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Paper Citation Record · LEDGER

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond

As of 7 August 2026, this Paper Citation Record lists 100 of 278 outbound references and 5 inbound Pith citation observations for arXiv:2506.13045.

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

pith.paper-citation-record.v1
2506.13045 v4

Coverage vector

measured 100 of 278 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:40:23.729973Z

measured 105 of 105 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:31:27.300705Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T08:04:28.956439Z

Reference resolution

100 of 278 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved100
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 748c114a-191a-4acc-90c7-655f02f4ca58 · outbound

This paper cites GPT-4 Technical Report.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond GPT-4 Technical Report

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:40:14.644296Z digest=sha256:cc1ae78269f400dcf88e93af7eb9d1e2726a14ada15f3d19460d4f586f543ddb

Observation 4118cd73-20a8-4f58-b0cf-9452dea1f93e · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 2

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source=pdf_text observed=2026-08-07T00:40:14.719150Z digest=sha256:88bb420469d632a14fa6f84be8d8209a29b91969e68fae34574585d365bdc616

Observation 08eda019-dd7f-4712-baae-21c9d19cab51 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 3

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source=pdf_text observed=2026-08-07T00:40:14.834450Z digest=sha256:e1f4e8d4e65e598275578fb25ee679f68e1380f98b95896c2c8ab05e0c002b25

Observation bfd37ff6-eabd-4e87-8a7c-ef755c0d1e31 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 4

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source=pdf_text observed=2026-08-07T00:40:14.946399Z digest=sha256:b08b5e43cb3d9d4ffabeec853b86bdd9ae1ba3584c1d5184fd320b42b8b7da9f

Observation e755928f-ca8b-41e9-a94f-df5762cf908f · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 5

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source=pdf_text observed=2026-08-07T00:40:15.027230Z digest=sha256:e318c7a0857e4df9c440fe3523d287c3435ad307eb7b97b256b38b6ad7ce9c8c

Observation 93c684bf-1b91-4773-9724-a20868021b45 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 6

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source=pdf_text observed=2026-08-07T00:40:15.134539Z digest=sha256:d37d018e9acec54cf7e1b1bd134eb81ca62ed6147a2f365ad1f6aee920707a05

Observation 954786b4-f701-4cb7-a6a4-0963ceb96c59 · outbound

This paper cites Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond

Reference 7

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source=pdf_text observed=2026-08-07T00:40:15.222276Z digest=sha256:b1b4bd3e4907377ab3e4cd15d1083ba88ea97ce46f03dc84a9947cc2c33152dd

Observation 51122505-9366-4b47-b88a-44dfc62d74c7 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 8

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source=pdf_text observed=2026-08-07T00:40:15.302171Z digest=sha256:8c860c23f401069392bccb8cd13ff1d2dda72fc72279ddf971778ce51e3c2f34

Observation fad56e56-f1e0-45ad-a642-0acdc6f04e3a · outbound

This paper cites Qwen2.5-VL Technical Report.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Qwen2.5-VL Technical Report

Reference 9

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source=pdf_text observed=2026-08-07T00:40:15.397521Z digest=sha256:0b5a4a09278c7cf89d71a45e43a928504261424e33b272bd73ecdfbfe699e056

Observation c0f54d5c-14d3-4563-8893-8c450a7853c4 · outbound

This paper cites Hallucination of Multimodal Large Language Models: A Survey.

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

Reference 10

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source=pdf_text observed=2026-08-07T00:40:15.516125Z digest=sha256:3873d4bcd53db007a931282b1cd1bc917363dff14652295cafc98f390c57d436

Observation b5454bf1-fd95-4f10-bdec-ce6784eee5e0 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 11

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source=pdf_text observed=2026-08-07T00:40:15.594203Z digest=sha256:e0b31582e25c0246071e27a73f4dccd9c52ba7b776ec0aa866986096432d4726

Observation 1508f7f1-7999-4efa-9e92-e1d158f3f0b3 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 12

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source=pdf_text observed=2026-08-07T00:40:15.677586Z digest=sha256:eee8ab09a4aa30a97fff24ccf024576110b5c34bfa22593cd63a019f8e514438

Observation a5328ab0-2904-47bd-9d24-396becdf44b9 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 13

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source=pdf_text observed=2026-08-07T00:40:15.763678Z digest=sha256:27b3cede64393257bea9cc993fbca4084c40d80c1031cb953837e140f47c731e

Observation 8b4bb1c3-8b0e-42ff-b2f6-6557b91d9197 · outbound

This paper cites Lifelong Reinforcement Learning with Modulating Masks.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Lifelong Reinforcement Learning with Modulating Masks

