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Paper Citation Record · LEDGER

Continual Learning of Large Language Models: A Comprehensive Survey

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 34 inbound Pith citation observations for arXiv:2404.16789.

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

pith.paper-citation-record.v1
2404.16789 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 34 of 34 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:37:13.110730Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T01:09:19.492400Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 4c6a4415-1ed6-4dfa-b194-abe71638ed56 · inbound

Boundless Socratic Learning with Language Games cites this paper.

Boundless Socratic Learning with Language Games Continual Learning of Large Language Models: A Comprehensive Survey

Reference 1997

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source=pdf_text observed=2026-08-12T12:50:17.151349Z digest=sha256:2613d4cf889c4a4eaf5ee8fa11c18451e9deb4c474166fdc8989452e1d85ff0b

Observation 7cf2f62d-36df-47fc-bf25-243329eef74d · inbound

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers cites this paper.

Planning vs Reasoning: Ablations to Test Capabilities of LoRA layers Continual Learning of Large Language Models: A Comprehensive Survey

Reference 16

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source=pdf_text observed=2026-08-12T17:37:13.110730Z digest=sha256:a8e972423061acb5f6aa30b250082832efd94089ff1dd3da9cb4db7498116faa

Observation d945bd22-8c68-447c-8a5a-bb1a1f036d76 · inbound

Survey of different Large Language Model Architectures: Trends, Benchmarks, and Challenges cites this paper.

Survey of different Large Language Model Architectures: Trends, Benchmarks, and Challenges Continual Learning of Large Language Models: A Comprehensive Survey

Reference 32

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source=pdf_text observed=2026-08-11T22:41:14.234747Z digest=sha256:60a3c861abcf4d9118dc2dcb0fbe408bf16d85354566d2de24603d4e2d79125b

Observation b5816682-773c-439c-a849-e914a6d72b10 · inbound

BgGPT 1.0: Extending English-centric LLMs to other languages cites this paper.

BgGPT 1.0: Extending English-centric LLMs to other languages Continual Learning of Large Language Models: A Comprehensive Survey

Reference 48

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source=arxiv_source observed=2026-08-11T15:35:55.406618Z digest=sha256:a6d9762fd455086916ef79a5bbd9bfce3c5a9f509600688216f42546506c455f

Observation 3430f85f-1549-46ad-a422-987c5e57a0fb · inbound

ZeroFlow: Overcoming Catastrophic Forgetting is Easier than You Think cites this paper.

ZeroFlow: Overcoming Catastrophic Forgetting is Easier than You Think Continual Learning of Large Language Models: A Comprehensive Survey

Reference 11

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no resolver link, observed 2026-08-10T22:41:42.407119Z

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source=pdf_text observed=2026-08-10T22:41:42.407119Z digest=sha256:f8c5fc8f6bcb9fbd4ed81d92003116441a5ad23db2479c1bd21918b0070f933c

Observation f3566798-edf3-4093-8407-d2357e65560f · inbound

Improving GenIR Systems Based on User Feedback cites this paper.

Improving GenIR Systems Based on User Feedback Continual Learning of Large Language Models: A Comprehensive Survey

Reference 76

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no resolver link, observed 2026-08-10T22:06:25.847908Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:06:25.847908Z digest=sha256:48ce4496169d18edb12efc6f7bfb0887f6998746dc85e9423c9d06e65522e408

Observation 8dc2fd5b-f86c-4152-9987-821493238dad · inbound

Enhancing Retrieval-Augmented Generation: A Study of Best Practices cites this paper.

Enhancing Retrieval-Augmented Generation: A Study of Best Practices Continual Learning of Large Language Models: A Comprehensive Survey

Reference 35

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no resolver link, observed 2026-08-10T20:46:57.022383Z

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source=arxiv_source observed=2026-08-10T20:46:57.022383Z digest=sha256:bea9ed13ce552fc1a5e4ab07743f16c2c3e0ab1f8a41b320d11e05cae298d948

Observation d6b7f3a3-1376-4f5c-9496-6f7e337d1309 · inbound

Continually Evolved Multimodal Foundation Models for Cancer Prognosis cites this paper.

