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Paper Citation Record · LEDGER

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification

As of 7 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2507.11310.

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

pith.paper-citation-record.v1
2507.11310 v1

Coverage vector

measured 47 of 47 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:15:44.394024Z

measured 47 of 47 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 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

47 of 47 outbound references displayed

  • verified exact1
  • verified fuzzy27
  • unresolved19
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 22eff2fa-db9a-46c4-99b7-cb1ac0174759 · outbound

This paper cites Towards improved cyber security information sharing,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Towards improved cyber security information sharing,

Reference 1

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Source-reported events for the cited work

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

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Observation 68005d86-3f3d-43dc-864d-6bdad56a62a7 · outbound

This paper cites Stiocs: Active learning-based semi-supervised training framework for ioc extraction,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Stiocs: Active learning-based semi-supervised training framework for ioc extraction,

Reference 2

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raw_fallback, observed 2026-08-06T17:15:45.295498Z

Source-reported events for the cited work

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

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Observation 3ea62407-0581-4c62-9c8e-6c761f7d3e92 · outbound

This paper cites Tweetcred: Real- time credibility assessment of content on twitter,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Tweetcred: Real- time credibility assessment of content on twitter,

Reference 3

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Source-reported events for the cited work

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

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Observation 3962309a-0a90-4893-a5d1-82e9d7cb80a5 · outbound

This paper cites Sentence-level evidence embedding for claim verification with hierarchical attention networks.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Sentence-level evidence embedding for claim verification with hierarchical attention networks

Reference 4

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raw_fallback, observed 2026-08-06T17:15:45.256452Z

Source-reported events for the cited work

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

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Observation 33f96c32-759b-4478-b012-d2b69b466b66 · outbound

This paper cites DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learning.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learning

Reference 5

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unresolved
no resolver link, observed 2026-08-06T17:15:44.150877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:15:44.150877Z digest=sha256:f09b222a777d0f2e87ee5d791a6d8fda68c95e625b17984f85e81ce7a2aab52b

Observation 4e0225c4-2dd8-4d0e-bdd2-79d1463701da · outbound

This paper cites Hierarchical Multi-head Attentive Network for Evidence-aware Fake News Detection.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Hierarchical Multi-head Attentive Network for Evidence-aware Fake News Detection

Reference 6

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local_arxiv, observed 2026-08-06T17:15:44.699221Z

Source-reported events for the cited work

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

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Observation b6c6605f-0a45-4f68-907e-f4d0acb3168c · outbound

This paper cites Evidence-aware fake news detection with graph neural networks,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Evidence-aware fake news detection with graph neural networks,

Reference 7

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:15:44.164110Z digest=sha256:bd784b513d3bfa8da8ad6d0c69f0b0ba984942f21a3f2df6a602baad5487749b

Observation 4e079823-9e5d-4c37-9024-7d9197a796ed · outbound

This paper cites Muser: A multi-step evidence retrieval enhancement framework for fake news detection,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Muser: A multi-step evidence retrieval enhancement framework for fake news detection,

Reference 8

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:15:44.169478Z digest=sha256:9c89eea5ad1d283595ee415354567102a9495a770fb0c0bcdc233cccd2728820

Observation 9bf81d3b-40ab-475c-833d-b2c7945f2829 · outbound

This paper cites A survey on large language model (llm) security and privacy: The good, the bad, and the ugly,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification A survey on large language model (llm) security and privacy: The good, the bad, and the ugly,

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 786fa32b-3315-4193-bbe7-d47dba6a01af · outbound

This paper cites Wikicoref: An english coreference- annotated corpus of wikipedia articles,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Wikicoref: An english coreference- annotated corpus of wikipedia articles,

Reference 10

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:15:44.180880Z digest=sha256:ebf5d10320a31bd0f47f51dde56fda923ffa7ca0adf154cb067a7a3be887295e

Observation 5a7e8350-0048-44e8-acbb-0c28a42559cc · outbound

This paper cites A survey on technical threat intelligence in the age of sophisticated cyber attacks,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification A survey on technical threat intelligence in the age of sophisticated cyber attacks,

Reference 11

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Source-reported events for the cited work

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

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Observation 720c983b-ff55-44b7-b47c-7455a569ab34 · outbound

This paper cites ‘towards a methodology for evaluating threat intelligence feeds,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification ‘towards a methodology for evaluating threat intelligence feeds,

