747381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.747381Z digest=sha256:b6af56c796ded3a9dd8834345bf51ca3a1d7cc55278df40d75c4fdd1466ac08a

Observation ead5f601-c1c6-4486-a7d7-e62a47f6dd3a · outbound

This paper cites C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models.

Continual Pre-Training is (not) What You Need in Domain Adaption C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.752653Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.752653Z digest=sha256:fc3076a4fc862f87fc75b40a8d71ea4f6cd14f6a00a9057f4489318090fc1e96

Observation 26b789ca-5a7c-4d7d-a66a-b9d2b3a8d86f · outbound

This paper cites an unresolved cited work.

Continual Pre-Training is (not) What You Need in Domain Adaption Unresolved cited work

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.758565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.758565Z digest=sha256:35dedfb84328de1406e1008d151b723ed88884ecb1404b6827e1d70ade6e6d0b

Observation d9a9bbef-a707-4aee-b32e-fbc247a0fe58 · outbound

This paper cites Large Language Models in Law: A Survey.

Continual Pre-Training is (not) What You Need in Domain Adaption Large Language Models in Law: A Survey

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.763190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.763190Z digest=sha256:49bf7720c5f78a7cf7bc37bfca25cd0ad1a9afd1c4c8ce00be4f79553b1752bc

Observation 729522ba-48fa-42f3-8db1-337126e630ee · outbound

This paper cites an unresolved cited work.

Continual Pre-Training is (not) What You Need in Domain Adaption Unresolved cited work

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.768699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.768699Z digest=sha256:7e1865c9771362f212ca1e37abcc8fe97724880e7f4cf80ceb2b5ed71c636888

Observation f179b158-7267-497b-abb7-4d26e6d920cc · outbound

This paper cites CMMLU: Measuring massive multitask language understanding in Chinese.

Continual Pre-Training is (not) What You Need in Domain Adaption CMMLU: Measuring massive multitask language understanding in Chinese

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.774250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.774250Z digest=sha256:c795340deb7295410ff17cbb9e0052dade4483d478a85d119cb5396f0ee03f02

Observation 0a5dc9af-c237-4c17-8fb3-396b1151979b · outbound

This paper cites Taiwan LLM: Bridging the Linguistic Divide with a Culturally Aligned Language Model.

Continual Pre-Training is (not) What You Need in Domain Adaption Taiwan LLM: Bridging the Linguistic Divide with a Culturally Aligned Language Model

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.780194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.780194Z digest=sha256:018908122c88ebe54934d9ebc9280778a6eac9e586ec19e1f02bb496f50ad660

Observation f4a5c182-6968-4c75-aa8a-bb9d1fbe39b7 · outbound

This paper cites EcomGPT-CT: Continual Pre-training of E-commerce Large Language Models with Semi-structured Data.

Continual Pre-Training is (not) What You Need in Domain Adaption EcomGPT-CT: Continual Pre-training of E-commerce Large Language Models with Semi-structured Data

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.787630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.787630Z digest=sha256:bbb561ed480cd2d2dcc6727e856e27c01ff772eddf2d40b4cce58375bc94c414

Observation df818812-d26b-4c14-8087-45938602e11f · outbound

This paper cites an unresolved cited work.

Continual Pre-Training is (not) What You Need in Domain Adaption Unresolved cited work

Reference 25

Resolution
unresolved
raw_fallback, observed 2026-08-16T12:07:47.857741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T12:07:46.793530Z digest=sha256:858130207e71bb445ddefa990d1ac35849e4de56f09f7cdba1de23eabf6d6e77

Observation 1a3d5df5-af2f-44a6-93da-f6b1b9ca8ac2 · outbound

This paper cites D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models.

