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Paper Citation Record · LEDGER

Continual Learning for Large Language Models: A Survey

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 59 inbound Pith citation observations for arXiv:2402.01364.

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

pith.paper-citation-record.v1
2402.01364 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 59 of 59 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:50:27.926559Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:29:15.805243Z

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 a366d8ec-e69d-4caa-aa29-b0e10018d33f · inbound

Plasticity Loss in Deep Reinforcement Learning: A Survey cites this paper.

Plasticity Loss in Deep Reinforcement Learning: A Survey Continual Learning for Large Language Models: A Survey

Reference 108

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arxiv_id, observed 2026-05-23T18:03:18.182461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation c4bf6a63-b492-4314-9bd5-081f96ecbcc0 · inbound

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods cites this paper.

LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods Continual Learning for Large Language Models: A Survey

Reference 253

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arxiv_id, observed 2026-05-11T23:08:35.702804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-11T23:08:34.312466Z digest=sha256:3e47a410077dc41eb80458adfe2b60e7bb05f385bf68dc74b9f1e50cac41ed1c

Observation e28803ca-25e4-430f-aac4-d8c461f338ca · inbound

How Vision-Language Tasks Benefit from Large Pre-trained Models: A Survey cites this paper.

How Vision-Language Tasks Benefit from Large Pre-trained Models: A Survey Continual Learning for Large Language Models: A Survey

Reference 220

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T18:11:55.203342Z digest=sha256:0af45c56f2ef97ccd1be0ff45c170a6480b5034ea05a30c5997932bd07fac3e3

Observation 6975edb4-d576-4d84-a91c-2803ad7bac2a · inbound

Revisiting Data Analysis with Pre-trained Foundation Models cites this paper.

Revisiting Data Analysis with Pre-trained Foundation Models Continual Learning for Large Language Models: A Survey

Reference 160

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source=pdf_text observed=2026-08-10T22:26:14.294987Z digest=sha256:e74bcdc8e86f1895e2bdac9160ccd7ffe31ba8fe5ef88b6c5be496ca1ed88cf7

Observation 908fbb56-e647-4d9e-b4a9-0412f9ed0cc8 · inbound

Improving GenIR Systems Based on User Feedback cites this paper.

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

Reference 75

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source=pdf_text observed=2026-08-10T22:06:25.840198Z digest=sha256:9af1634ef8fee178175f30a711a0c848ac21949d9055bf2afb059ce7e6651886

Observation 5d48f7b6-09f7-4fd9-8bbe-81c2b87f0ca2 · inbound

TiEBe: Tracking Language Model Recall of Notable Worldwide Events Through Time cites this paper.

TiEBe: Tracking Language Model Recall of Notable Worldwide Events Through Time Continual Learning for Large Language Models: A Survey

Reference 27

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no resolver link, observed 2026-08-10T20:43:45.427120Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:43:45.427120Z digest=sha256:39c42c840555ceeb5c15584b298925c967554f01490be0bc02a9ced763dc92b9

Observation 011dbd7e-2fee-4b6b-bbb8-e85c3bc0c80a · inbound

Parametric Retrieval Augmented Generation cites this paper.

Parametric Retrieval Augmented Generation Continual Learning for Large Language Models: A Survey

Reference 54

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source=pdf_text observed=2026-08-10T13:55:04.123475Z digest=sha256:cea2071facd34aeb21f4738e26e423cdce6d602b167f6230d1f836ad0bdef695

Observation c7cb4721-32a7-49f0-92d8-680c67d49870 · inbound

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

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

Reference 50

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source=pdf_text observed=2026-08-10T00:29:02.009153Z digest=sha256:62fcf996dab99d34a04410a51a757c2a0337c706849ce519005a3788b330a5c5

Observation 93c68484-0d6a-476d-8e7d-5a80e8661979 · inbound

Scalable Framework for Classifying AI-Generated Content Across Modalities cites this paper.

Scalable Framework for Classifying AI-Generated Content Across Modalities Continual Learning for Large Language Models: A Survey

Reference 24

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no resolver link, observed 2026-08-09T19:17:52.113052Z

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source=pdf_text observed=2026-08-09T19:17:52.113052Z digest=sha256:175303c7653f541b3e22f6e551ee18d78502a8490d836ec8a189df0a34d3d380

Observation 366b7fd0-d338-4d61-8664-b8213d15b214 · inbound

Efficient Few-Shot Continual Learning in Vision-Language Models cites this paper.

