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Paper Citation Record · LEDGER

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

As of 9 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2506.04739.

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

pith.paper-citation-record.v1
2506.04739 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:38:32.334386Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

52 of 52 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

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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Observation 30bd8efb-1aa4-4498-85cf-aadecbeb0300 · outbound

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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Observation c9170924-62e4-4dfb-93ec-7beded3da07d · outbound

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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Observation 9aa590d8-26a8-4795-ab66-8c46fdec3037 · outbound

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

Resolution
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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

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Source-reported events for the cited work

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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

Resolution
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Source-reported events for the cited work

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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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Source-reported events for the cited work

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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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Source-reported events for the cited work

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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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Source-reported events for the cited work

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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

Resolution
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Source-reported events for the cited work

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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

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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

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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

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Source-reported events for the cited work

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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
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Source-reported events for the cited work

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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
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Source-reported events for the cited work

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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

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Source-reported events for the cited work

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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

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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

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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
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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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Source-reported events for the cited work

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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
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Source-reported events for the cited work

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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

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Observation bf99117d-7e24-402a-b0bf-ad4b44175797 · outbound

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
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Source-reported events for the cited work

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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
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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

Resolution
verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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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

Resolution
unresolved
no resolver link, observed 2026-08-07T10:38:30.822509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:38:30.822509Z digest=sha256:eeb8134fb89fb45ec597a9bd01672af0a2946764b96ba7947828581578498552

Observation c9b064ab-08b5-4baf-975e-cc7ba9149ac1 · outbound

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:38:30.867763Z digest=sha256:b859742c516c874ab1f304cca29cad2107c0a61eb292888f3ba6cce304ddc8db

Observation 201a19d9-bf57-4b23-88ad-e6059a5467dc · outbound

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:38:30.906858Z digest=sha256:979a1638c1d3349d6cc8bad48944d62daab27a211e5ecbfb7b9e4268cb0ed196

Observation d402376a-5acc-4fbf-b828-9965a35db443 · outbound

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

Resolution
unresolved
no resolver link, observed 2026-08-07T10:38:30.965804Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:38:30.965804Z digest=sha256:95bc7d45127df88e1c14d94b9f3ab85b3019664365448b69b0d73e7fb20f1634

Observation da8b5680-dc8d-45cb-ba3e-78e16e31ad10 · outbound

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

Resolution
unresolved
no resolver link, observed 2026-08-07T10:38:31.023176Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:38:31.023176Z digest=sha256:270c6909c8e65f3adb15009cc992888c9d681fe5d12bbeb4a5603db7feb4e4d8

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:38:34.931624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:38:31.108265Z digest=sha256:360fa795dd37f16b0ddff1754298c4f40fe2e44c21d4546118144c9d2cbbe75e

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:38:31.175885Z digest=sha256:067acdd252edc0c29ef15379f3a1774c4f59295d7937f40616e0b3a93bdbc8d1

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

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T10:38:34.511212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:38:31.253232Z digest=sha256:7ab773f5570f530e9e4283cbab35a3733d2d0e38a098a6014bd1739643ff740d

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,

Reference 42

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:38:31.346198Z digest=sha256:a8b9c0cbed4aa470a9b62f4caac1b301121f153a4a6283616a4931f60f97df70

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:38:31.471545Z digest=sha256:d0b40ba2690375e122027345e5642999749a6781c9c6fae284d835ff97e38ea1

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

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:38:31.556229Z digest=sha256:641754fd0aa722f947db03bfbe22ba972715877567144a1ece8309bb5700e22f

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

Resolution
unresolved
no resolver link, observed 2026-08-07T10:38:31.642644Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:38:31.642644Z digest=sha256:ce422f2221e6326dc1ea4d9f28be12749f7352459786e611a9e818da2d0d6cba

Observation 98d1d884-5b9e-4e98-8955-fc57464329d4 · outbound

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

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:38:31.701494Z digest=sha256:23788f9a5f0fb0372524b06a9be87dfbab41f26fbc1ec93f254790fdd272146e

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

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:38:31.862046Z digest=sha256:c01af5d5e3fe649ccb0613e798e32978004ca57d399cd152c561a1c07f85dc2e

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:38:31.967631Z digest=sha256:a778ef82e278dbfeb2047b67f3e575bbc4a0a409fd0526a1666241a67a5a5c43

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:38:32.071774Z digest=sha256:7c4911edad047fa2876ad7ba8509d8d90cb31ed8048f9e5f50c7a3ed33c4d1cb

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:38:32.147673Z digest=sha256:a36e13fa27606ca95a43a16f23f3aaa600032ed9e20753643dc59bc868cbc3f0

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:38:32.232986Z digest=sha256:6ae7e4c2b85a4e98f275cc6d483ca2d98ae9c84404a64c532be64a506ded200f

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 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T10:38:32.334386Z digest=sha256:c6a09d27e2ec24d64095a6c8acd0e67e28defdb6286adf4434e90938ba372015

Pith citing papers

No inbound Pith citation observations are available.