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Paper Citation Record · LEDGER

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology

As of 10 August 2026, this Paper Citation Record lists 67 of 67 outbound references and 1 inbound Pith citation observation for arXiv:2502.01243.

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

pith.paper-citation-record.v1
2502.01243 v1

Coverage vector

measured 67 of 67 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T16:10:24.939025Z

measured 68 of 68 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T15:28:47.559357Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T15:28:49.752882Z

Reference resolution

67 of 67 outbound references displayed

  • verified exact0
  • verified fuzzy34
  • unresolved33
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7e99fa3b-888c-4a5c-90f2-199ff7fc5cd1 · outbound

This paper cites Language models are few-shot learners.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Language models are few-shot learners

Reference 1

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verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.760346Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.678965Z digest=sha256:208fd947adb935b834ad758e49782c75c422a031c5ec5aa74942e988a3b58f54

Observation 1de9be11-abb6-45fd-949e-25ebf9fae69d · outbound

This paper cites Gpt-4 technical report.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Gpt-4 technical report

Reference 2

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raw_fallback, observed 2026-08-09T16:10:25.747043Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.683514Z digest=sha256:0167d4c37f20c3550d8962d18dc721784703bf8697660421fecbef79ec60bc55

Observation a41e2ddc-1d59-44ec-bd1e-246b0d7f4905 · outbound

This paper cites Large language models encode clinical knowledge.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Large language models encode clinical knowledge

Reference 3

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raw_fallback, observed 2026-08-09T16:10:25.735523Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.688490Z digest=sha256:56235063eacc3cc9cfe1b078456264ddf556c32e755da8b9f856ce7fad213ad3

Observation 0d3b57c8-360b-4980-8481-7f8ab45a301a · outbound

This paper cites Empowering biomedical discovery with ai agents.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Empowering biomedical discovery with ai agents

Reference 4

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verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.724649Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.692316Z digest=sha256:1854401f315c1cd5cc32a7e5a71fe6687f48926cf8aafc71dff9d99427faa0fa

Observation e97a4fec-78c5-490b-9977-a1b61d53dbdd · outbound

This paper cites A Survey on Large Language Models for Critical Societal Domains: Finance, Healthcare, and Law.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology A Survey on Large Language Models for Critical Societal Domains: Finance, Healthcare, and Law

Reference 5

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unresolved
no resolver link, observed 2026-08-09T16:10:24.696498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.696498Z digest=sha256:89873ce46f70364f040e03b2b8de36434a0fa4cc90572af79013155afb056f0b

Observation 6e62f7f1-09b0-4069-89fb-fe5ad06c5a24 · outbound

This paper cites Integrated image- based deep learning and language models for primary diabetes care.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Integrated image- based deep learning and language models for primary diabetes care

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.712403Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.700872Z digest=sha256:e68c1ba99aad83c626291fd93655b4dbfc8127243970915eb55dce6700c62789

Observation 8d44da20-e9a1-42d2-9b23-0aee28cfa1b5 · outbound

This paper cites Evaluating large language models on medical evidence summarization.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Evaluating large language models on medical evidence summarization

Reference 7

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raw_fallback, observed 2026-08-09T16:10:25.700623Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.705174Z digest=sha256:ee91e572d0b73c3dbcc8c43456613ae535c12e86df28112eda84ae7e2c9a0764

Observation bc5c8d60-4222-432e-b65e-4f1038fa2f4b · outbound

This paper cites Adapted large language models can outperform medical experts in clinical text summarization.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Adapted large language models can outperform medical experts in clinical text summarization

Reference 8

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raw_fallback, observed 2026-08-09T16:10:25.688533Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.708747Z digest=sha256:87aa73aa797e6a757260b17bed5a78e80492ee2fd594d3e09983f47f3e65ef78

Observation 5fe34d09-1522-47b6-80be-77a2e93fb158 · outbound

This paper cites A strategy for cost-effective large language model use at health system-scale.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology A strategy for cost-effective large language model use at health system-scale

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.676461Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.712213Z digest=sha256:28006c5cf8d3ce9d535d40f5ae6edb639422fb0f5a0ed0536450c767dc3001c0

Observation 182b487d-c709-4e94-8f91-c865bc0549c7 · outbound

This paper cites Matching patients to clinical trials with large language models.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Matching patients to clinical trials with large language models

Reference 10

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verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.663887Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.716163Z digest=sha256:72ca752c739e12bd837a6e6663f169f1d7d1b0c2e872bf89df92b8af639f0055

Observation a4da407d-a80b-4065-b7fb-d86764577b6f · outbound

This paper cites Scaling clinical trial matching using large language models: a case study in oncology.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Scaling clinical trial matching using large language models: a case study in oncology

