Paper Citation Record · LEDGER

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer

As of 8 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2606.05626.

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

pith.paper-citation-record.v1
2606.05626 v1

Coverage vector

measured 44 of 44 reference resolution

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One-hop event checks from named stored sources.

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Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

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External citation measurements

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Outbound references

Observation 094a64c4-d06f-45b2-8193-d653665cf8bd · outbound

This paper cites New Insights on Reducing Abrupt Representation Change in Online Continual Learning.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer New Insights on Reducing Abrupt Representation Change in Online Continual Learning

Reference 1

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Observation 3386ea96-771b-496e-b80c-c30f68a7c572 · outbound

This paper cites Openturingbench: An open-model-based benchmark and framework for machine-generated text detection and attribution.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Openturingbench: An open-model-based benchmark and framework for machine-generated text detection and attribution

Reference 2

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This paper cites Divscore: Zero-shot detection of llm-generated text in specialized domains.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Divscore: Zero-shot detection of llm-generated text in specialized domains

Reference 3

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This paper cites Could AI Trace and Explain the Origins of AI-Generated Images and Text?.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Could AI Trace and Explain the Origins of AI-Generated Images and Text?

Reference 4

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Observation 5419a0e5-1737-41a7-bd7b-ae7914d110b8 · outbound

This paper cites Catastrophic forgetting in connection- ist networks.Trends in cognitive sciences, 3(4):128–135,.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Catastrophic forgetting in connection- ist networks.Trends in cognitive sciences, 3(4):128–135,

Reference 5

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Observation 86ac0f9d-082a-471c-a49d-bba89ad4cd95 · outbound

This paper cites The Llama 3 Herd of Models.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer The Llama 3 Herd of Models

Reference 6

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Observation e586ac31-9f63-4a24-a706-bc9c20590df8 · outbound

This paper cites Learning to rewrite: Generalized llm- generated text detection.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Learning to rewrite: Generalized llm- generated text detection

Reference 7

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This paper cites DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing

Reference 8

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Observation 8824fa00-a1b3-44ab-aa3d-4e1557784bc8 · outbound

This paper cites Mgtbench: Benchmarking machine- generated text detection.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Mgtbench: Benchmarking machine- generated text detection

Reference 9

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Observation 65b67ea7-ae7b-4577-bf1b-e98d6124f127 · outbound

This paper cites Authorship attribution in the era of llms: Problems, methodologies, and challenges.ACM SIGKDD Explorations Newsletter, 26(2):21–43, 2025.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Authorship attribution in the era of llms: Problems, methodologies, and challenges.ACM SIGKDD Explorations Newsletter, 26(2):21–43, 2025

Reference 10

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Observation 2b56e9e4-fc14-4332-999d-39badc7ea77c · outbound

This paper cites Mitigating catastrophic forgetting in large language models with self-synthesized rehearsal.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Mitigating catastrophic forgetting in large language models with self-synthesized rehearsal

Reference 11

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Observation 6bbb30af-b76c-4f89-9bce-a5b89f32c0e5 · outbound

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer GPT-4o System Card

Reference 12

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Observation f40979b6-3abc-4e34-ab9d-0a6aaa350397 · outbound

This paper cites Mixtral of Experts.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Mixtral of Experts

Reference 13

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This paper cites M-rangedetector: Enhancing gen- eralization in machine-generated text detection through multi-range attention masks.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer M-rangedetector: Enhancing gen- eralization in machine-generated text detection through multi-range attention masks

Reference 14

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This paper cites A Survey of AI-generated Text Forensic Systems: Detection, Attribution, and Characterization.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer A Survey of AI-generated Text Forensic Systems: Detection, Attribution, and Characterization

Reference 15

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Observation 2468bd3a-a25d-4b02-ad0d-bae1d4827689 · outbound

This paper cites Authorship Attribution in Multilingual Machine-Generated Texts.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Authorship Attribution in Multilingual Machine-Generated Texts