Reference 14

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source=pdf_text observed=2026-08-07T00:40:15.914354Z digest=sha256:125995a362e0878a62d63a72ce423171d5ee2a420a27a7a6d67e3cb407fe8c14

Observation 9672c0d4-b22b-436f-8c68-e99fc5e87b85 · outbound

This paper cites FinTral: A Family of GPT-4 Level Multimodal Financial Large Language Models.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond FinTral: A Family of GPT-4 Level Multimodal Financial Large Language Models

Reference 15

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source=pdf_text observed=2026-08-07T00:40:16.025380Z digest=sha256:a9187551d6043b9bde78c8298822f3eab06d095563e09b90511da097a223c57d

Observation 70e3c51f-0afc-493e-9197-fea1f9e58e43 · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 16

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source=pdf_text observed=2026-08-07T00:40:16.148926Z digest=sha256:a43191849621d9457efb5287aa2cdcc900f426ae2103260995446ae86fb9ec57

Observation f9e6ac21-8631-4ac3-80ae-a4f90631814e · outbound

This paper cites RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control

Reference 17

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source=pdf_text observed=2026-08-07T00:40:16.259589Z digest=sha256:469060964cc2f55dca1b7a7bf0e2d41f6baafd1198eb1c9be6fc26b0db4bcbdd

Observation fb03829a-9cf4-4944-ad1a-a2de22396e41 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 18

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source=pdf_text observed=2026-08-07T00:40:16.378440Z digest=sha256:8bc78f1538bf5dbe7aefa46df57859e2ae2be31eca23bc660a030ad6e1b96fee

Observation c2feff39-16e6-4b66-8839-81b01bc822e6 · outbound

This paper cites Empowering Large Language Model for Continual Video Question Answering with Collaborative Prompting.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Empowering Large Language Model for Continual Video Question Answering with Collaborative Prompting

Reference 19

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source=pdf_text observed=2026-08-07T00:40:16.492956Z digest=sha256:0010a772522b9b4293b15006d4ed6b0fdc03932bc2a134d09001c27ce54d6be2

Observation d363f274-379c-4690-8a04-3f1b8d42dabc · outbound

This paper cites CluMo: Cluster-based Modality Fusion Prompt for Continual Learning in Visual Question Answering.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond CluMo: Cluster-based Modality Fusion Prompt for Continual Learning in Visual Question Answering

Reference 20

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source=pdf_text observed=2026-08-07T00:40:16.603197Z digest=sha256:5e81ee4a8397ef0f6aa5ac55053abe778e80a55a3f187dac10bb27602cc5811d

Observation 429028f9-ee9d-419f-b899-e5dd0d0f437c · outbound

This paper cites Task-Attentive Transformer Architecture for Continual Learning of Vision-and-Language Tasks Using Knowledge Distillation.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Task-Attentive Transformer Architecture for Continual Learning of Vision-and-Language Tasks Using Knowledge Distillation

Reference 21

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source=pdf_text observed=2026-08-07T00:40:16.694520Z digest=sha256:e00053782c97e0f035f344f45a74657b0fde9dbcac8834bcfedf6aacac395a09

Observation ab0a39a1-948c-4af8-8a5d-a96000ad60be · outbound

This paper cites Continual LLaVA: Continual Instruction Tuning in Large Vision-Language Models.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Continual LLaVA: Continual Instruction Tuning in Large Vision-Language Models

Reference 22

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source=pdf_text observed=2026-08-07T00:40:16.807608Z digest=sha256:35620291e34d588bae99bb51981655e35f3bf24e7ebfecd281ae290ce253b591

Observation 175206ea-5e8c-4731-9d0b-762f731bf5fb · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 23

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source=pdf_text observed=2026-08-07T00:40:16.901574Z digest=sha256:6a73f7169b80ebfb7d6301a09724afcc66720e934adc76e857e81f255e6756c4

Observation 55853938-041d-475b-a39c-993e964dae0f · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 24

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source=pdf_text observed=2026-08-07T00:40:16.984642Z digest=sha256:a780f92c90cfd751c8277b32f287b97e4474d0d8b6e208d7a478527b6d58c96f

Observation 4895f3b0-2d74-44f3-8345-78878645bbaf · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 25

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source=pdf_text observed=2026-08-07T00:40:17.073401Z digest=sha256:61996f7e8fb3b1e776c7eb66f03371d1b605c726787ec0aa8eedb888501d3cf5

Observation dfc248f3-af8c-45cd-8c52-f9f778caaddd · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 26

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source=pdf_text observed=2026-08-07T00:40:17.178111Z digest=sha256:a91360314a91aa3355033a6237c6d98d7fae2d821d963131fc6f148336572393