Continually Evolved Multimodal Foundation Models for Cancer Prognosis Continual Learning of Large Language Models: A Comprehensive Survey

Reference 49

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source=pdf_text observed=2026-08-10T00:29:02.006147Z digest=sha256:e40be67fc62dea48c0d9bf11832db1f43b82573ce5aebd1f24e3853a07902a2a

Observation b509e789-60c7-4d04-b561-ddbda7c42535 · inbound

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning cites this paper.

Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning Continual Learning of Large Language Models: A Comprehensive Survey

Reference 167

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verified exact
arxiv_id, observed 2026-05-23T04:32:32.775456Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-23T04:30:38.804702Z digest=sha256:d19aa713c70fb0a6301f42a9fd1a4f55a1560952c4ac8820ba399cefb7f4edd5

Observation daa22cd9-8fe2-42e5-9bea-c3920abb2aef · inbound

Franken-Adapter: Cross-Lingual Adaptation of LLMs by Embedding Surgery cites this paper.

Franken-Adapter: Cross-Lingual Adaptation of LLMs by Embedding Surgery Continual Learning of Large Language Models: A Comprehensive Survey

Reference 11

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no resolver link, observed 2026-08-08T11:05:43.601057Z

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source=pdf_text observed=2026-08-08T11:05:43.601057Z digest=sha256:94bad75e683e7f713287b01e121650fa62195d05a906c4842fb100ce93079d58

Observation a3132390-4c37-406f-8e3b-d2a56e2b0a33 · inbound

From RAG to Memory: Non-Parametric Continual Learning for Large Language Models cites this paper.

From RAG to Memory: Non-Parametric Continual Learning for Large Language Models Continual Learning of Large Language Models: A Comprehensive Survey

Reference 7

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arxiv_id, observed 2026-05-17T01:36:19.849329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-17T01:36:19.795644Z digest=sha256:6b13dbae84ca31cd768b6c1be27eb391ee4af9504d490f85b7975c9b320edb8a

Observation 545850d2-c155-4d66-b91d-d078b2b5be0b · inbound

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training cites this paper.

T2I-ConBench: Text-to-Image Benchmark for Continual Post-training Continual Learning of Large Language Models: A Comprehensive Survey

Reference 26

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no resolver link, observed 2026-08-07T14:55:54.664729Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:55:54.664729Z digest=sha256:1a4ce98216df5486aac9c3c2d25f64af3dd4082982bf97bbad2b9d584de1d321

Observation dd9d3501-4338-42c2-9a40-000fe3cfd09c · inbound

Towards Objective Fine-tuning: How LLMs' Prior Knowledge Causes Potential Poor Calibration? cites this paper.

Towards Objective Fine-tuning: How LLMs' Prior Knowledge Causes Potential Poor Calibration? Continual Learning of Large Language Models: A Comprehensive Survey

Reference 33

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source=arxiv_source observed=2026-08-07T13:51:12.793920Z digest=sha256:fc3b591820d88ebc69dfad2b86f1f19387bdb8ca436ba9a5e08ed6d1bf62e453

Observation 173ef998-a96c-4288-893c-51ec30484503 · inbound

From Knowledge to Noise: CTIM-Rover and the Pitfalls of Episodic Memory in Software Engineering Agents cites this paper.

From Knowledge to Noise: CTIM-Rover and the Pitfalls of Episodic Memory in Software Engineering Agents Continual Learning of Large Language Models: A Comprehensive Survey

Reference 2017

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source=pdf_text observed=2026-08-07T12:49:58.983895Z digest=sha256:dcd014b950f624978addc3fafd686db6478974872333d2a8d7382d8c6e983612

Observation 0c8b633c-188f-42b5-a35d-2955b4f54253 · inbound

Bridging the Gap: From Ad-hoc to Proactive Search in Conversations cites this paper.

