Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection | Paper Citation Record

Observation f9aa9ed4-9a92-45b3-9054-6d62a2480159 · outbound

This paper cites Fake news on social media: the impact on society,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Fake news on social media: the impact on society,

Reference 1

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This paper cites Inoculating against fake news about covid-19,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Inoculating against fake news about covid-19,

Reference 2

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This paper cites The diffusion of misinformation on social media: Temporal pattern, message, and source,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection The diffusion of misinformation on social media: Temporal pattern, message, and source,

Reference 3

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Observation e9b8a06a-41f9-4a7a-9cf0-a2b1e9ac9b7c · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 4

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This paper cites New explainability method for bert-based model in fake news detection,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection New explainability method for bert-based model in fake news detection,

Reference 5

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Observation ccc9be9e-827f-4981-887b-fa7bae073e7a · outbound

This paper cites Reinforced adaptive knowl- edge learning for multimodal fake news detection,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Reinforced adaptive knowl- edge learning for multimodal fake news detection,

Reference 6

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Observation c13bc442-8dac-48f4-b993-27e39cfc84af · outbound

This paper cites Dpsg: Dynamic propagation social graphs for multi-modal fake news detection,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Dpsg: Dynamic propagation social graphs for multi-modal fake news detection,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:39.370524Z

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Observation 3f0ecba6-a747-4939-9fc4-ae67ae963c42 · outbound

This paper cites Embracing domain differences in fake news: Cross-domain fake news detection using multi-modal data,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Embracing domain differences in fake news: Cross-domain fake news detection using multi-modal data,

Reference 8

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Observation 2278681d-a2b5-446e-afd3-4a68f07601f8 · outbound

This paper cites A survey on evaluation of large language models,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection A survey on evaluation of large language models,

Reference 9

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Observation a02d65f9-5375-4648-9e34-617b7be3b863 · outbound

This paper cites A Survey of Large Language Models.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection A Survey of Large Language Models

Reference 10

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Observation 4ecbb032-62b3-447a-bac9-f145f9919ecc · outbound

This paper cites Bad actor, good advisor: Exploring the role of large language models in fake news detection,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Bad actor, good advisor: Exploring the role of large language models in fake news detection,

Reference 11

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Observation ebb1c5cf-b36b-49bc-978a-f00e296aa355 · outbound

This paper cites DELL: Generating Reactions and Explanations for LLM-Based Misinformation Detection.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection DELL: Generating Reactions and Explanations for LLM-Based Misinformation Detection

Reference 12

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Observation 70f830e8-8444-400b-861e-816618aea969 · outbound

This paper cites Fake news in sheep’s clothing: Robust fake news detection against llm-empowered style attacks,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Fake news in sheep’s clothing: Robust fake news detection against llm-empowered style attacks,

Reference 13

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Observation c6dd5d98-5f4b-4b2f-8994-9b3f0b75cdae · outbound

This paper cites Mdfend: Multi-domain fake news detection,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Mdfend: Multi-domain fake news detection,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:38.615453Z

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Observation 881bbaae-301b-4cd9-92ee-b4f14c1e4f4f · outbound

This paper cites Memory-guided multi-view multi-domain fake news detection,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Memory-guided multi-view multi-domain fake news detection,

Reference 15

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Observation b457129b-f557-452b-a77c-fc75267b534d · outbound

This paper cites A survey of fake news: Fun- damental theories, detection methods, and opportunities,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection A survey of fake news: Fun- damental theories, detection methods, and opportunities,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:38.320552Z

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Observation 8e709546-bb79-4962-8be8-fe7bb5839f60 · outbound

This paper cites Mvae: Multimodal varia- tional autoencoder for fake news detection,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Mvae: Multimodal varia- tional autoencoder for fake news detection,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:38.192505Z

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Observation e38595e2-09ec-4867-a012-49f506f19fe7 · outbound

