Paper Citation Record · LEDGER

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity

As of 18 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 1 inbound Pith citation observation for arXiv:2507.05816.

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

pith.paper-citation-record.v1
2507.05816 v1

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:21:59.080689Z

measured 59 of 59 standing notices

One-hop event checks from named stored sources.

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:27:18.985888Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T12:27:19.085288Z

Reference resolution

58 of 58 outbound references displayed

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External citation measurements

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Outbound references

Observation 6f5f8c9a-0696-4054-a457-bcc2e15ced8f · outbound

This paper cites The llama 4 herd: The beginning of a new era of natively multimodal ai innovation,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity The llama 4 herd: The beginning of a new era of natively multimodal ai innovation,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:03.865341Z

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Observation 5476cabf-d566-4897-ad6c-9cd2be91e82f · outbound

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

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 2

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Observation 193446ab-dfd6-44fa-9bd2-9573b283b8eb · outbound

This paper cites From softmax to nucleusmax: A novel sparse language model for chinese radiology report summarization,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity From softmax to nucleusmax: A novel sparse language model for chinese radiology report summarization,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:03.845243Z

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Observation d9683f5d-a067-4bc5-aaea-fc2167d20f65 · outbound

This paper cites Uni-Retrieval: A Multi-Style Retrieval Framework for STEM's Education.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Uni-Retrieval: A Multi-Style Retrieval Framework for STEM's Education

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-08-06T19:22:00.026476Z

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Observation 159cf43c-1dda-439e-ac4f-690a66397778 · outbound

This paper cites Towards robust evaluation of stem education: Leveraging mllms in project-based learning,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Towards robust evaluation of stem education: Leveraging mllms in project-based learning,

Reference 5

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Observation e5537a60-a95d-4c3b-b2f4-afeed8ffef03 · outbound

This paper cites From Query to Explanation: Uni-RAG for Multi-Modal Retrieval-Augmented Learning in STEM.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity From Query to Explanation: Uni-RAG for Multi-Modal Retrieval-Augmented Learning in STEM

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T19:21:55.518850Z

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Observation d0538884-6aae-4a0d-b762-14969e6c7eec · outbound

This paper cites BloombergGPT: A Large Language Model for Finance.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity BloombergGPT: A Large Language Model for Finance

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T19:21:55.595765Z

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Observation 6d32b85b-aa3a-4815-92a3-2d74d4662d1f · outbound

This paper cites Cross-modal knowledge diffusion-based generation for difference-aware medical vqa,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Cross-modal knowledge diffusion-based generation for difference-aware medical vqa,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:03.816517Z

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Observation 411c75ef-beaf-44f3-b95e-f58d06e11190 · outbound

This paper cites A survey of large language models for healthcare: from data, technology, and applications to accountability and ethics,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity A survey of large language models for healthcare: from data, technology, and applications to accountability and ethics,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:03.788209Z

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Observation 408ed323-664b-480b-81ed-cc9d884d2048 · outbound

This paper cites Harnessing the potential of multimodal ehr data: A comprehensive survey of clinical predictive modeling for intelligent healthcare,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Harnessing the potential of multimodal ehr data: A comprehensive survey of clinical predictive modeling for intelligent healthcare,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:03.762656Z

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Observation 5ce02ed5-26a6-4906-8c37-9b5c1d020176 · outbound

This paper cites Chimed-gpt: A chinese medical large language model with full training regime and better alignment to human preferences,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Chimed-gpt: A chinese medical large language model with full training regime and better alignment to human preferences,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:03.728859Z

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Observation 81eaebc2-49f5-4328-8124-80704bfd4531 · outbound

This paper cites Megacare: Knowledge-guided multi-view hypergraph predictive framework for healthcare,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Megacare: Knowledge-guided multi-view hypergraph predictive framework for healthcare,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:03.700094Z

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Observation b6eec42a-47b3-4058-bd1f-79e1a73d9074 · outbound