Continual Pre-Training is (not) What You Need in Domain Adaption D-CPT Law: Domain-specific Continual Pre-Training Scaling Law for Large Language Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.798924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.798924Z digest=sha256:007eedebeec9ab96350a09fdab87cee5677e85788a5c98fbe09472beaafee37a

Observation f87618a8-ccea-4022-8c80-b3226b766eb1 · outbound

This paper cites Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

Continual Pre-Training is (not) What You Need in Domain Adaption Direct Preference Optimization: Your Language Model is Secretly a Reward Model

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.805154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.805154Z digest=sha256:812eeb430974490a67de93ec93d5151b770050a7e654d1f5331a5a409c6be9c1

Observation ca31f367-95d8-440e-a600-d1e6afe1ced4 · outbound

This paper cites Continual Learning of Large Language Models: A Comprehensive Survey.

Continual Pre-Training is (not) What You Need in Domain Adaption Continual Learning of Large Language Models: A Comprehensive Survey

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.811697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.811697Z digest=sha256:15cf9cf9ad3624e2fac5528e98328484ffd7c0e35514c8e87ace14bbbfa7eee1

Observation 1abd4c0b-e611-46c7-9158-d6d28703f02f · outbound

This paper cites An Improved Traditional Chinese Evaluation Suite for Foundation Model.

Continual Pre-Training is (not) What You Need in Domain Adaption An Improved Traditional Chinese Evaluation Suite for Foundation Model

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.817618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.817618Z digest=sha256:c5a955c08f97f0d7e1f81bfb430f40d5dfca272d9a90e71b145d6f4aeee5f7ea

Observation a4cb9092-fec1-425f-8995-6f4944a9a476 · outbound

This paper cites an unresolved cited work.

Continual Pre-Training is (not) What You Need in Domain Adaption Unresolved cited work

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.823084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.823084Z digest=sha256:64020266aca7f07fc3d1d2f79c8f0a03b652d20baf5e60613f6207bd56ac1197

Observation 85ae0514-0e4a-4e15-bf14-57c44ce2ac26 · outbound

This paper cites BloombergGPT: A Large Language Model for Finance.

Continual Pre-Training is (not) What You Need in Domain Adaption BloombergGPT: A Large Language Model for Finance

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.827795Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.827795Z digest=sha256:e8dad19a2e4a173f3a99eaa3c1356707e29ab24d4d88267877bed3cb6b107576

Observation 5663a284-8000-4dc2-b171-2116376edba4 · outbound

This paper cites an unresolved cited work.

Continual Pre-Training is (not) What You Need in Domain Adaption Unresolved cited work

Reference 32

Resolution
unresolved
raw_fallback, observed 2026-08-16T12:07:47.829480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T12:07:46.832902Z digest=sha256:3bfec4130fd8316d65c0e7cd1e1c255eee31f8a9b7ecfec02dda545efdf01a85

Observation cba8ef77-167c-4f05-9dec-b5418d64274a · outbound

This paper cites an unresolved cited work.

Continual Pre-Training is (not) What You Need in Domain Adaption Unresolved cited work

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.838649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.838649Z digest=sha256:db0751d0a91daf56f98941ee7170d037b311c77b173f59afdf6662409b468396

Observation bb50b9d5-a8eb-4a2d-b769-784b97c1ff63 · outbound

This paper cites Fine-Tuning Medical Language Models for Enhanced Long-Contextual Understanding and Domain Expertise.

Continual Pre-Training is (not) What You Need in Domain Adaption Fine-Tuning Medical Language Models for Enhanced Long-Contextual Understanding and Domain Expertise

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.843331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.843331Z digest=sha256:03408811a7eeaab7870e229bedcc334914024b03853b262156e0d41b7f2f02d2

Observation 873d1561-18e0-4061-992e-32ca429e8c52 · outbound

This paper cites DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services.

Continual Pre-Training is (not) What You Need in Domain Adaption DISC-LawLLM: Fine-tuning Large Language Models for Intelligent Legal Services

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.848690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.848690Z digest=sha256:d7a69d89b5576392d22c727d3ae8be9f92b9072bc36df90d2777ae6d276d4d1c

Observation 41c557e4-991d-4a29-a108-4a50453e4e3f · outbound

This paper cites an unresolved cited work.