Reference 16

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Observation 29bad8fa-564a-45bd-a066-3755c2e2bfdf · outbound

This paper cites Prde- tect: Perturbation-robust llm-generated text detection based on syntax tree.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Prde- tect: Perturbation-robust llm-generated text detection based on syntax tree

Reference 17

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This paper cites Iron sharpens iron: Defending 8 against attacks in machine-generated text detection with adversarial training.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Iron sharpens iron: Defending 8 against attacks in machine-generated text detection with adversarial training

Reference 18

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This paper cites Learning without forget- ting.IEEE transactions on pattern analysis and machine intelligence, 40(12):2935–2947, 2017.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Learning without forget- ting.IEEE transactions on pattern analysis and machine intelligence, 40(12):2935–2947, 2017

Reference 19

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This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-07-02T12:56:57.675389Z

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Observation 82596d4d-8d0d-4b4c-ac98-4465e391c12c · outbound

This paper cites On the gen- eralization and adaptation ability of machine-generated text detectors in academic writing.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer On the gen- eralization and adaptation ability of machine-generated text detectors in academic writing

Reference 21

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This paper cites Multisocial: Multilingual benchmark of machine- generated text detection of social-media texts.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Multisocial: Multilingual benchmark of machine- generated text detection of social-media texts

Reference 22

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Catastrophic interference in connectionist networks: The sequential learning problem

Reference 23

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Moonshot AI

Reference 24

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This paper cites Leveraging explainable ai for llm text attribution: Differentiating human-written and multiple llm-generated text.Information, 16(9):767, 2025.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Leveraging explainable ai for llm text attribution: Differentiating human-written and multiple llm-generated text.Information, 16(9):767, 2025

Reference 25

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Openclaw docs

Reference 26

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Artificial intelligence (ai) tools for academic research.Library Hi Tech News, 41(8):18–20,

Reference 27

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This paper cites Stress-testing machine generated text detection: Shifting language models writing style to fool detectors.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Stress-testing machine generated text detection: Shifting language models writing style to fool detectors

Reference 28

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This paper cites Random features for large-scale kernel machines.Advances in neural infor- mation processing systems, 20, 2007.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Random features for large-scale kernel machines.Advances in neural infor- mation processing systems, 20, 2007

Reference 29

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer icarl: Incremental classifier and representation learning

Reference 30

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Almost ai, almost human: The challenge of detecting ai-polished writing

Reference 31

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This paper cites Overview of AuTexTification at IberLEF 2023: Detection and Attribution of Machine-Generated Text in Multiple Domains.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Overview of AuTexTification at IberLEF 2023: Detection and Attribution of Machine-Generated Text in Multiple Domains

Reference 32

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Haco-det: A study to- wards fine-grained machine-generated text detection un- der human-ai coauthoring

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Are we in the ai-generated text world already? quantify- ing and monitoring AIGT on social media

Reference 34

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer LLaMA: Open and Efficient Foundation Language Models

Reference 35

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 36

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Continual Learning: Applications and the Road Forward

Reference 37

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Chao, and Derek Fai Wong

Reference 38

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Large scale incremental learning

Reference 39

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Semantic drift compensation for class-incremental learning

Reference 40

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Evobench: To- wards real-world llm-generated text detection bench- marking for evolving large language models

Reference 41

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This paper cites Revisiting class-incremental learning with pre-trained models: Generalizability and adaptivity are all you need.International Journal of Computer Vision, 133(3):1012–1032, 2025.

When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Revisiting class-incremental learning with pre-trained models: Generalizability and adaptivity are all you need.International Journal of Computer Vision, 133(3):1012–1032, 2025

Reference 42

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Expandable subspace ensemble for pre- trained model-based class-incremental learning

Reference 43

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When New Generators Arrive: Lifelong Machine-Generated Text Attribution via Ridge Feature Transfer Ori.” column is marked “—

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