This paper cites The ability of large language models to generate patient information materials for retinopathy of prematurity: Evaluation of readability, accuracy, and comprehensiveness,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity The ability of large language models to generate patient information materials for retinopathy of prematurity: Evaluation of readability, accuracy, and comprehensiveness,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:03.676973Z

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Observation a0ca57f7-e96e-4d0d-b314-b8294102cc43 · outbound

This paper cites International classification of retinopathy of prematurity,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity International classification of retinopathy of prematurity,

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:03.640553Z

Source-reported events for the cited work

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Observation 5bd4c860-cb9c-4699-a71d-2467306fb03d · outbound

This paper cites Research progress on the risk factors of retinopathy of prematurity,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Research progress on the risk factors of retinopathy of prematurity,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:03.607253Z

Source-reported events for the cited work

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Observation 8b5c2c1f-fa44-4afd-a151-63be37272f4a · outbound

This paper cites Oxygenation fluctuations associated with severe retinopathy of prematurity: Insights from a multimodal deep learning approach,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Oxygenation fluctuations associated with severe retinopathy of prematurity: Insights from a multimodal deep learning approach,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:03.572922Z

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Observation 11aeda18-4c29-4b6d-91fd-0b6d323567c4 · outbound

This paper cites Development and validation of a deep learning model to predict the occurrence and severity of retinopathy of prematurity.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Development and validation of a deep learning model to predict the occurrence and severity of retinopathy of prematurity

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:03.545831Z

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Observation 308929e8-4094-4fa0-b616-8cff97ec0bcb · outbound

This paper cites Exploring cognitive and aesthetic causality for multimodal aspect-based sentiment analysis,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Exploring cognitive and aesthetic causality for multimodal aspect-based sentiment analysis,

Reference 18

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Observation 5a89710f-5b7e-4c1a-a968-57f5fa468378 · outbound

This paper cites Seeing sound, hearing sight: Uncovering modality bias and conflict of ai models in sound localization,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Seeing sound, hearing sight: Uncovering modality bias and conflict of ai models in sound localization,

Reference 19

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This paper cites Time Matters: Examine Temporal Effects on Biomedical Language Models.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Time Matters: Examine Temporal Effects on Biomedical Language Models

Reference 20

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Observation c566cf33-98a0-40f1-ba1d-2bf7628ca069 · outbound

This paper cites Has multimodal learning delivered universal intelligence in healthcare? a comprehensive survey,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Has multimodal learning delivered universal intelligence in healthcare? a comprehensive survey,

Reference 21

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Observation d0815713-e4bd-41d1-be1d-0f1f02ac8272 · outbound

This paper cites Chain-of-Interaction: Enhancing Large Language Models for Psychiatric Behavior Understanding by Dyadic Contexts.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Chain-of-Interaction: Enhancing Large Language Models for Psychiatric Behavior Understanding by Dyadic Contexts

Reference 22

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Observation c4715837-2dbb-4232-b641-d992d3f1094c · outbound

This paper cites Evaluating multiple large language models in pediatric ophthalmology.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Evaluating multiple large language models in pediatric ophthalmology

Reference 23

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Observation 38623464-b9b6-4667-9160-c506e909307d · outbound

This paper cites Exploring the role of chatgpt-4, bingai, and gemini as virtual consultants to educate families about retinopathy of prematurity,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Exploring the role of chatgpt-4, bingai, and gemini as virtual consultants to educate families about retinopathy of prematurity,

Reference 24

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Observation 05cc2c39-c9d7-46fb-bbce-b420a6002a5f · outbound

This paper cites Ermis, E.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Ermis, E

Reference 25

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Observation c72061c0-23b7-4acf-94c0-e8b3dc286695 · outbound

This paper cites Ffa-gpt: an interactive visual question answering system for fundus fluorescein angiography,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Ffa-gpt: an interactive visual question answering system for fundus fluorescein angiography,

Reference 26

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Observation 8c35e0d5-0ae9-4b7b-b357-ddc56a28fdec · outbound