Reference 11

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verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.652381Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.720054Z digest=sha256:d2a37e9f053bf757577fdfaecdf18e217c97e8857d55c18c8ecded8b12bbf9f6

Observation da2f6e5f-dd5a-4797-8de1-143aa2b10568 · outbound

This paper cites Chatgpt and other large language models are double-edged swords, 2023.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Chatgpt and other large language models are double-edged swords, 2023

Reference 12

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verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.640220Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.723503Z digest=sha256:aa73a335b37e1b3585acd23436ed5beb7fb6326115ad8a9a794fa49fa29afe44

Observation bf522576-4202-40ae-b728-d052f4c49912 · outbound

This paper cites Ethics of large language models in medicine and medical research.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Ethics of large language models in medicine and medical research

Reference 13

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raw_fallback, observed 2026-08-09T16:10:25.628493Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.727096Z digest=sha256:ed888f9f743c0e891a37f193ecee4c36a7606b9d700fcf8a0b9322796ecb79ea

Observation c874e2de-d98c-4048-bf06-dc518f7af110 · outbound

This paper cites The ethics of chatgpt in medicine and healthcare: a systematic review on large language models (llms).

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology The ethics of chatgpt in medicine and healthcare: a systematic review on large language models (llms)

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.616731Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.730761Z digest=sha256:d8a9cd4e0dcc659cec1c72d00ba0693b432c420bd54d0c8f74cee6ddafa34e02

Observation a4f1d673-17c7-49cb-a5a8-2ab014bf55a3 · outbound

This paper cites Clinical large language models with misplaced focus.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Clinical large language models with misplaced focus

Reference 15

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raw_fallback, observed 2026-08-09T16:10:25.604718Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.734504Z digest=sha256:dc444b06cd486fa283bf89afc319394cc7850e1b25ccdaca3cb58390c476d160

Observation d3b74ea7-6568-4de2-9581-ade055a3e330 · outbound

This paper cites Medmcqa: A large-scale multi-subject multi-choice dataset for medical domain question answering.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Medmcqa: A large-scale multi-subject multi-choice dataset for medical domain question answering

Reference 16

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raw_fallback, observed 2026-08-09T16:10:25.593609Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.737963Z digest=sha256:b516b63568a747735ba2464972aee2cd26d1d9f997d6d67a1209a5706f8780f7

Observation b76d961a-4776-4dd0-b14d-602468740e1c · outbound

This paper cites MedCalc-Bench: Evaluating Large Language Models for Medical Calculations.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology MedCalc-Bench: Evaluating Large Language Models for Medical Calculations

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.741545Z digest=sha256:99d4d7076f17986c832f2043961c527f4b4120a65764d98ea3c8ab2a263b7602

Observation a8cc993e-f3a7-42a1-b109-dd93db1cb612 · outbound

This paper cites LongHealth: A Question Answering Benchmark with Long Clinical Documents.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology LongHealth: A Question Answering Benchmark with Long Clinical Documents

Reference 18

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no resolver link, observed 2026-08-09T16:10:24.745537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.745537Z digest=sha256:5d79ed9e87f908fe62ef8c392f12aa5dd79c632668666bb3121bb830230090b4

Observation 923368a5-8d70-4a75-a643-63a5321f5411 · outbound

This paper cites CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark

Reference 19

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no resolver link, observed 2026-08-09T16:10:24.749724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.749724Z digest=sha256:ec7cb94b399ffb31089c0d8713a455e0748aa65481680394fa04f24e48db1b4a

Observation 52a7410b-c299-43fc-8f7b-65288a1214c1 · outbound

This paper cites case of the month.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology case of the month

Reference 20

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raw_fallback, observed 2026-08-09T16:10:25.580838Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.753613Z digest=sha256:e36c638dc5c6c8a5cb2fb318fdabff9346240bfef27a772a0ffde14759672604

Observation 08b4cb75-e5d1-4176-a539-5258376ce987 · outbound

This paper cites Accuracy and reliability of chatbot responses to physician questions.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Accuracy and reliability of chatbot responses to physician questions

Reference 21

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raw_fallback, observed 2026-08-09T16:10:25.569108Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.757046Z digest=sha256:763ae1e14b03ddd4c38132ee8186180f5e39f836875e5ef6d07d6af3271539ff

Observation d295919a-1296-4748-8b26-6cdc5da31ebe · outbound

This paper cites Capabilities of gpt-4 in ophthalmology: an analysis of model entropy and progress towards human-level medical question answering.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Capabilities of gpt-4 in ophthalmology: an analysis of model entropy and progress towards human-level medical question answering