Efficient Few-Shot Continual Learning in Vision-Language Models Continual Learning for Large Language Models: A Survey

Reference 44

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no resolver link, observed 2026-08-08T23:37:28.765591Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T23:37:28.765591Z digest=sha256:9b02dae7b9dac9f1f1ba57398165f998eb9999c9caae3a27e52fbc62ccdad1cc

Observation 0c8805af-1584-4276-9ae2-cf5b9fbdd591 · inbound

LongReD: Mitigating Short-Text Degradation of Long-Context Large Language Models via Restoration Distillation cites this paper.

LongReD: Mitigating Short-Text Degradation of Long-Context Large Language Models via Restoration Distillation Continual Learning for Large Language Models: A Survey

Reference 72

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no resolver link, observed 2026-08-08T13:02:23.620761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T13:02:23.620761Z digest=sha256:5ef6728adbfa569e5b1d56a87d18b240262564488c8e9982862aa269c622aa3e

Observation 7c7d0086-2289-4c4b-ab98-b24412aa91f7 · inbound

Meta-Thinking in LLMs via Multi-Agent Reinforcement Learning: A Survey cites this paper.

Meta-Thinking in LLMs via Multi-Agent Reinforcement Learning: A Survey Continual Learning for Large Language Models: A Survey

Reference 47

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no resolver link, observed 2026-08-16T11:50:27.926559Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:50:27.926559Z digest=sha256:8f980576a541503adb6ab4b5cd42c0ec825a26c7d51fb1205bf1edf7b49ee584

Observation 4f6f4673-3fc7-4e9f-9277-3b3a72a70db5 · inbound

Multimodal Large Language Models for Medicine: A Comprehensive Survey cites this paper.

Multimodal Large Language Models for Medicine: A Comprehensive Survey Continual Learning for Large Language Models: A Survey

Reference 194

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no resolver link, observed 2026-08-16T05:32:54.693561Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T05:32:54.693561Z digest=sha256:7987fd80094e615c357539159583b66384122d908a9c673e8288b63f0a31dc7e

Observation baa1544d-9a9e-4ff5-8665-a75369a99c71 · inbound

SEFE: Superficial and Essential Forgetting Eliminator for Multimodal Continual Instruction Tuning cites this paper.

SEFE: Superficial and Essential Forgetting Eliminator for Multimodal Continual Instruction Tuning Continual Learning for Large Language Models: A Survey

Reference 61

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no resolver link, observed 2026-08-16T00:53:21.130036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:53:21.130036Z digest=sha256:9fd58e63137c1a27568d9868c7e24b873fb0395face389b9fdab1a7382bbb57f

Observation 7c0c2e9b-2268-47e9-b0b9-d84d0a005395 · inbound

Aligning Large Language Models with Healthcare Stakeholders: A Pathway to Trustworthy AI Integration cites this paper.

Aligning Large Language Models with Healthcare Stakeholders: A Pathway to Trustworthy AI Integration Continual Learning for Large Language Models: A Survey

Reference 2021

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no resolver link, observed 2026-08-16T04:33:20.383737Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T04:33:20.383737Z digest=sha256:f0a794036514b6b4838bc220d8046f7ae737aee77754a1f86a51e611d3fb9c0b

Observation f2549d4f-86c9-4f5e-bba8-49617eedade3 · inbound

Continuous Self-Improvement of Large Language Models by Test-time Training with Verifier-Driven Sample Selection cites this paper.

Continuous Self-Improvement of Large Language Models by Test-time Training with Verifier-Driven Sample Selection Continual Learning for Large Language Models: A Survey

Reference 16

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no resolver link, observed 2026-08-07T14:17:44.344757Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:17:44.344757Z digest=sha256:04c3017fb238e5489737a3db44adbe7a1f71a43155980d3fd67be05d60b6d73b

Observation 456c8a55-bdc7-4a0e-aca0-dcc8c5803e59 · inbound

Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn cites this paper.

Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn Continual Learning for Large Language Models: A Survey

Reference 19

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no resolver link, observed 2026-08-07T12:07:25.660754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:07:25.660754Z digest=sha256:05a257d6b08e5331f5c5e4a2346b65f085e0b87ceefda4a6b33a77b71c5ffc42

Observation 563017a7-53f1-4f38-8427-44b697a05264 · inbound

Pitfalls in Evaluating Language Model Forecasters cites this paper.

Pitfalls in Evaluating Language Model Forecasters Continual Learning for Large Language Models: A Survey

Reference 34

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no resolver link, observed 2026-08-07T12:03:13.143938Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T12:03:13.143938Z digest=sha256:41df5defbcf5207c33687cd919140369427f1864de0633c71691301d2ded4e0e

Observation 726e082f-ed53-489c-8209-30c6a92a0c51 · inbound

Continual Speech Learning with Fused Speech Features cites this paper.

Continual Speech Learning with Fused Speech Features Continual Learning for Large Language Models: A Survey

Reference 8

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no resolver link, observed 2026-08-07T11:46:58.525073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:46:58.525073Z digest=sha256:25b0f37c546323725c22d522bc6dcaf3b96cc336384089e74d610a0e184c966d

Observation e6a6860c-0706-4fb5-9b00-4d29d8717c77 · inbound

Is Extending Modality The Right Path Towards Omni-Modality? cites this paper.

Is Extending Modality The Right Path Towards Omni-Modality? Continual Learning for Large Language Models: A Survey

Reference 50

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no resolver link, observed 2026-08-07T11:36:40.908092Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T11:36:40.908092Z digest=sha256:9b1f4d9610f848d10da8ce4dfadf3abea72897c46b198e6a45a3380929bf7a49

Observation ab1cc3b8-1773-4cb9-915d-ca237cb47720 · inbound

Enhancing Multimodal Continual Instruction Tuning with BranchLoRA cites this paper.

Enhancing Multimodal Continual Instruction Tuning with BranchLoRA Continual Learning for Large Language Models: A Survey

Reference 42

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no resolver link, observed 2026-08-07T12:09:07.878789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:07.878789Z digest=sha256:7419a059f43416a55aec1c156b7cc907d2fef7f0aa3517f377ee69b67c771850

Observation a4f34592-cbbc-4a33-8ab8-1bb339c86fae · 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 for Large Language Models: A Survey

Reference 67

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no resolver link, observed 2026-08-07T11:10:14.790774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:10:14.790774Z digest=sha256:043558c36d0f49d677eeabe536619b347a21a9c293b1316dcf3d9c04af6ebc36

Observation be5740b2-467d-4104-8125-18f233b571b6 · inbound

Table-r1: Self-supervised and Reinforcement Learning for Program-based Table Reasoning in Small Language Models cites this paper.

Table-r1: Self-supervised and Reinforcement Learning for Program-based Table Reasoning in Small Language Models Continual Learning for Large Language Models: A Survey

Reference 39

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no resolver link, observed 2026-08-07T06:03:45.938974Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:03:45.938974Z digest=sha256:61623556804031d330e68c116bcd6cda75ed0cf57a41e991f757b1452b7d613d

Observation 930d14a3-00b3-4f7d-934b-e96036f0b139 · inbound

A Systematic Review of Poisoning Attacks Against Large Language Models cites this paper.

A Systematic Review of Poisoning Attacks Against Large Language Models Continual Learning for Large Language Models: A Survey

Reference 42

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no resolver link, observed 2026-08-07T05:59:33.962759Z

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source=pdf_text observed=2026-08-07T05:59:33.962759Z digest=sha256:3a7ddf8fde5d5bbf010ae88bf0ec674d859b6947ce45cf373af5448b5c235f63

Observation cd3e91e7-638d-4646-b709-6e728d70096d · 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 for Large Language Models: A Survey

Reference 215

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no resolver link, observed 2026-08-07T00:40:34.109256Z

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source=pdf_text observed=2026-08-07T00:40:34.109256Z digest=sha256:697282d5dae0f5a022e4ff1e6f3114331842f3f5cf7bd664940d99c69a9640ae

Observation 10af06ab-1c71-4686-9b39-c95862ac5a4d · inbound

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence cites this paper.