This paper cites Fine-tuning Large Language Model (LLM) Artificial Intelligence Chatbots in Ophthalmology and LLM-based evaluation using GPT-4.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Fine-tuning Large Language Model (LLM) Artificial Intelligence Chatbots in Ophthalmology and LLM-based evaluation using GPT-4

Reference 27

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Observation b171dea8-c3b2-4326-8538-abdaca7ab5de · outbound

This paper cites Advancing question-answering in ophthalmology with retrieval augmented generations (rag): Benchmarking open-source and proprietary large language models,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Advancing question-answering in ophthalmology with retrieval augmented generations (rag): Benchmarking open-source and proprietary large language models,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:03.409522Z

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Observation 8d711db2-7a0d-4fbe-aabe-31b7cd6fabc9 · outbound

This paper cites Deep dive in retinal fundus image segmentation using deep learning for retinopathy of prematurity,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Deep dive in retinal fundus image segmentation using deep learning for retinopathy of prematurity,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:03.390328Z

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Observation 27873f91-b8a4-4ced-b7f1-108618c06ab5 · outbound

This paper cites Deep learning-assisted retinopathy of prematurity (rop) screening,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Deep learning-assisted retinopathy of prematurity (rop) screening,

Reference 30

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Observation 51acaf04-f4a8-4465-ae53-d9aac675d428 · outbound

This paper cites Automated diagnosis of retinopathy of prematurity from retinal images of preterm infants using hybrid deep learning techniques,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Automated diagnosis of retinopathy of prematurity from retinal images of preterm infants using hybrid deep learning techniques,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:03.345922Z

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Observation 84624af8-f2d1-4478-affe-a0dbd01e1443 · outbound

This paper cites Evaluation of a deep learning image assessment system for detecting severe retinopathy of prematurity,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Evaluation of a deep learning image assessment system for detecting severe retinopathy of prematurity,

Reference 32

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Observation bb7109ed-cb16-4012-9a4b-d8cdd35d0b06 · outbound

This paper cites Atlantis: Aesthetic-oriented multiple granularities fusion network for joint multimodal aspect-based sentiment analysis,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Atlantis: Aesthetic-oriented multiple granularities fusion network for joint multimodal aspect-based sentiment analysis,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:02.852408Z

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Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Vanessa: Visual connotation and aesthetic attributes understanding network for multimodal aspect-based sentiment analysis,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:02.569912Z

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This paper cites Emo-bias: A large scale evaluation of social bias on speech emotion recognition,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Emo-bias: A large scale evaluation of social bias on speech emotion recognition,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:02.345319Z

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Observation cd2ddbcb-4f2a-4543-8745-469c9d04536e · outbound

This paper cites Understanding latent affective bias in large pre-trained neural language models,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Understanding latent affective bias in large pre-trained neural language models,

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:02.085286Z

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Observation 524e6c45-1675-419b-a313-c54a2d469788 · outbound

This paper cites Active learning with complementary sampling for instructing class-biased multi-label text emotion classification,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Active learning with complementary sampling for instructing class-biased multi-label text emotion classification,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:01.873655Z

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Observation ce53d8e5-5e66-4b0b-84ac-cf19862814f8 · outbound

This paper cites The biases of pre-trained language models: An empirical study on prompt-based sentiment analysis and emotion detection,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity The biases of pre-trained language models: An empirical study on prompt-based sentiment analysis and emotion detection,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:01.674141Z

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Observation 87dae848-3695-458c-99f2-93c837ed3107 · outbound

This paper cites Screening examination of premature infants for retinopathy of prematurity,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Screening examination of premature infants for retinopathy of prematurity,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:01.490219Z

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Observation 83523a73-9017-4aa2-ba17-d5100bd21c07 · outbound

This paper cites Optimised retinopathy of prematurity screening guideline in china based on a 5-year cohort study,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Optimised retinopathy of prematurity screening guideline in china based on a 5-year cohort study,

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:01.373713Z

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Observation 8e3b6115-b64f-4b83-95b0-77e242566d21 · outbound