Observation ef71d889-30e5-445f-9436-009e82f16ba1 · outbound

This paper cites Overcoming Catastrophic Forgetting by Exemplar Selection in Task-oriented Dialogue System.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Overcoming Catastrophic Forgetting by Exemplar Selection in Task-oriented Dialogue System

Reference 27

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source=pdf_text observed=2026-08-07T00:40:17.289614Z digest=sha256:1d60a0953aa129cfdbe45153ac37234d136695c126d96becb3981ab441160a1a

Observation d99c106e-7c8f-46a0-8c7a-81ac032f95bc · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 28

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source=pdf_text observed=2026-08-07T00:40:17.400460Z digest=sha256:717c6e6a0ce310308ba5b0c1494dc3f75cd4b3b745d42147e181cfc3c2c01877

Observation 0cff34c7-dafc-49db-99ac-11a1256c228a · outbound

This paper cites Towards Effective and Efficient Continual Pre-training of Large Language Models.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Towards Effective and Efficient Continual Pre-training of Large Language Models

Reference 29

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source=pdf_text observed=2026-08-07T00:40:17.481210Z digest=sha256:2912466194848ff482635841727cc5f66ed20a80dad4d13f36c88b1bb8bd89df

Observation 9eb17c07-7c54-4c5a-85ce-c007f17d8b11 · outbound

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

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond SEFE: Superficial and Essential Forgetting Eliminator for Multimodal Continual Instruction Tuning

Reference 30

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source=pdf_text observed=2026-08-07T00:40:17.556570Z digest=sha256:fbe80511bd2254bc228f2c8e32c44f653a40e1f9b5178bcaddbed4fb3a4acf55

Observation 77ca1757-28c2-420c-b7e1-869d8b605141 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 31

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source=pdf_text observed=2026-08-07T00:40:17.637192Z digest=sha256:e1f19535b4ea1886b28807890b97ac0ac77f4b3722c7b85704c7b19b80c43f82

Observation f623d9b4-1130-43c0-8603-55747791ccc7 · outbound

This paper cites MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning

Reference 32

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source=pdf_text observed=2026-08-07T00:40:17.873778Z digest=sha256:5fcfad37d94eb88af1066ff51fca937bf27808b72ac16bb929fd637e7f0d99f0

Observation e893c920-03f8-4d7c-9de4-dfdc3f3951f4 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 33

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source=pdf_text observed=2026-08-07T00:40:17.982395Z digest=sha256:bcc3d6288786ae9646cb18b55cd6a09e019ac2043c7173716c8bd672cff26a1f

Observation 5ba7b8e9-cd30-4bbb-9b4b-4a787056305a · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 34

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source=pdf_text observed=2026-08-07T00:40:18.081202Z digest=sha256:70598ba23acb739f758d60012733c428cb4e5ee384c0364b6e67be1e0364ef62

Observation a80f302d-4d88-4a5f-b01f-d33c787cb22a · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 35

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source=pdf_text observed=2026-08-07T00:40:18.185390Z digest=sha256:aff6a829f49761da0655f40a8c38305f204f881951aeaf08a34bac2e787c1794

Observation 077f0b6a-046c-4a10-9c57-654d4156c6b8 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 36

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source=pdf_text observed=2026-08-07T00:40:18.272523Z digest=sha256:89256f5887ce1686a0c7ded78768fc7a56d5ef21748a0193d3af49315b5862c8

Observation 7a4b0fdc-8592-405f-8240-3790dd164bf2 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 37

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source=pdf_text observed=2026-08-07T00:40:18.347973Z digest=sha256:4b2d7c89743d793c6c8835a9ed346c4c7235496115e3ceb2c8cf6824381b21a9

Observation b53a6f26-bafe-4057-8939-3ac93358c424 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 38

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source=pdf_text observed=2026-08-07T00:40:18.425559Z digest=sha256:e7c9996ae7ceeb2ed6604722cc889004f5da2b3a890b3a7bdf6ef9b80da6c268

Observation ae325670-0fee-49d8-b258-77e1afc648bb · outbound

This paper cites SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Reference 39

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Observation 878c2401-3932-41dd-ab59-7a35e9808fe1 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 40

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Observation 20f69cf9-a1c2-4766-b937-84ebbe622cfb · outbound

This paper cites InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning

Reference 41

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Observation 19e4f4a5-9252-445c-8857-a9f83f759e45 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 42

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Observation 50e33863-9bb7-4563-bb69-0b148de06f02 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 43