Dynamic Context-oriented Decomposition for Task-aware Low-rank Adaptation with Less Forgetting and Faster Convergence Continual Learning for Large Language Models: A Survey

Reference 75

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source=pdf_text observed=2026-08-07T00:43:51.513729Z digest=sha256:9db7802e1ef301a2c49561f584010e065e2d6e146d337714bea727cfa78f30ba

Observation 2b558d5a-3981-440f-a4e8-4f2e676fe004 · inbound

Continual Learning with Columnar Spiking Neural Networks cites this paper.

Continual Learning with Columnar Spiking Neural Networks Continual Learning for Large Language Models: A Survey

Reference 16

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no resolver link, observed 2026-08-15T19:16:40.804190Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T19:16:40.804190Z digest=sha256:8bb61733c5cae59ad2c0cf0e825d413fea0408f5638c0afb455cd77c2c92b920

Observation 9e3fc6f8-f047-4105-a42d-6c75416d9d4e · inbound

Bisecle: Binding and Separation in Continual Learning for Video Language Understanding cites this paper.

Bisecle: Binding and Separation in Continual Learning for Video Language Understanding Continual Learning for Large Language Models: A Survey

Reference 31

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no resolver link, observed 2026-08-06T21:20:09.686126Z

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source=pdf_text observed=2026-08-06T21:20:09.686126Z digest=sha256:b17ed78f4b60033034adeaaf7747cf4b7ed1bbad6d1dbeb290598b55df221548

Observation 8c2097e5-e5b9-4a6e-9836-95c69bde9327 · inbound

EMERGE: A Benchmark for Updating Knowledge Graphs with Emerging Textual Knowledge cites this paper.

EMERGE: A Benchmark for Updating Knowledge Graphs with Emerging Textual Knowledge Continual Learning for Large Language Models: A Survey

Reference 70

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verified exact
arxiv_id, observed 2026-05-19T06:07:07.552746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-19T06:03:40.874012Z digest=sha256:58e816ec75e475e40f91b240a304c93c10f1a463dfeb2a5cb6a2b8973a21ad77

Observation 5ea87402-3417-49e2-a15c-424e739cb0c9 · 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 for Large Language Models: A Survey

Reference 83

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no resolver link, observed 2026-08-05T10:34:46.795186Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T10:34:46.795186Z digest=sha256:1aeafe4aba5e2a2975a016f137e267f5ba03b7d359100de1f887b20b29fe4be5

Observation 28f4312b-c361-4034-9a6a-89568767f33f · inbound

LifeAlign: Lifelong Alignment for Large Language Models with Memory-Augmented Focalized Preference Optimization cites this paper.

LifeAlign: Lifelong Alignment for Large Language Models with Memory-Augmented Focalized Preference Optimization Continual Learning for Large Language Models: A Survey

Reference 31

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arxiv_id, observed 2026-05-18T14:51:30.407863Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-18T14:46:45.598080Z digest=sha256:08ad2f252a45546fef8e6543f6826d7b16aa59b7e997897fbf5a55034609202c

Observation d2e18458-78fa-4378-9fe4-b6d48b571ed4 · 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 for Large Language Models: A Survey

Reference 40

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no resolver link, observed 2026-08-04T08:49:34.512955Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T08:49:34.512955Z digest=sha256:b0b742027970178ce55687baa6af7f815190b1ead37fc1e84512f31e6743db77

Observation 7b60eb24-951e-4d69-a78c-9266cfdd0597 · inbound

Preconditioned Test-Time Adaptation for Out-of-Distribution Debiasing in Narrative Generation cites this paper.

Preconditioned Test-Time Adaptation for Out-of-Distribution Debiasing in Narrative Generation Continual Learning for Large Language Models: A Survey

Reference 11

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metadata mismatch
arxiv_id, observed 2026-05-15T12:15:34.534939Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-15T12:13:24.420641Z digest=sha256:dac412dc99bbfbc06a5354c1a132cc1b6158fcc59795cdfca0c186aa0d7b7c83

Observation 54b9c9d7-a539-4086-b215-ee252f95fea7 · inbound

Preconditioned Test-Time Adaptation for Out-of-Distribution Debiasing in Narrative Generation cites this paper.