Continual Pre-Training is (not) What You Need in Domain Adaption Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-16T12:07:47.811732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-16T12:07:46.853458Z digest=sha256:18bf2cc3709cb87db0c90cc84af1f62a186f7d12b53bd05e6dab299785a71c68

Observation 6be01827-ff6d-4cb8-8935-51e985ba339c · outbound

This paper cites an unresolved cited work.

Continual Pre-Training is (not) What You Need in Domain Adaption Unresolved cited work

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.859521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.859521Z digest=sha256:881c5eb2f5495726bddbc10352c8b5e1a0281a3b895aed5052ff1ae673e8be52

Observation 3cdbd2d2-7c7f-439b-87d7-e53d9fd3e1b8 · outbound

This paper cites XuanYuan 2.0: A Large Chinese Financial Chat Model with Hundreds of Billions Parameters.

Continual Pre-Training is (not) What You Need in Domain Adaption XuanYuan 2.0: A Large Chinese Financial Chat Model with Hundreds of Billions Parameters

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.865722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.865722Z digest=sha256:1cf6163b19282340c697f709237b1bf0458005f2b7d25fba24c10a993c9676e8

Observation 80cac27f-5f26-4afa-b5d2-78eb4d093632 · outbound

This paper cites LLaMA Beyond English: An Empirical Study on Language Capability Transfer.

Continual Pre-Training is (not) What You Need in Domain Adaption LLaMA Beyond English: An Empirical Study on Language Capability Transfer

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.871027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.871027Z digest=sha256:fba36853c108c916501924398b05cc95cb682cb978eb426709ff1978f78f022d

Observation c67d58d7-651c-44ef-a608-17dd9ecca77b · outbound

This paper cites MarineGPT: Unlocking Secrets of Ocean to the Public.

Continual Pre-Training is (not) What You Need in Domain Adaption MarineGPT: Unlocking Secrets of Ocean to the Public

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.877890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.877890Z digest=sha256:50386e9906d383aebf52a7264baff932ffa20e6edc516954bce961ab9082e77e

Observation d1e7dd28-6c2c-4c30-a580-1b29bd7f887d · outbound

This paper cites Investigating Continual Pretraining in Large Language Models: Insights and Implications.

Continual Pre-Training is (not) What You Need in Domain Adaption Investigating Continual Pretraining in Large Language Models: Insights and Implications

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.883583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.883583Z digest=sha256:0b982d7a50d364c23f3c1d63430c533c4e7126cfaf28c45d6256cfa26bff57b4

Observation 818d902f-aa6c-429d-a0fd-a4ebb63b64d7 · outbound

This paper cites online" 'onlinestring :=.

Continual Pre-Training is (not) What You Need in Domain Adaption online" 'onlinestring :=

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.889127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.889127Z digest=sha256:a8fb9459fdb189d5722e32d43d9423821c6ea321265e753fb917cad01510a470

Observation 6add0b66-bcd2-467a-82b0-7c0e25175549 · outbound

This paper cites write newline.

Continual Pre-Training is (not) What You Need in Domain Adaption write newline

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-16T12:07:46.894477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:07:46.894477Z digest=sha256:5471fbedb40c5276eaffdd9d12d7f43b1f585838740d0b52cad08906b5ff06c9

Pith citing papers

Observation 27f7d920-4101-4f8a-8288-9c1c48547b2a · inbound

Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report cites this paper.

Llama-3.1-FoundationAI-SecurityLLM-Base-8B Technical Report Continual Pre-Training is (not) What You Need in Domain Adaption

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-08-16T05:53:59.044366Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-08-16T05:53:58.324895Z digest=sha256:8fbb2b7dbdcb58d0c8cacca45c7bba5b53c4743fa9acc16b255c066f1530839c