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source=pdf_text observed=2026-08-07T00:40:18.910721Z digest=sha256:394e08a0c945d39856cc5d617bf285657e9e03648dbb4907a15a227193e2ab13

Observation 07f72488-b4a6-4ad8-898f-b6a71901126a · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 44

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Observation 65c594af-b7d0-464e-9286-ff26d07fff3f · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 45

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source=pdf_text observed=2026-08-07T00:40:19.051987Z digest=sha256:c00d0110f5634e78c3995a4be52531f7f12372391fece294ef9a976f047bb2c1

Observation fe603198-5c7e-49a5-b721-f5158cd9b6c5 · outbound

This paper cites A Survey on In-context Learning.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond A Survey on In-context Learning

Reference 46

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source=pdf_text observed=2026-08-07T00:40:19.127630Z digest=sha256:be1644be2d22af168eee9376192da1499531e292512468b77660ffcf017f361d

Observation 50dcc7d6-d006-4294-9336-54494aa5690f · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 47

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source=pdf_text observed=2026-08-07T00:40:19.247224Z digest=sha256:55dc3c8824e1b4b4ada5d67ecca9c15dbd520af0f4dcfea1574551b9ee35e441

Observation e4d5cc64-2ce2-4280-9d27-344b813c0664 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 48

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source=pdf_text observed=2026-08-07T00:40:19.363857Z digest=sha256:33aa5a2832ce345962489f07d11b0f0661821ef427796dc1b6dab5f44443074e

Observation 34943bd4-0330-4053-ac8b-d10b5c2eebad · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 49

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source=pdf_text observed=2026-08-07T00:40:19.514286Z digest=sha256:dde503a6b5905994f14d95ea3674318e3f3921a83b4c12f8de4d1215cd22227b

Observation dd83fc7b-e672-429a-ab9f-5e381c581ec1 · outbound

This paper cites TaSL: Continual Dialog State Tracking via Task Skill Localization and Consolidation.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond TaSL: Continual Dialog State Tracking via Task Skill Localization and Consolidation

Reference 50

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source=pdf_text observed=2026-08-07T00:40:19.606370Z digest=sha256:8126311cbac94d08d9d979d0066b9f4e4ab21131d531a5b80d2900c50c06e101

Observation 55341a8d-e7eb-4894-b3d6-19f26172326f · outbound

This paper cites Recurrent Knowledge Identification and Fusion for Language Model Continual Learning.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Recurrent Knowledge Identification and Fusion for Language Model Continual Learning

Reference 51

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source=pdf_text observed=2026-08-07T00:40:19.719838Z digest=sha256:3f2a98c45bb88160e9c693d797d3ac71f95021319794350f2cee138054bf2b6c

Observation 1b5e4fca-23bb-4798-b706-ccae4584fd73 · outbound

This paper cites Gradient Localization Improves Lifelong Pretraining of Language Models.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Gradient Localization Improves Lifelong Pretraining of Language Models

Reference 52

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Observation 13e261a0-12d3-48a3-a014-f124eb5b9efb · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 53

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Observation 6f8e011f-2ebc-440a-8cc9-c75fec9a2434 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 54

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Observation a6b583d0-7c78-4c1d-841f-39f2295107b8 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 55

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source=pdf_text observed=2026-08-07T00:40:20.308064Z digest=sha256:424b123aef970e9c5448e023cc07723c42519ffb16d7ddd53ea783939abde104

Observation 63024dd3-0e31-4646-b6ee-9c34bbfb24ee · outbound

This paper cites Retrieval-Augmented Generation for Large Language Models: A Survey.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Retrieval-Augmented Generation for Large Language Models: A Survey

Reference 56

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source=pdf_text observed=2026-08-07T00:40:20.476217Z digest=sha256:1f86cf2324e28e6bf9b6c79bd20d45955af592fa55f054623efe4e7c3efaa24f

Observation 96d8380d-dc7a-4d0d-83b4-111658ec0acc · outbound

This paper cites Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning

Reference 57

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source=pdf_text observed=2026-08-07T00:40:20.613277Z digest=sha256:dbb6747ee42a964919588553ae1fc845c264bbf418bedf2f3a0b85df79d1f9f7

Observation 34d20c37-8c5d-47f0-b6a3-3af6aca0c267 · outbound

This paper cites SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation

Reference 58

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source=pdf_text observed=2026-08-07T00:40:20.678848Z digest=sha256:893f38a019dcb27e711954142d8cdcdb4f516567d5c34e1bfb16ef42f9bb66de