Reference 22

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raw_fallback, observed 2026-08-09T16:10:25.556229Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.760571Z digest=sha256:49b5d46e3e4de17c161108b15f28240822792bab5226b3161eb9dbdce2d5081d

Observation 0f6d3176-eabc-423b-85c6-d0d35b2d3257 · outbound

This paper cites Comparison of ophthalmologist and large language model chatbot responses to online patient eye care questions.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Comparison of ophthalmologist and large language model chatbot responses to online patient eye care questions

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.544626Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.763952Z digest=sha256:8e58c7ee6fe8417ac76cb1e3a030179840804208c80d3866c54cb23b3a5b1069

Observation 2a944e9d-4e16-4d65-b16e-455948925008 · outbound

This paper cites Eval- uation and mitigation of the limitations of large language models in clinical decision-making.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Eval- uation and mitigation of the limitations of large language models in clinical decision-making

Reference 24

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verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.532999Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.768000Z digest=sha256:5de0ddfafe3f15690171a88548558376e7540a186f26f06c1a93d36ad48ccf46

Observation aa21e586-7bd3-457d-8355-710588fe5e0d · outbound

This paper cites Assessing the utility of chatgpt throughout the entire clinical workflow: development and usability study.J.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Assessing the utility of chatgpt throughout the entire clinical workflow: development and usability study.J

Reference 25

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verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.520990Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.771483Z digest=sha256:bbf79a791b10b72e2855ad93d947bca28745989d96acfca905074ca67f569ad6

Observation 3abfeb09-357f-4ed7-a9ed-cd5a0c6b1ec4 · outbound

This paper cites Benchmarking large language models’ performances for myopia care: a comparative analysis of chatgpt- 3.5, chatgpt-4.0, and google bard.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Benchmarking large language models’ performances for myopia care: a comparative analysis of chatgpt- 3.5, chatgpt-4.0, and google bard

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.508808Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.775135Z digest=sha256:bda20e2bcf1766e24a3f1b051bc906012c3ac1868799706b59bf44495f323996

Observation 10b8a1cc-80fb-48e3-bee7-a67abab142e6 · outbound

This paper cites an unresolved cited work.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Unresolved cited work

Reference 27

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unresolved
raw_fallback, observed 2026-08-09T16:10:25.496109Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.779033Z digest=sha256:78b743a2b406c34611fc8e883924dd8c48fce1874830b919d161562332ce6072

Observation 19d09383-f60a-4b06-91c2-6e860c2edb0c · outbound

This paper cites Performance of large language models on medical oncology examination questions.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Performance of large language models on medical oncology examination questions

Reference 28

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raw_fallback, observed 2026-08-09T16:10:25.483260Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.782880Z digest=sha256:9c5a508feaac2781c359fd85d17b8f37bb4a9bcbe7c425edf694998e70237c92

Observation 04624a96-4206-4d55-9dfa-f084ee9eb189 · outbound

This paper cites Assessment of a large lan- guage model’s responses to questions and cases about glaucoma and retina management.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Assessment of a large lan- guage model’s responses to questions and cases about glaucoma and retina management

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.471017Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.786529Z digest=sha256:f33ab78e58724021a27a15b67b674c79dd3e24dcbd6bd31dda6b17c607ab9ca2

Observation 5d08a686-870b-49d0-8346-787cd400db66 · outbound

This paper cites What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams

Reference 30

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unresolved
no resolver link, observed 2026-08-09T16:10:24.790099Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.790099Z digest=sha256:63f8cefc466265966a64c4c35f9446168cb1535a4079c58d8c0bb0801c4ccf44

Observation ceff7c40-0281-4790-aa80-bf67584a4be2 · outbound

This paper cites Medmcqa: A large-scale multi-subject multi-choice dataset for medical domain question answering.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Medmcqa: A large-scale multi-subject multi-choice dataset for medical domain question answering

Reference 31

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verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.457888Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.793887Z digest=sha256:c7aa86800745cd371370a92ca0b38840a12f9b8f05b7aca22997c724525fc065

Observation 2311a256-556e-4f71-98ca-186de61b45c2 · outbound

This paper cites Benchmarking large language models on cmexam-a comprehensive chinese medical exam dataset.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Benchmarking large language models on cmexam-a comprehensive chinese medical exam dataset

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.447084Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.798044Z digest=sha256:949b11eff09d167684c43bf28c1005381cfc6506d14d1193cded9c319cbdd0ce

Observation 617b143a-964f-4a98-9b4a-5eacc8cc4831 · outbound

This paper cites Medbench: A large- scale chinese benchmark for evaluating medical large language models.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Medbench: A large- scale chinese benchmark for evaluating medical large language models