Reference 12

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:15:44.192522Z digest=sha256:9dc755daa5b90c74c4f64785eb3b1162af4d86e9251dce1950a3a15b00966b51

Observation 231afe79-0654-4def-826c-b4db067b537f · outbound

This paper cites Pure: Generating quality threat intelligence by clustering and correlating osint,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Pure: Generating quality threat intelligence by clustering and correlating osint,

Reference 13

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raw_fallback, observed 2026-08-06T17:15:45.090519Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:15:44.197822Z digest=sha256:2bf36a1b500dbd464fb660dbdc34479218cbb1a94ae06c4d240d33b4e67740dc

Observation 9a707e26-2f4e-4db3-9616-805ce48a9e3e · outbound

This paper cites A multi-source threat intelligence confidence value evaluation method based on machine learning,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification A multi-source threat intelligence confidence value evaluation method based on machine learning,

Reference 14

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raw_fallback, observed 2026-08-06T17:15:45.071591Z

Source-reported events for the cited work

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

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Observation 9a7455e3-bebc-4c77-ab9e-37bf071d4a6a · outbound

This paper cites Sharing machine learning models as indicators of compromise for cyber threat intelligence,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Sharing machine learning models as indicators of compromise for cyber threat intelligence,

Reference 15

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Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:15:44.209888Z digest=sha256:d6bb2158c10e331e4416752ec6bf352d37f833a5a1a172f24337e4ae21e52c02

Observation 1f19d694-40ab-47c9-b944-4439962e1e2c · outbound

This paper cites Security threat model under internet of things using deep learning and edge analysis of cyberspace governance,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Security threat model under internet of things using deep learning and edge analysis of cyberspace governance,

Reference 16

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raw_fallback, observed 2026-08-06T17:15:45.029942Z

Source-reported events for the cited work

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

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Observation 9dd4a327-5720-4a80-a6a6-9718adebfdaf · outbound

This paper cites Scoring model for iocs by combining open intelligence feeds to reduce false positives,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Scoring model for iocs by combining open intelligence feeds to reduce false positives,

Reference 17

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Source-reported events for the cited work

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

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Observation 3b2276c6-8441-4323-a0f4-4d7eb19019b9 · outbound

This paper cites Large language models struggle to learn long-tail knowledge,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Large language models struggle to learn long-tail knowledge,

Reference 18

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raw_fallback, observed 2026-08-06T17:15:44.991239Z

Source-reported events for the cited work

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

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Observation 0f79018d-ae85-4187-bbc8-35acb2cc7e43 · outbound

This paper cites Prompt-and-align: prompt-based social alignment for few-shot fake news detection,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Prompt-and-align: prompt-based social alignment for few-shot fake news detection,

Reference 19

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raw_fallback, observed 2026-08-06T17:15:44.973595Z

Source-reported events for the cited work

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

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Observation b0bd8af0-9841-474d-873e-836ca9eff8f4 · outbound

This paper cites Explainable Claim Verification via Knowledge-Grounded Reasoning with Large Language Models.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Explainable Claim Verification via Knowledge-Grounded Reasoning with Large Language Models

Reference 20

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:15:44.235700Z digest=sha256:4f715867d7ee42af7374bcb160e2163e7ade10f3fdbd194c3e0e5514540fa5cb

Observation 60fcf308-fbe2-4743-8b5d-08453abb5d9c · outbound

This paper cites Active Retrieval Augmented Generation.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Active Retrieval Augmented Generation

Reference 21

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Unavailable: canonical work link unavailable.

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Observation e5c33949-4710-4f13-96df-01bdd98d6745 · outbound

This paper cites REPLUG: Retrieval-Augmented Black-Box Language Models.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification REPLUG: Retrieval-Augmented Black-Box Language Models

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:15:44.246773Z digest=sha256:f6e44f1be0630336ba93a9731464e56cbcd3ed18c7881f574561fef6231a4895

Observation 6876fb99-b04d-42d0-9b1c-053d158ccdd1 · outbound

This paper cites Factcheck-Bench: Fine-Grained Evaluation Benchmark for Automatic Fact-checkers.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Factcheck-Bench: Fine-Grained Evaluation Benchmark for Automatic Fact-checkers

Reference 23

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no resolver link, observed 2026-08-06T17:15:44.252025Z

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Unavailable: canonical work link unavailable.