Observation 3b7b9d9f-f74f-4eaa-aaa1-cc9b59646267 · outbound

This paper cites Continual Learning for Task-oriented Dialogue System with Iterative Network Pruning, Expanding and Masking.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Continual Learning for Task-oriented Dialogue System with Iterative Network Pruning, Expanding and Masking

Reference 59

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source=pdf_text observed=2026-08-07T00:40:20.748927Z digest=sha256:9857422da60d23226845ddeaf2110724edff2174b6c7c7955910b126a2530ac6

Observation 232424b1-de5c-46bb-bae4-f553d23b703c · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 60

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source=pdf_text observed=2026-08-07T00:40:20.782285Z digest=sha256:2d4f472e156e85755ef242d0982d54f2f1d64ed9465132f6dac53994a1b121a9

Observation 2f46a137-3efb-4dd4-a511-5b11a0ebfec1 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 61

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source=pdf_text observed=2026-08-07T00:40:20.831511Z digest=sha256:541a615e6d89febff4eebd257b45e9d234f5d9b7716aba8bef8b8be6bd5045b9

Observation dd7b66fe-d590-4a48-9692-c1919124e30e · outbound

This paper cites The Llama 3 Herd of Models.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond The Llama 3 Herd of Models

Reference 62

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source=pdf_text observed=2026-08-07T00:40:20.887157Z digest=sha256:e48504252c2e11a56a56d8447c8bdd106a504f04df2ab5d0182cf7ca777dac0b

Observation c5e468d5-4cbc-482d-9b01-bec6c84d844a · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 63

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source=pdf_text observed=2026-08-07T00:40:20.951270Z digest=sha256:f8b011a4b8d30bdd76f13d3839e768c85d5a555308fcdae32be703a4fe1eecd6

Observation 4f16451d-12d4-4f8f-8492-7cf60724438d · outbound

This paper cites HiDe-LLaVA: Hierarchical Decoupling for Continual Instruction Tuning of Multimodal Large Language Model.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond HiDe-LLaVA: Hierarchical Decoupling for Continual Instruction Tuning of Multimodal Large Language Model

Reference 64

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source=pdf_text observed=2026-08-07T00:40:21.047717Z digest=sha256:8135373964495944daf1803234aa6a73222ff25401fbbab3c6b253565dbe969d

Observation 318df3d9-ca66-4677-ac09-7cb29b1a6368 · outbound

This paper cites Federated Continual Instruction Tuning.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Federated Continual Instruction Tuning

Reference 65

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source=pdf_text observed=2026-08-07T00:40:21.128497Z digest=sha256:367dc1a4c9ea9b18926809e0bd45aad993ac61bead78fd7379d6656d6549c3d6

Observation 754024e3-dd89-433b-8664-6c729397f797 · outbound

This paper cites DESIRE: Dynamic Knowledge Consolidation for Rehearsal-Free Continual Learning.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond DESIRE: Dynamic Knowledge Consolidation for Rehearsal-Free Continual Learning

Reference 66

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source=pdf_text observed=2026-08-07T00:40:21.198224Z digest=sha256:6312b13c535c178244a42ee79b180ddecd4cd2df3bc4a0644dc3908b3f7b993a

Observation 4867052f-09b6-4810-be3d-e025bb1f628c · outbound

This paper cites Efficient Continual Pre-training by Mitigating the Stability Gap.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Efficient Continual Pre-training by Mitigating the Stability Gap

Reference 67

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source=pdf_text observed=2026-08-07T00:40:21.272531Z digest=sha256:7d52c7869b080aa748daf795ebf4c15e21d202b0201aa4998348b1986ee58079

Observation cfca879b-8ccc-4355-b6aa-7c99d8fd2014 · outbound

This paper cites Q-Tuning: Queue-based Prompt Tuning for Lifelong Few-shot Language Learning.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Q-Tuning: Queue-based Prompt Tuning for Lifelong Few-shot Language Learning

Reference 68

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source=pdf_text observed=2026-08-07T00:40:21.345565Z digest=sha256:5fff37b72da4c255c6e94b6a99d469ba6c0a0feb51e55e1ca9ea683430f8018f

Observation 7c594d43-1aa7-4147-8322-d05287c928d0 · outbound

This paper cites Improving Vision-Language-Action Model with Online Reinforcement Learning.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Improving Vision-Language-Action Model with Online Reinforcement Learning

Reference 69

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source=pdf_text observed=2026-08-07T00:40:21.447558Z digest=sha256:452e1aaa3bc66cb56174df4e3265b62151ad8fa62c7dcad591dc70da116c6f1d

Observation 54f5bb62-8b7b-47b0-9505-c96193c5e4d1 · outbound

This paper cites ConceptGuard: Continual Personalized Text-to-Image Generation with Forgetting and Confusion Mitigation.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond ConceptGuard: Continual Personalized Text-to-Image Generation with Forgetting and Confusion Mitigation