This paper cites The probabilistic relevance framework: Bm25 and beyond,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity The probabilistic relevance framework: Bm25 and beyond,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:01.271177Z

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Observation 25661d09-4918-41c9-bf45-9cc154eeefe2 · outbound

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

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

Reference 42

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Observation f8803a40-750c-45a1-8dd9-295a3fd7d161 · outbound

This paper cites Gemma 2: Improving open language models at a practical size,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Gemma 2: Improving open language models at a practical size,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:01.163247Z

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Observation 256a4155-5dfc-411b-918d-56c8b0e98e78 · outbound

This paper cites Yi: Open Foundation Models by 01.AI.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Yi: Open Foundation Models by 01.AI

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-06T19:21:58.121374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59a1e186-1aa5-48e8-a4a4-c1da9bc991f5 · outbound

This paper cites Mixtral of Experts.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Mixtral of Experts

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-06T19:21:58.167354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7e3e49e-38a1-4c70-9614-40ebecc44f45 · outbound

This paper cites Llama 3 model card,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Llama 3 model card,

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T19:21:58.221008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2298c2e2-fae4-4cf3-b4d3-b0dbf18caa39 · outbound

This paper cites Qwen3: Think Deeper, Act Faster,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Qwen3: Think Deeper, Act Faster,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:01.039544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation db2c3df3-eaac-4315-8d37-4e1186657d97 · outbound

This paper cites Qwen2.5: A party of foundation models,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Qwen2.5: A party of foundation models,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:00.916186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7b226345-d860-459a-84db-3b27eec47257 · outbound

This paper cites Training language models to follow instructions with human feedback,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Training language models to follow instructions with human feedback,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:00.824515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 22062b34-de72-4563-bbe3-35e797edb2f7 · outbound

This paper cites GPT-4 Technical Report.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity GPT-4 Technical Report

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T19:21:58.544193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 954620cf-9416-43ee-a97f-d1c0c5204118 · outbound

This paper cites GPT-4o System Card.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity GPT-4o System Card

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T19:21:58.624350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd5cb537-d5bf-49f7-ad25-d885d4b45211 · outbound

This paper cites Doubao pro models,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Doubao pro models,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:00.723459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6e314a2b-3a78-41c4-bc52-6858a3ec7710 · outbound

This paper cites Introducing ernie 3.5: Baidu’s knowledge enhanced foundation model takes a giant leap forward,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Introducing ernie 3.5: Baidu’s knowledge enhanced foundation model takes a giant leap forward,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:00.611226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 491aa3d3-7078-4b89-8387-b0629d2ca842 · outbound

This paper cites Baichuan,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Baichuan,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:00.514369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 762a8d76-1608-4e03-9376-ab9d07df7392 · outbound

This paper cites The claude 3 model family: Opus, sonnet, haiku,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity The claude 3 model family: Opus, sonnet, haiku,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:00.426180Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 0b9bf5f5-fca0-4474-992a-0964a978bb22 · outbound

This paper cites HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-06T19:21:58.941883Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5cf0877-9e67-47a5-9bd0-b6d1b762bb97 · outbound

This paper cites Openbiollms: Advancing open-source large language models for healthcare and life sciences,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Openbiollms: Advancing open-source large language models for healthcare and life sciences,

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:00.283771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d595fafb-204b-48e6-b49c-25aa1525807a · outbound

This paper cites Lora: Low-rank adaptation of large language models,.

Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity Lora: Low-rank adaptation of large language models,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:22:00.186557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation d92b7ffa-1d1f-4630-ad2f-ba1284bc1d45 · inbound

HRIPBench: Benchmarking LLMs in Harm Reduction Information Provision to Support People Who Use Drugs cites this paper.

HRIPBench: Benchmarking LLMs in Harm Reduction Information Provision to Support People Who Use Drugs Affective-ROPTester: Capability and Bias Analysis of LLMs in Predicting Retinopathy of Prematurity

Reference 52

Resolution: verified exact; local_arxiv, observed 2026-08-06T12:27:19.093731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.