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Observation 784fc684-9b17-4b5c-a865-569a0f1b75a9 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Chain-of-thought prompting elicits reasoning in large language models,

Reference 24

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Source-reported events for the cited work

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

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Observation 0c574154-9b63-42a6-9dc2-49aef673a5b7 · outbound

This paper cites ReAct: Synergizing Reasoning and Acting in Language Models.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification ReAct: Synergizing Reasoning and Acting in Language Models

Reference 25

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no resolver link, observed 2026-08-06T17:15:44.262596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 2f8f36ed-15ac-4873-af44-7342ae3d0e23 · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Tree of thoughts: Deliberate problem solving with large language models,

Reference 26

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation b6143fe1-f56b-4021-8876-d1c9ed460586 · outbound

This paper cites In-context retrieval-augmented language models,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification In-context retrieval-augmented language models,

Reference 27

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Source-reported events for the cited work

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

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Observation 1228d12e-22fa-4720-a74c-e32a921e9b1a · outbound

This paper cites Improving language models by retrieving from trillions of tokens,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Improving language models by retrieving from trillions of tokens,

Reference 28

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raw_fallback, observed 2026-08-06T17:15:44.903935Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:15:44.281264Z digest=sha256:d4d1d3b59c5ec1ac21d3cfe3c3a6f7e5ad22e9ac9e5d456c33d77534e0477255

Observation 432f718e-f71f-4e18-ab9b-ba5a68681dc5 · outbound

This paper cites Webglm: Towards an efficient web-enhanced question answering system with human preferences,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Webglm: Towards an efficient web-enhanced question answering system with human preferences,

Reference 29

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raw_fallback, observed 2026-08-06T17:15:44.886693Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:15:44.287649Z digest=sha256:3becfb232731ed8cfc7b8066b8ffc4df68b256586a9b248597ab614b9da6c90f

Observation 1483eee7-bc76-44e8-a5e3-ab50508acb6f · outbound

This paper cites Pegasus: Pre-training with extracted gap-sentences for abstractive summarization,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Pegasus: Pre-training with extracted gap-sentences for abstractive summarization,

Reference 30

Resolution
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raw_fallback, observed 2026-08-06T17:15:44.868259Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:15:44.293669Z digest=sha256:5e1894b913c198b048d9992bb6c812a74fda872c71e928674883e6d0e9351b12

Observation a3af6f4b-0aeb-478d-ac42-900dc8fbb017 · outbound

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

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:15:44.298991Z digest=sha256:cdf747ab119c5fe2dc3cce15c5ad7ef90fd7e6cb43c58ad83f3e59c3e5a92d1e

Observation 550b6cfb-832d-41bc-b54e-2227a724676d · outbound

This paper cites Improving language understanding by generative pre-training,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Improving language understanding by generative pre-training,

Reference 32

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no resolver link, observed 2026-08-06T17:15:44.304951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:15:44.304951Z digest=sha256:cdc5499596902c92d8567f19943982a211bead3b00007319e3f02d0b525c29c1

Observation 3095eebd-7772-4718-8f46-9b432c287384 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 33

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:15:44.311722Z digest=sha256:7843e6a5294cd6a4bbfaf92bbac186fce75c0b0eb4131178209f24811f7761a2

Observation 1d9e004a-9e3a-4e6b-85de-69478b59ddf5 · outbound

This paper cites Dense Passage Retrieval for Open-Domain Question Answering.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Dense Passage Retrieval for Open-Domain Question Answering

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-06T17:15:44.317362Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:15:44.317362Z digest=sha256:9b6713c0d2093937ee13484e7ee98676e246eb12eb74bcdbf4efbe1560a26241

Observation 74d000c0-5df8-4577-8d25-d1b78cad69f4 · outbound

This paper cites One Embedder, Any Task: Instruction-Finetuned Text Embeddings.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification One Embedder, Any Task: Instruction-Finetuned Text Embeddings

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T17:15:44.323907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:15:44.323907Z digest=sha256:778bd3c80128c89b9651e6f736b51eb4eca15a152d4fdbc5b9478708f9d6f04f

Observation 91824627-31e4-491b-8e5c-b9e6bf6c226e · outbound

This paper cites Palm: Scaling language modeling with pathways,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Palm: Scaling language modeling with pathways,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:15:44.829564Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:15:44.329178Z digest=sha256:98a5b2882f20a1d5c9d1814c8a8b29e482e8e9c29988394f07b9db33260bef26