This paper cites Content-based fake news detection with machine and deep learning: a systematic review,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Content-based fake news detection with machine and deep learning: a systematic review,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:38.040964Z

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Observation c83e21b7-f393-425e-9301-9c39ec8fbdd7 · outbound

This paper cites Mmdfnd: Multi-modal multi- domain fake news detection,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Mmdfnd: Multi-modal multi- domain fake news detection,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:37.881863Z

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Observation 33f8aae6-afaf-4b91-b99b-afb90cc02192 · outbound

This paper cites Robust domain misinforma- tion detection via multi-modal feature alignment,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Robust domain misinforma- tion detection via multi-modal feature alignment,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:37.734336Z

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Observation 82a2c3c7-a22a-4e3c-9f95-d7f265bf6bbb · outbound

This paper cites A comprehensive survey of continual learning: theory, method and application,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection A comprehensive survey of continual learning: theory, method and application,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:37.599778Z

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Observation abda8fa1-3474-428d-8be7-768186789f0d · outbound

This paper cites Incremental task learning with incremental rank updates,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Incremental task learning with incremental rank updates,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:37.412880Z

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Observation bd58f9bd-4b9d-474c-9452-4357dfc06463 · outbound

This paper cites A comprehensive study of class incremental learning algorithms for visual tasks,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection A comprehensive study of class incremental learning algorithms for visual tasks,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:37.250365Z

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Observation 6494f9fb-6192-4f6f-8f0c-582fe5af90e8 · outbound

This paper cites Three types of incremental learning,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Three types of incremental learning,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:37.082378Z

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Observation e2649d58-526d-4eb0-9cf0-affe4a27ac40 · outbound

This paper cites Learning without forgetting,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Learning without forgetting,

Reference 25

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Observation 30137dbe-d424-496f-8e9d-5d28aed0a746 · outbound

This paper cites Efficient lifelong learning with a-gem,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Efficient lifelong learning with a-gem,

Reference 26

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Observation e08941e4-40b5-4bf1-aeaa-68fa0205cb04 · outbound

This paper cites A unified approach to domain in- cremental learning with memory: Theory and algorithm,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection A unified approach to domain in- cremental learning with memory: Theory and algorithm,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:36.601437Z

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Observation b04f7c3e-29a3-4064-a09d-d5b4627442ff · outbound

This paper cites Collaborative evolution: Multi-round learning between large and small language models for emergent fake news detection,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Collaborative evolution: Multi-round learning between large and small language models for emergent fake news detection,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:36.430498Z

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This paper cites Unveiling the generalization power of fine-tuned large language models,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Unveiling the generalization power of fine-tuned large language models,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:36.300508Z

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Observation 2b3ed7f4-2ee8-45b2-8e7d-4e93abc2d661 · outbound

This paper cites Editing factual knowledge in language models,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Editing factual knowledge in language models,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:36.133865Z

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Observation b9fb69d6-3209-4a65-82c0-19bc80193803 · outbound

This paper cites Rethinking the role of demon- strations: What makes in-context learning work?,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Rethinking the role of demon- strations: What makes in-context learning work?,

Reference 31

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Observation a2a1ab81-1265-4b27-bacb-2da0295c060c · outbound

This paper cites Knowledge injection to counter large language model (llm) hallucination,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Knowledge injection to counter large language model (llm) hallucination,

Reference 32

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Observation 5d4e691e-0de9-4b1b-bcfa-e03c53704174 · outbound

This paper cites Aging with grace: Lifelong model editing with discrete key-value adaptors,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Aging with grace: Lifelong model editing with discrete key-value adaptors,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:35.540660Z

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Observation 9543c01b-4fdf-46e7-afab-771957e1fff4 · outbound

This paper cites A Survey on In-context Learning.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection A Survey on In-context Learning

Reference 34

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This paper cites A survey on deep active learning: Recent advances and new frontiers,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection A survey on deep active learning: Recent advances and new frontiers,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:35.319753Z