Bridging the Gap: From Ad-hoc to Proactive Search in Conversations Continual Learning of Large Language Models: A Comprehensive Survey

Reference 88

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source=pdf_text observed=2026-08-07T11:58:30.245048Z digest=sha256:dfd81ccdd854cc5f94e0b7eef2105af94bd0110a56aec9959121a5d40890bbcd

Observation 2c331c91-631c-4af5-b869-baa82fe3d10c · inbound

The Future of Continual Learning in the Era of Foundation Models: Three Key Directions cites this paper.

The Future of Continual Learning in the Era of Foundation Models: Three Key Directions Continual Learning of Large Language Models: A Comprehensive Survey

Reference 9

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no resolver link, observed 2026-08-07T11:10:09.704815Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:10:09.704815Z digest=sha256:6e07c902ef5ce38891e465e12fa5f6c2a6ee0027306b1311b930e16ef4bc939c

Observation 02a7be75-45b9-434b-a160-8fc78a8b70b5 · inbound

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond cites this paper.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Continual Learning of Large Language Models: A Comprehensive Survey

Reference 185

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no resolver link, observed 2026-08-07T00:40:31.606004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:40:31.606004Z digest=sha256:37670e49514df6b40ab2a2acaae303faf534653dbaadfc47519d68306378ef94

Observation a40be9ca-bd43-43c5-9d58-c61a669f49fd · inbound

SEAT: Sparse Entity-Aware Tuning for Knowledge Adaptation while Preserving Epistemic Abstention cites this paper.

SEAT: Sparse Entity-Aware Tuning for Knowledge Adaptation while Preserving Epistemic Abstention Continual Learning of Large Language Models: A Comprehensive Survey

Reference 11

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arxiv_id, observed 2026-05-19T09:37:14.185282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-19T09:34:24.194855Z digest=sha256:d3f09b3cfe2335f046381129f0c9d85dd5589be53e3d160e199116c8b53c2df3

Observation d27f66ef-674d-47ad-9826-b7b39c8ef32e · inbound

Minifinetuning: Low-Data Generation Domain Adaptation through Corrective Self-Distillation cites this paper.

Minifinetuning: Low-Data Generation Domain Adaptation through Corrective Self-Distillation Continual Learning of Large Language Models: A Comprehensive Survey

Reference 5

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:40:22.228275Z digest=sha256:41d9d4a9a5709cb126031b0e9286f4c0fc3e65dee6af996da82a300805336aa5

Observation b32e0bf4-63ca-49db-816f-2acdea6583fd · inbound

Continual Gradient Low-Rank Projection Fine-Tuning for LLMs cites this paper.

Continual Gradient Low-Rank Projection Fine-Tuning for LLMs Continual Learning of Large Language Models: A Comprehensive Survey

Reference 33

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no resolver link, observed 2026-08-06T20:35:04.495349Z

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source=arxiv_source observed=2026-08-06T20:35:04.495349Z digest=sha256:dd8f76c17e5078685919fb58f599d19156357a6ff150a2df5b18749b384560ff

Observation 9833c31c-a62f-4055-b887-2e8f76993ae5 · inbound

Improving MLLM's Document Image Machine Translation via Synchronously Self-reviewing Its OCR Proficiency cites this paper.

Improving MLLM's Document Image Machine Translation via Synchronously Self-reviewing Its OCR Proficiency Continual Learning of Large Language Models: A Comprehensive Survey

Reference 29

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no resolver link, observed 2026-08-06T18:28:13.014475Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:28:13.014475Z digest=sha256:ecd8b97a78ff9bf6753dbae11c60b7b5e8e0946c0b4ddebf2e265c218bf8e29e

Observation 4aaeacdd-b6ac-4123-b652-20f406154120 · inbound

GeRe: Towards Efficient Anti-Forgetting in Continual Learning of LLM via General Samples Replay cites this paper.