Preconditioned Test-Time Adaptation for Out-of-Distribution Debiasing in Narrative Generation Continual Learning for Large Language Models: A Survey

Reference 11

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no resolver link, observed 2026-08-03T02:35:46.214786Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T02:35:46.214786Z digest=sha256:682d4c80681e1af0b352db085733825f1b76ba1c6c4b8000a0aeae39e574327c

Observation fa03ab17-8281-456c-b66c-2a337552bed6 · inbound

The Agentification of Scientific Research: A Physicist's Perspective cites this paper.

The Agentification of Scientific Research: A Physicist's Perspective Continual Learning for Large Language Models: A Survey

Reference 31

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arxiv_id, observed 2026-05-10T11:15:11.126259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-10T11:12:32.165086Z digest=sha256:68e8adacfe13f126ccfe5c0fd0f2e0c2ae0ba96e06c118cf66d29b4da773e195

Observation db95e6fe-35b0-4dd0-9d6f-edc70e1039b2 · inbound

Shortcut Solutions Learned by Transformers Impair Continual Compositional Reasoning cites this paper.

Shortcut Solutions Learned by Transformers Impair Continual Compositional Reasoning Continual Learning for Large Language Models: A Survey

Reference 15

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verified exact
arxiv_id, observed 2026-05-11T18:06:05.490509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-08T16:42:08.322419Z digest=sha256:e06c9a9b7ddffd3ffa7e1b6520c120f264ec94f0899a1d792df04641054ac59f

Observation 3f515dd3-2789-41dc-bd29-38f0e1c64013 · inbound

Phoenix-VL 1.5 Medium Technical Report cites this paper.

Phoenix-VL 1.5 Medium Technical Report Continual Learning for Large Language Models: A Survey

Reference 24

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metadata mismatch
arxiv_id, observed 2026-05-12T06:01:24.882774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-12T04:41:27.144815Z digest=sha256:ad4e11721686cbb79c5db6373adf07c82ef1fbe1eb5ead2c924db7327ccc1130

Observation 2ced553a-6262-4b05-a0a2-db8638a237f9 · inbound

Dynamic Cross-Modal Prompt Generation for Multimodal Continual Instruction Tuning cites this paper.

Dynamic Cross-Modal Prompt Generation for Multimodal Continual Instruction Tuning Continual Learning for Large Language Models: A Survey

Reference 43

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:21:25.195079Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-12T03:27:45.784361Z digest=sha256:a64fa8021e6f4a1cbee7a1ba25ea1244ae00aeefda5bcf8a2241d31b79c1449f

Observation 3f3b1322-ce79-46db-bdc2-666e0c76d7ff · inbound

From Text to Voice: A Reproducible and Verifiable Framework for Evaluating Tool Calling LLM Agents cites this paper.

From Text to Voice: A Reproducible and Verifiable Framework for Evaluating Tool Calling LLM Agents Continual Learning for Large Language Models: A Survey

Reference 43

Resolution
metadata mismatch
arxiv_id, observed 2026-05-21T08:49:53.642624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-21T08:45:56.550821Z digest=sha256:8db47960cefb7caf22e12dc2bdea2cd00073be87620dc16b973829d229563127

Observation b022a7f4-3761-46c0-ac90-1a1793432e62 · inbound

MeMo: Memory as a Model cites this paper.

MeMo: Memory as a Model Continual Learning for Large Language Models: A Survey

Reference 81

Resolution
verified exact
arxiv_id, observed 2026-05-15T03:19:43.451662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-15T03:17:23.202604Z digest=sha256:b6831b2ab00bb8ed77e594f39d827ae2133dde69775e06316d066867639f6733

Observation 2f75d670-cf81-4465-a3db-238bbb9110b0 · inbound

MeMo: Memory as a Model cites this paper.

MeMo: Memory as a Model Continual Learning for Large Language Models: A Survey

Reference 82

Resolution
verified exact
arxiv_id, observed 2026-05-21T08:39:53.689378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-21T08:36:31.022046Z digest=sha256:ce1787c04ea66e9bbec832e5676be0c36510caa149ebab51811fdf837a98e9c8

Observation 75deadf3-aa15-4bbc-9f59-e0fe92afc671 · inbound

Is One Score Enough? Rethinking the Evaluation of Sequentially Evolving LLM Memory cites this paper.