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This paper cites Context-aware query selection for active learning in event recognition,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Context-aware query selection for active learning in event recognition,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:35.130106Z

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

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 37

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This paper cites Mixtral of Experts.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Mixtral of Experts

Reference 38

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Observation 129fbd18-8904-4d2e-ad18-b9ea6d526afd · outbound

This paper cites Loramoe: Alleviating world knowledge forgetting in large language models via moe- style plugin,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Loramoe: Alleviating world knowledge forgetting in large language models via moe- style plugin,

Reference 39

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Observation 2b88e39d-4a96-430f-8f16-a16b7e532c47 · outbound

This paper cites Multi-modality cross attention network for image and sentence matching,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Multi-modality cross attention network for image and sentence matching,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:34.751250Z

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Observation 8d847d8d-c2e1-44bd-9d72-6db72d31af98 · outbound

This paper cites Dark experience for general continual learning: a strong, simple baseline,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Dark experience for general continual learning: a strong, simple baseline,

Reference 41

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Observation dbeec292-df92-4dfd-a4d1-a06605b30f9c · outbound

This paper cites A survey on semi- supervised learning,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection A survey on semi- supervised learning,

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Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:34.308873Z

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Observation 295c9ffb-58be-478b-80d7-c262272c6f56 · outbound

This paper cites What makes good in-context examples for gpt-3?,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection What makes good in-context examples for gpt-3?,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:34.157985Z

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Observation c63114be-a6be-4959-b8e4-61c485d5d2c4 · outbound

This paper cites How to measure uncertainty in uncertainty sampling for active learning,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection How to measure uncertainty in uncertainty sampling for active learning,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:33.969594Z

Source-reported events for the cited work

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Observation 95fbb7da-9e5f-4971-9229-eceeba423cdf · outbound

This paper cites GLEAN: Active Generalized Category Discovery with Diverse LLM Feedback.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection GLEAN: Active Generalized Category Discovery with Diverse LLM Feedback

Reference 45

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Source-reported events for the cited work

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This paper cites Boididou, christina and papadopoulos, symeon and others,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Boididou, christina and papadopoulos, symeon and others,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:33.768500Z

Source-reported events for the cited work

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Observation fa23e9c0-959c-4737-a524-2d725c3f4b8d · outbound

This paper cites Exploiting context for rumour detection in social media,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Exploiting context for rumour detection in social media,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:33.552025Z

Source-reported events for the cited work

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Observation b48b908d-59d6-44c9-8feb-5f164adb842b · outbound

This paper cites Compare to the knowledge: Graph neural fake news detection with external knowl- edge,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Compare to the knowledge: Graph neural fake news detection with external knowl- edge,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:33.336415Z

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Observation ca58e147-8bcd-4d0c-afce-3dd992f08f66 · outbound

This paper cites Learn over past, evolve for future: Forecasting temporal trends for fake news de- tection,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Learn over past, evolve for future: Forecasting temporal trends for fake news de- tection,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:33.140282Z

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No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation eeb304b0-2264-4912-a028-edb1c72e3a4c · outbound

This paper cites Explainable fake news detection with large language model via defense among competing wisdom,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Explainable fake news detection with large language model via defense among competing wisdom,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:32.971256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f88c423c-dfcb-4e35-900a-abe3edac31c2 · outbound

This paper cites Eann: Event adversarial neural networks for multi-modal fake news detection,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Eann: Event adversarial neural networks for multi-modal fake news detection,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:32.764365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1624daef-9959-47a0-a8d3-5126614780f9 · outbound

This paper cites Contrastive domain adaptation for early misinformation detection: A case study on covid-19,.

Lifelong Evolution: Collaborative Learning between Large and Small Language Models for Continuous Emergent Fake News Detection Contrastive domain adaptation for early misinformation detection: A case study on covid-19,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T10:38:32.589550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

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Pith citing papers