Reference 70

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Observation 919e91c0-e72d-476d-a769-8a95247bdc05 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 71

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source=pdf_text observed=2026-08-07T00:40:21.680508Z digest=sha256:cffcfe3f7968fdf7184419215a4253ba21b096315a97f1ed396ecda66a1edbf4

Observation 55052ecf-4710-42ca-a5de-5902d08e9e76 · outbound

This paper cites PolyTask: Learning Unified Policies through Behavior Distillation.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond PolyTask: Learning Unified Policies through Behavior Distillation

Reference 72

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source=pdf_text observed=2026-08-07T00:40:21.846962Z digest=sha256:0fe80e2f88d25ca5c5d0b233d04951f85d88ed5c38d460d235964f6449669e02

Observation d359c03a-7aad-4982-9c5a-49b1d273e160 · outbound

This paper cites SLIM: Let LLM Learn More and Forget Less with Soft LoRA and Identity Mixture.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond SLIM: Let LLM Learn More and Forget Less with Soft LoRA and Identity Mixture

Reference 73

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source=pdf_text observed=2026-08-07T00:40:22.014455Z digest=sha256:7e46c25217f17115497d11576bfb025a12ae03f096af7bc78ff22f2ebc15468c

Observation 3d5251cd-c1e1-4461-bc16-17fa09e9c00f · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 74

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source=pdf_text observed=2026-08-07T00:40:22.025593Z digest=sha256:e530a934ec97dbeb32cf14cc71e0d0ca343a1f0995285e41382f95783009fb8a

Observation 2499a6b0-ac18-4471-ab79-133415da982d · outbound

This paper cites Temporal Difference Learning for Model Predictive Control.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Temporal Difference Learning for Model Predictive Control

Reference 75

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source=pdf_text observed=2026-08-07T00:40:22.074261Z digest=sha256:323fca21c5e8e26df06986f5bce3db59b660f4211e9c8eae2554f12fbd558539

Observation bd5ef001-8abe-4b2a-9ab6-58a65bf3bb4a · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 76

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source=pdf_text observed=2026-08-07T00:40:22.191274Z digest=sha256:3b8d31cf70b6159cedb3aa3a3668307e63150fc7350a0109e2e5758a9c89505a

Observation d0b42821-790e-4063-9c0b-b96a429b82e5 · outbound

This paper cites Continual Instruction Tuning for Large Multimodal Models.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Continual Instruction Tuning for Large Multimodal Models

Reference 77

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source=pdf_text observed=2026-08-07T00:40:22.248079Z digest=sha256:5013914fb4f6b8e459002d87e0dbaa073777110924176feb7bc9ab81dd9209da

Observation 13276fd9-a719-4c39-9a87-80eef63e53fa · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 78

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source=pdf_text observed=2026-08-07T00:40:22.279601Z digest=sha256:e3eb663a24a9f2e57d1d1a1ba97318c1321f4419d263e3b7375647fa3d5dcf38

Observation 7524521f-ab4c-446c-8cc3-ef01e6cc4a0a · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 79

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Observation 9f9da976-3e4d-41e0-a6a2-854ec19017af · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 80

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source=pdf_text observed=2026-08-07T00:40:22.369537Z digest=sha256:307b15ee85b3aca8cdd263bdcd7c250897d89478658e1d69b3217a404b492b02

Observation 156ebcd2-40f0-4df7-ba1a-6b6ce5958c8e · outbound

This paper cites Don't Half-listen: Capturing Key-part Information in Continual Instruction Tuning.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Don't Half-listen: Capturing Key-part Information in Continual Instruction Tuning

Reference 81

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source=pdf_text observed=2026-08-07T00:40:22.399148Z digest=sha256:a2017e289217953ea08549592521eddb1b90faeb7c5e994f79852c8d57d9841b

Observation 8cc59c59-53e9-4dff-aeec-32c6719b89f6 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 82

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source=pdf_text observed=2026-08-07T00:40:22.456804Z digest=sha256:70655d71f14b32e4e08fa434ce0bc3909581c19fa2a042863f0af4f08fae1c8f

Observation 3d90a124-4980-4cc2-9a9e-39cda47cd312 · outbound

This paper cites Distilling the Knowledge in a Neural Network.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Distilling the Knowledge in a Neural Network

Reference 83

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source=pdf_text observed=2026-08-07T00:40:22.562199Z digest=sha256:cd861c42a05f06a7b94753b1fa820c540314d23d3d4a4c067c38b9ef18097dda