Is One Score Enough? Rethinking the Evaluation of Sequentially Evolving LLM Memory Continual Learning for Large Language Models: A Survey

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-19T16:47:40.484917Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-19T16:43:37.472644Z digest=sha256:f49874e317cbd1d697135dc1c533afcbc8d279af323cf83977b3d63ffe7e69a2

Observation 1d4def46-75f5-4171-a7f9-92dafd500dcb · inbound

MasFACT: Continual Multi-Agent Topology Learning via Geometry-Aware Posterior Transfer cites this paper.

MasFACT: Continual Multi-Agent Topology Learning via Geometry-Aware Posterior Transfer Continual Learning for Large Language Models: A Survey

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-20T14:38:21.612825Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-20T14:35:46.376752Z digest=sha256:6573b91735dd9ee82975d7476bf0215dc0f95723299cb276454e88d8d7198c14

Observation 0e0b418c-0ea1-42f1-94f0-5fc70f223110 · inbound

MasFACT: Continual Multi-Agent Topology Learning via Geometry-Aware Posterior Transfer cites this paper.

MasFACT: Continual Multi-Agent Topology Learning via Geometry-Aware Posterior Transfer Continual Learning for Large Language Models: A Survey

Reference 42

Resolution
unresolved
no resolver link, observed 2026-07-12T16:38:30.296706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T16:38:30.296706Z digest=sha256:3fd5b502794f007fa2dc968fbb46ab543b21f2374c7095d90c62192671698ba6

Observation efddcd3c-038b-4381-bd2f-b9666a90bfeb · inbound

Forgetting in Language Models: Capacity, Optimization, and Self-Generated Replay cites this paper.

Forgetting in Language Models: Capacity, Optimization, and Self-Generated Replay Continual Learning for Large Language Models: A Survey

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-06-29T23:24:01.944699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-29T23:15:45.174086Z digest=sha256:817db86a97cee3407850ed716da1853c8c99931a97be3f376e68a42505d13cef

Observation 11f9169f-12ac-42c4-983c-554a2773051e · 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 for Large Language Models: A Survey

Reference 5

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T19:16:01.026834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-28T22:53:48.040141Z digest=sha256:397e2f032ca3f0c273d42a298b6e3c8c09f49036c275df0413d9ebd75c357446

Observation 4c654f57-05d5-4083-8d32-931094b85822 · inbound

Rethinking Continual Experience Internalization for Self-Evolving LLM Agents cites this paper.

Rethinking Continual Experience Internalization for Self-Evolving LLM Agents Continual Learning for Large Language Models: A Survey

Reference 74

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T07:56:47.817667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-28T06:29:11.398007Z digest=sha256:ead6bd5b77901037528b61ae8ee6414a5f9e490da63aafde0213be93240f8934

Observation 7dc1f29e-3501-4036-b547-1dbac22bf3ed · inbound

RECAP: Regression Evaluation for Continual Adaptation of Prompts cites this paper.

RECAP: Regression Evaluation for Continual Adaptation of Prompts Continual Learning for Large Language Models: A Survey

Reference 19

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T12:06:56.294379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-28T02:24:52.140361Z digest=sha256:2bac0e0212a476b6969fbc8034cdf66d54f418d89182346bd9ab2b90c2c28c4e

Observation 9d0e9491-fb4b-48cc-916a-e5d72961f533 · inbound

Sparse Subspace-to-Expert Sharing for Task-Agnostic Continual Learning cites this paper.

Sparse Subspace-to-Expert Sharing for Task-Agnostic Continual Learning Continual Learning for Large Language Models: A Survey

Reference 11

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T16:57:10.231994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-27T22:15:36.264240Z digest=sha256:e10357a05ebc06956b5cace8c229e2df56f5010ebeb94c74d9cd4179ee05a069

Observation a875d461-13d3-4c59-93f0-3dfeb8f80d25 · 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 for Large Language Models: A Survey

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T00:29:15.808388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-26T21:12:05.209407Z digest=sha256:38e699d8835ad2fed01492b8d6faf3b99bbb56a09042dab23ac2d2b148777601

Observation 2b0648be-0ed1-4b3f-b7a8-bed24cfee717 · inbound

LLM Evolution as an Industry-Scale Ecosystem: A Lifecycle Perspective on Continual Learning cites this paper.