Observation dc97d2bc-36e3-41ed-982d-f3c5a83550fa · outbound

This paper cites Adversarial Retriever-Ranker for dense text retrieval.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Adversarial Retriever-Ranker for dense text retrieval

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T17:15:44.334814Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:15:44.334814Z digest=sha256:23835122ef3ecb071ab5cc60f3d4b449e8fffdd6e3b1c7eb56113fbee5f8de10

Observation 66ec70a9-8ad2-495a-9f3f-f4a6248251c1 · outbound

This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Self-Consistency Improves Chain of Thought Reasoning in Language Models

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T17:15:44.341658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:15:44.341658Z digest=sha256:8c10de761509a4ceaaaddea32a46ac1b7741b5e4df9c04a7350cc644e1e6a12f

Observation 09c09803-4771-4fe6-aed0-f2a9d315e0d9 · outbound

This paper cites Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T17:15:44.347608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:15:44.347608Z digest=sha256:c1710994261092bc67f6143aeb4c24a734a79e2aa9d38a4b7f4f3c94407c0cd7

Observation 553717d7-0062-4a6c-88b8-b023ca381562 · outbound

This paper cites Fakenewsnet: A data repository with news content, social context, and spatiotemporal information for studying fake news on social media,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Fakenewsnet: A data repository with news content, social context, and spatiotemporal information for studying fake news on social media,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:15:44.810502Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:15:44.354195Z digest=sha256:0df116d50458a411df1b5283946216077e45d8e7ec3ee4c9e216b6ecb8ae6599

Observation 1b6230c5-b6b5-4896-a5bf-beff2d358407 · outbound

This paper cites KGV: Integrating Large Language Models with Knowledge Graphs for Cyber Threat Intelligence Credibility Assessment.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification KGV: Integrating Large Language Models with Knowledge Graphs for Cyber Threat Intelligence Credibility Assessment

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T17:15:44.359359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:15:44.359359Z digest=sha256:07e98f0dae421c96bd7deeeb056a08fca3c3623bb19682eb5538a58ad6d668b0

Observation c0784362-7025-4245-80d2-70a8a415fc09 · outbound

This paper cites Evidence-aware hierarchical interactive attention networks for explainable claim verifi- cation,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Evidence-aware hierarchical interactive attention networks for explainable claim verifi- cation,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:15:44.793196Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:15:44.364781Z digest=sha256:f12a91608a079d7f40b8d4e5a723ff605707803828bc7d862db46daed452ba99

Observation f9cd5687-6a61-4ff0-ad69-29472c434031 · outbound

This paper cites Chatgpt-3.5 turbo,.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Chatgpt-3.5 turbo,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:15:44.775091Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:15:44.370932Z digest=sha256:1a57f5ac390345ae424ac1005f1347933daa0fbbaa55faefdb78a9dbe8001356

Observation 65e9fcd0-f487-40e0-9acf-2d296c514a46 · outbound

This paper cites ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-06T17:15:44.377788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:15:44.377788Z digest=sha256:e01ae7d27174e2b59f48d8bc4c7c5d8c3d1e285cd930c073eda9cbb2d357a9c8

Observation 8f34a159-81d0-4fbf-aacf-bce1529d4d05 · outbound

This paper cites Fact-Checking Complex Claims with Program-Guided Reasoning.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification Fact-Checking Complex Claims with Program-Guided Reasoning

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T17:15:44.383025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:15:44.383025Z digest=sha256:079d69fd60e02a093e3f1528a84f1727087fed838f56fb5c6dcd277f76f3c5cf

Observation a9bf17cb-7d75-4d58-971a-2c67098c0989 · outbound

This paper cites These sentences should form a set \( R \).

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification These sentences should form a set \( R \)

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:15:44.757190Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:15:44.388803Z digest=sha256:238a38d17aaa399a7f57a7dae4957d8b3fc47c6608c763553f611ab4c0cc54f0

Observation 661efa04-84b2-4ac1-8fb5-d4cb96e24ad7 · outbound

This paper cites {Insert CTI content here}.

LRCTI: A Large Language Model-Based Framework for Multi-Step Evidence Retrieval and Reasoning in Cyber Threat Intelligence Credibility Verification {Insert CTI content here}

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T17:15:44.736868Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T17:15:44.394024Z digest=sha256:db632090e211e68b4a2e49fcd26b1fcc70ec58c402c67b46f3c6ea044bc82da8

Pith citing papers

No inbound Pith citation observations are available.