Observation de86234c-e47f-4792-829f-7f099887553c · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 84

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source=pdf_text observed=2026-08-07T00:40:22.626583Z digest=sha256:ed7cfa8b7c732aa72b12f7d4f7296423b15038f1d289f74e43ebcedfa2b5ffea

Observation afdb7e76-f217-4e7c-b5ab-c81f6239cb70 · outbound

This paper cites Training Compute-Optimal Large Language Models.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Training Compute-Optimal Large Language Models

Reference 85

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source=pdf_text observed=2026-08-07T00:40:22.716523Z digest=sha256:d36fb5bbcc3c30c88e977702394367f2095541330b9a0323ca701bcbc6115348

Observation 3158efd7-6655-4206-b8c9-3dc2aa0fe1f0 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 86

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source=pdf_text observed=2026-08-07T00:40:22.782496Z digest=sha256:45e7b1b60f90c46052ddf6ae86e69d3b0c85f62b90fa4ff36cd6f4b7a904cb3c

Observation c3e684aa-20ca-4332-ae13-324b5a4dd030 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 87

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source=pdf_text observed=2026-08-07T00:40:22.862315Z digest=sha256:98e78a926d7bde0d8835af729d1a3a4fe3eae6f6eaf2321e317811c515e831c8

Observation 2c3e1cee-cfd4-4017-b0f8-a7a1cc484f08 · outbound

This paper cites CL-MoE: Enhancing Multimodal Large Language Model with Dual Momentum Mixture-of-Experts for Continual Visual Question Answering.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond CL-MoE: Enhancing Multimodal Large Language Model with Dual Momentum Mixture-of-Experts for Continual Visual Question Answering

Reference 88

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source=pdf_text observed=2026-08-07T00:40:22.918334Z digest=sha256:1b219c24d436403516c03a1138095ebd8dafb89b7a4c76a0278be7ef87da2cd4

Observation 62652338-5352-47fd-a5e0-2445b83d45f6 · outbound

This paper cites Mitigating Catastrophic Forgetting in Large Language Models with Self-Synthesized Rehearsal.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Mitigating Catastrophic Forgetting in Large Language Models with Self-Synthesized Rehearsal

Reference 89

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source=pdf_text observed=2026-08-07T00:40:22.986424Z digest=sha256:d52e0d2eb8de61314cd6913d7e3a191642e487faf1c83dcfee5253f93bf48e94

Observation d6bfc525-93bb-4e1f-8493-512a1572b10d · outbound

This paper cites Towards Practical Tool Usage for Continually Learning LLMs.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Towards Practical Tool Usage for Continually Learning LLMs

Reference 90

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source=pdf_text observed=2026-08-07T00:40:23.048772Z digest=sha256:5286a1db254744f82995b80961d5c0eda0d2a166c77412b93f5139021374c10f

Observation abfd72d6-2822-4766-bc55-b4e5c8237438 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 91

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source=pdf_text observed=2026-08-07T00:40:23.115652Z digest=sha256:068925ca00dae08a9dc786c702036e60d82ec3c5a9f4503e94a39fe85adc3529

Observation 30cfe9fa-d60d-46ed-8ef1-802904d1693a · outbound

This paper cites Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Vision-R1: Incentivizing Reasoning Capability in Multimodal Large Language Models

Reference 92

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source=pdf_text observed=2026-08-07T00:40:23.174507Z digest=sha256:5d24c1ac448d9fb289e8cd5f7663debc7c4465404dca63c339b42655de21bb02

Observation 926282d5-a1f7-4f77-8489-13eab0551947 · outbound

This paper cites Keeping Yourself is Important in Downstream Tuning Multimodal Large Language Model.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Keeping Yourself is Important in Downstream Tuning Multimodal Large Language Model

Reference 93

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source=pdf_text observed=2026-08-07T00:40:23.245168Z digest=sha256:efca97b0fd10d4268561fc051e421e05202ebcb89fd23204a1d0bb3d7b2b79d6

Observation 4f5cc45e-8a91-4853-8278-83229e352999 · outbound

This paper cites Learn from Downstream and Be Yourself in Multimodal Large Language Model Fine-Tuning.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Learn from Downstream and Be Yourself in Multimodal Large Language Model Fine-Tuning

Reference 94

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source=pdf_text observed=2026-08-07T00:40:23.310658Z digest=sha256:f355ea14c0e91b95278dc465649b9c33d18d51788bebb8b7de2a9ea8eee0fe3d

Observation bc930cf2-44be-4801-af6d-e5c2ec6e4bf5 · outbound

This paper cites When Continue Learning Meets Multimodal Large Language Model: A Survey.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond When Continue Learning Meets Multimodal Large Language Model: A Survey