LLM Evolution as an Industry-Scale Ecosystem: A Lifecycle Perspective on Continual Learning Continual Learning for Large Language Models: A Survey

Reference 116

Resolution
verified exact
arxiv_id, observed 2026-07-03T16:48:39.951343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-27T05:02:18.347642Z digest=sha256:5d37a60d1359621c5c401c94e6945dac03f8880db931a927e999a8730dcf9ee6

Observation 2bb0b629-56ad-4bf3-a393-3ba9bac79889 · inbound

MedEvoEval: Evaluating Continual Evolution of Doctor Agents through Simulated Clinical Episodes cites this paper.

MedEvoEval: Evaluating Continual Evolution of Doctor Agents through Simulated Clinical Episodes Continual Learning for Large Language Models: A Survey

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-06-30T09:34:34.406343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-30T09:33:50.358159Z digest=sha256:39b519948e49909ef5167be35c978c3a2ee2b85f1056aaa27d16af60fecb4bbd

Observation 6838d90f-b5c3-4ccc-9964-7260f6369d19 · inbound

ReCoLoRA: Spectrum-Aware Recursive Consolidation for Continual LLM Fine-Tuning cites this paper.

ReCoLoRA: Spectrum-Aware Recursive Consolidation for Continual LLM Fine-Tuning Continual Learning for Large Language Models: A Survey

Reference 5

Resolution
unresolved
no resolver link, observed 2026-07-11T23:28:26.009765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T23:28:26.009765Z digest=sha256:caed40a8636fcb9c44853239faee627c371a4efd8c83419ff05ed103651f9936

Observation 82a4a779-bf7c-4ec4-8288-907dcc772307 · 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 for Large Language Models: A Survey

Reference 220

Resolution
unresolved
no resolver link, observed 2026-08-02T09:51:03.782356Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T09:51:03.782356Z digest=sha256:d0630221c8d399e53ef9760db33e49b2eb70af1a87668a979b7609e2e1d54e1a

Observation 44ce3f33-e5bb-444d-b68f-21fc76dd0456 · inbound

How LLM Task-Adaptation Reshapes Alignment: A Multi-dimensional Study of Behavioral and Representational Drift cites this paper.

How LLM Task-Adaptation Reshapes Alignment: A Multi-dimensional Study of Behavioral and Representational Drift Continual Learning for Large Language Models: A Survey

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-02T07:44:11.986628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T07:44:11.986628Z digest=sha256:05790b952861862ec70ad0dc16b8d29c80581218d73f57acdc764f9f68d6962a

Observation 10385ec2-f5a9-4b91-886c-e58a213087fe · inbound

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI cites this paper.

A Taxonomy of Cognitive Capability Gaps in Generative and Agentic AI Continual Learning for Large Language Models: A Survey

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-04T04:52:56.255590Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T04:52:56.255590Z digest=sha256:257c54659f1508a73cf5e05c3710c592403e926e49fcb3d096df5b431f074fd3

Observation 2e8f8ff6-b6dc-471e-a402-a339a2980f05 · inbound

Continual Learning in Transition cites this paper.

Continual Learning in Transition Continual Learning for Large Language Models: A Survey

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T12:23:57.796801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:23:57.796801Z digest=sha256:d491498c793d46564f62740c85f394b5694bd2bfa6a97c2080585f707ccd9c90

Observation 5e94c368-a56c-4e45-b11b-def480831907 · inbound

Continual Learning in Transition cites this paper.

Continual Learning in Transition Continual Learning for Large Language Models: A Survey

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-15T14:38:34.687532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:38:34.687532Z digest=sha256:c27c70e087a977b10d820ea1b58d82ccd2272726a5b0821c16823c4084456b83

Observation 5ca98dd9-f3cb-4b24-83a1-e65827ae1da4 · inbound

TELLME: Test-Enhanced Learning for Language Model Enrichment cites this paper.

TELLME: Test-Enhanced Learning for Language Model Enrichment Continual Learning for Large Language Models: A Survey

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-16T00:31:45.562851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:31:45.562851Z digest=sha256:4212ddd156546a8cbb6f1c409723dc663a009d9cd1815120cd46386c162d0c8d