GeRe: Towards Efficient Anti-Forgetting in Continual Learning of LLM via General Samples Replay Continual Learning of Large Language Models: A Comprehensive Survey

Reference 3

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source=pdf_text observed=2026-08-05T23:54:23.113997Z digest=sha256:1f5dd93992521c2795f88189274962662ba733c1065e121d73e46f87cf5e7cf7

Observation a12959f0-7b28-4cd4-b13f-f5dc42eef4a5 · inbound

Enhancing Memory Recall in LLMs with Gauss-Tin: A Hybrid Instructional and Gaussian Replay Approach cites this paper.

Enhancing Memory Recall in LLMs with Gauss-Tin: A Hybrid Instructional and Gaussian Replay Approach Continual Learning of Large Language Models: A Comprehensive Survey

Reference 2022

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no resolver link, observed 2026-08-05T21:04:56.078739Z

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source=pdf_text observed=2026-08-05T21:04:56.078739Z digest=sha256:c1ef6da88ec023d118567bea79d5087f3174902633edfcde9bd671d639be5020

Observation c0c0b0eb-f2bd-4eae-a384-4abc1e19f4a5 · inbound

SelfAug: Mitigating Catastrophic Forgetting in Retrieval-Augmented Generation via Distribution Self-Alignment cites this paper.

SelfAug: Mitigating Catastrophic Forgetting in Retrieval-Augmented Generation via Distribution Self-Alignment Continual Learning of Large Language Models: A Comprehensive Survey

Reference 67

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no resolver link, observed 2026-08-05T10:34:45.963993Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T10:34:45.963993Z digest=sha256:34134aa72d85b0703a9123b08e990eedc518c28483eb82355004b44c3fdd0b67

Observation 9332d627-5c56-42a2-849e-24ba071000fd · inbound

Retaining by Doing: The Role of On-Policy Data in Mitigating Forgetting cites this paper.

Retaining by Doing: The Role of On-Policy Data in Mitigating Forgetting Continual Learning of Large Language Models: A Comprehensive Survey

Reference 33

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no resolver link, observed 2026-08-04T08:49:34.024285Z

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source=arxiv_source observed=2026-08-04T08:49:34.024285Z digest=sha256:3429e994e255acd49ec5a6d8acbf1221bc306e09e08493248fab5ee32ff043c4

Observation e3441ddc-d4e8-4819-bb78-09a7434372a8 · inbound

Towards Scalable Lifelong Knowledge Editing with Selective Knowledge Suppression cites this paper.

Towards Scalable Lifelong Knowledge Editing with Selective Knowledge Suppression Continual Learning of Large Language Models: A Comprehensive Survey

Reference 39

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arxiv_id, observed 2026-05-11T13:21:05.177469Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-05-10T01:56:27.674057Z digest=sha256:678905d3a52b574127f16af38acf6583ff518395f5b2e72667b7145c08723181

Observation 1194d303-03be-4908-95c8-8e5cb486b316 · inbound

MADS: Model-Aware Diverse Core Set Selection for Instruction Tuning cites this paper.

MADS: Model-Aware Diverse Core Set Selection for Instruction Tuning Continual Learning of Large Language Models: A Comprehensive Survey

Reference 4

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arxiv_id, observed 2026-07-01T19:16:01.030698Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-06-28T22:53:48.040141Z digest=sha256:3333985e8ea5820f12804b5fa5cd8e0b85c66f064d18240d0301dbd98a0e930c

Observation b6ee9206-41ac-4c8e-a221-d98d2aa9cb23 · inbound

A Local Perturbation Theory for Cross-Domain Interference and Recovery in Multi-Domain RL cites this paper.