Reference 95

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source=pdf_text observed=2026-08-07T00:40:23.358940Z digest=sha256:8f893d821df95d80e5a1fd13662658a4fba8e519573bb3721f1b84d59a96ae6f

Observation df8482fb-8f45-4f36-bd79-d3b52ef94e80 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 96

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source=pdf_text observed=2026-08-07T00:40:23.446551Z digest=sha256:545779727ec7d42438145396775b6827fc7d03a63bc2cdcc438ed5c45447c157

Observation ae5eee20-0eb3-4a8c-87d2-cbebd125ef19 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 97

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source=pdf_text observed=2026-08-07T00:40:23.510944Z digest=sha256:8ab3ef6851fa57f048f681dffbc22fcb8b35b0dbf88efbdecfe18babbbac8ac7

Observation 94d19f2f-fd78-421c-8ed6-2e0fae5e4370 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 98

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source=pdf_text observed=2026-08-07T00:40:23.599936Z digest=sha256:ca5144aabc84477dcf7556660e5fa1133dffa052df9572d9892a42dc825ca857

Observation f1694415-d5da-401d-8927-c0b7affb3f8e · outbound

This paper cites Hierarchical-Task-Aware Multi-modal Mixture of Incremental LoRA Experts for Embodied Continual Learning.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Hierarchical-Task-Aware Multi-modal Mixture of Incremental LoRA Experts for Embodied Continual Learning

Reference 99

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source=pdf_text observed=2026-08-07T00:40:23.664865Z digest=sha256:4988fca046cda71269809c52740d6df61f3a2768da99a5651954c61039cf2e16

Observation 4eb9bb66-0b05-425b-afd9-8acb2139ed37 · outbound

This paper cites an unresolved cited work.

Continual Learning for Generative AI: From LLMs to MLLMs and Beyond Unresolved cited work

Reference 100

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source=pdf_text observed=2026-08-07T00:40:23.729973Z digest=sha256:9a63db06816f17dbab756c25690f203efcb32ca294d28100cf328163f00c1e23

Pith citing papers

Observation c475cba2-0e4b-4003-bb6b-22a47838e224 · inbound

Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training cites this paper.

Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training Continual Learning for Generative AI: From LLMs to MLLMs and Beyond

Reference 10

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source=arxiv_source observed=2026-08-06T19:31:27.300705Z digest=sha256:68f9a6bcf3ac08dc649d82b5dac485fdf36f6821952e534bd56405124b6f4778

Observation 414babc3-5c7e-47fb-b12f-3ad4a3aee7eb · inbound

Agentic Software Engineering: Foundational Pillars and a Research Roadmap cites this paper.

Agentic Software Engineering: Foundational Pillars and a Research Roadmap Continual Learning for Generative AI: From LLMs to MLLMs and Beyond

Reference 11

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source=pdf_text observed=2026-08-04T23:57:06.320358Z digest=sha256:abcadc5c742653d8fcb2d5a1282c67a3b634db1c86ecf48b2d5ea2e1c7d431e5

Observation 7098192c-f3da-4059-9c36-7960ef4cb363 · inbound

C-NAV: Towards Self-Evolving Continual Object Navigation in Open World cites this paper.

C-NAV: Towards Self-Evolving Continual Object Navigation in Open World Continual Learning for Generative AI: From LLMs to MLLMs and Beyond

Reference 14

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arxiv_id, observed 2026-05-18T04:35:52.475793Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T04:33:13.564547Z digest=sha256:0019b08480e519dab08061f7bd30177964873a5b51d17279dc12eefc2ebbf666

Observation 41150240-ffa3-44d3-925b-6e39fb74f005 · 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 Generative AI: From LLMs to MLLMs and Beyond

Reference 11

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arxiv_id, observed 2026-05-12T07:21:25.190405Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-12T03:27:45.784361Z digest=sha256:5a95ef7112bc80ba5acd81e395211c31eab5422c230b2c6e0835cbf36b4cf0eb

Observation 9fc26e2e-1d13-46bb-89bc-554d412208ff · inbound

Towards Continual Motion-Language Agents: LoRA Variants for Incremental Motion Understanding and Generation cites this paper.

Towards Continual Motion-Language Agents: LoRA Variants for Incremental Motion Understanding and Generation Continual Learning for Generative AI: From LLMs to MLLMs and Beyond

Reference 4

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arxiv_id, observed 2026-06-30T08:04:28.958535Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T07:36:50.034451Z digest=sha256:59f76397be0f0750e2495b51241fe1833767b757a7f1f56d13563f6723352fc8