A Local Perturbation Theory for Cross-Domain Interference and Recovery in Multi-Domain RL Continual Learning of Large Language Models: A Comprehensive Survey

Reference 28

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verified exact
arxiv_id, observed 2026-07-01T22:16:15.926927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-06-28T15:37:35.932354Z digest=sha256:7a08eb2b53b25355c87fa47dc057fbfe05527efc86eca945a7886654ecb39d80

Observation 91ef92c5-da53-4a8e-ad9f-bffbcf9b5989 · inbound

Catastrophic Forgetting is Low-Rank: A Function-Space Theory for Continual Adaptation cites this paper.

Catastrophic Forgetting is Low-Rank: A Function-Space Theory for Continual Adaptation Continual Learning of Large Language Models: A Comprehensive Survey

Reference 11

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verified exact
arxiv_id, observed 2026-07-03T20:08:56.177017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-06-27T01:37:06.730611Z digest=sha256:8f9768ac4299baa7f12e10923ae0a072907e2e665335ac4048d1b22bd48a85f0

Observation 8414fc18-236b-4113-92bd-49752098a379 · inbound

User as Engram: Internalizing Per-User Memory as Local Parametric Edits cites this paper.

User as Engram: Internalizing Per-User Memory as Local Parametric Edits Continual Learning of Large Language Models: A Comprehensive Survey

Reference 87

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verified exact
arxiv_id, observed 2026-07-04T01:09:19.493740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-06-26T20:37:01.382431Z digest=sha256:4616d52c3732e177be74b1fbb3ebb3a6ed7d157e2ea823cf80409908c321f8db

Observation bce83926-e16b-4251-9817-baec6046f051 · inbound

Repeated post-training is not Self-improving: Diagnosing Scientific Amnesia in Continual DPO Pipelines cites this paper.

Repeated post-training is not Self-improving: Diagnosing Scientific Amnesia in Continual DPO Pipelines Continual Learning of Large Language Models: A Comprehensive Survey

Reference 7

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metadata mismatch
arxiv_id, observed 2026-07-04T00:29:15.813475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-06-26T21:12:05.209407Z digest=sha256:7c0f62f0b8ffc71d2bc8c7ccf472f5e3a7b3c675de6b6dec6a437691276c5355

Observation a1479995-2e93-4a4b-b222-8505cda6f74c · inbound

Assert, don't describe: Linguistic features that shift LLM reasoning about animal welfare cites this paper.

Assert, don't describe: Linguistic features that shift LLM reasoning about animal welfare Continual Learning of Large Language Models: A Comprehensive Survey

Reference 11

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metadata mismatch
arxiv_id, observed 2026-07-01T08:05:31.129123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=arxiv_source observed=2026-07-01T08:00:40.906200Z digest=sha256:8c019d534953082fe66d99672ad1a7a9602840557a75b8c517b4054b6a94849f

Observation 73b8ebf3-d160-4fa8-860d-b5341ee0a915 · inbound

SOS-LoRA: Static Orthogonal-Subspace Low-Rank Adaptation with Fixed Multi-Scale Scaling cites this paper.

SOS-LoRA: Static Orthogonal-Subspace Low-Rank Adaptation with Fixed Multi-Scale Scaling Continual Learning of Large Language Models: A Comprehensive Survey

Reference 91

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no resolver link, observed 2026-08-02T09:51:03.489576Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T09:51:03.489576Z digest=sha256:fdeb97bbe84bf1f30b699fc9affebb47e8e69ae5866dc91b658c653729b434c9

Observation 9889a54c-af73-4b5c-9ba7-f893384671f4 · inbound

Latent-LoRA: Compact Latent-Space Adapters with Gradient-Free Routing for Continual Learning cites this paper.

Latent-LoRA: Compact Latent-Space Adapters with Gradient-Free Routing for Continual Learning Continual Learning of Large Language Models: A Comprehensive Survey

Reference 2

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no resolver link, observed 2026-07-30T10:55:15.286541Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-30T10:55:15.286541Z digest=sha256:6f4dc125345db19eb7c9a8b75dd32a6704e8efc6446e9dd8d82fb7388f24dd11