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.435761Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.801431Z digest=sha256:b921941170d2447b82ad3dd335cb7baf44003d7f8f847f6e61bbe5305be775de

Observation f673d7e5-430d-48c9-94d8-88119444602f · outbound

This paper cites JMedBench: A Benchmark for Evaluating Japanese Biomedical Large Language Models.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology JMedBench: A Benchmark for Evaluating Japanese Biomedical Large Language Models

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.805634Z digest=sha256:227e2e6402daec417d01dd1e750fd47d4d1f17f401f214fe73d81b7be35abfc7

Observation bc0ad3c2-dcb6-41d1-9372-a96d7608da06 · outbound

This paper cites an unresolved cited work.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Unresolved cited work

Reference 35

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raw_fallback, observed 2026-08-09T16:10:25.424731Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.809987Z digest=sha256:2b1403ad69fa3c6fa1ee2514942c9c6deaa0afb6f1ef2d5f23e427316470247f

Observation c57837f2-3a88-4656-b7a3-39b439c99c3a · outbound

This paper cites TCMBench: A Comprehensive Benchmark for Evaluating Large Language Models in Traditional Chinese Medicine.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology TCMBench: A Comprehensive Benchmark for Evaluating Large Language Models in Traditional Chinese Medicine

Reference 36

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no resolver link, observed 2026-08-09T16:10:24.814407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.814407Z digest=sha256:81dfd87ae18b9ba90581ef44c3c665a9902cd96cb891bffa260008ef67ed2936

Observation d482c786-74a1-4a91-b16e-9883d91b5654 · outbound

This paper cites ProSA: Assessing and Understanding the Prompt Sensitivity of LLMs.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology ProSA: Assessing and Understanding the Prompt Sensitivity of LLMs

Reference 37

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no resolver link, observed 2026-08-09T16:10:24.818576Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.818576Z digest=sha256:a382332d68e3fa75abf68c58b31e457c46326cdf7481ce981c38c31320c1e004

Observation 2a71d522-7843-4352-9b75-b8e446b01855 · outbound

This paper cites Generalization or Memorization: Data Contamination and Trustworthy Evaluation for Large Language Models.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Generalization or Memorization: Data Contamination and Trustworthy Evaluation for Large Language Models

Reference 38

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no resolver link, observed 2026-08-09T16:10:24.822355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.822355Z digest=sha256:a57e6363e0a80abac4a5d38a01c891ce43d954becc121d250da2bafb7f033382

Observation e820c545-33ae-423f-92a6-4eb234ebc7d3 · outbound

This paper cites Promptcblue: A chinese prompt tuning benchmark for the medical domain.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Promptcblue: A chinese prompt tuning benchmark for the medical domain

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.411148Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.826194Z digest=sha256:1174bffedf0c865717e21714893857319170b60ee5afa0542a5f642d0d214884

Observation 799dc24d-aa5c-4314-b38e-520bde0bade2 · outbound

This paper cites CMB: A Comprehensive Medical Benchmark in Chinese.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology CMB: A Comprehensive Medical Benchmark in Chinese

Reference 40

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no resolver link, observed 2026-08-09T16:10:24.829663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.829663Z digest=sha256:f00748db543951796d75a657a5b3c5e38e632de510f82de3552cd6beb56f4a57

Observation 542fd470-72f3-4c92-bc67-fa278e2454c2 · outbound

This paper cites LLM-as-a-Judge & Reward Model: What They Can and Cannot Do.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology LLM-as-a-Judge & Reward Model: What They Can and Cannot Do

Reference 41

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no resolver link, observed 2026-08-09T16:10:24.833277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.833277Z digest=sha256:e8f270fb55bf7500194bb244941631330cfbe59efebc18c6ec96ed32aa3c6a56

Observation 1f0190b6-7b45-4a20-8858-e051a840d010 · outbound

This paper cites CompassJudger-1: All-in-one Judge Model Helps Model Evaluation and Evolution.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology CompassJudger-1: All-in-one Judge Model Helps Model Evaluation and Evolution

Reference 42

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no resolver link, observed 2026-08-09T16:10:24.837215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.837215Z digest=sha256:f5413232157621deb69546cf82b9bf3a647e691110ba2d488c053d960c867516

Observation 0238ef16-b694-4f66-b618-6eee003b9da5 · outbound

This paper cites an unresolved cited work.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-09T16:10:25.398747Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.840870Z digest=sha256:f1ddddb6dfba37b6a99dbae5951f5a45aefab3123b720e1002751164b8df350f

Observation 0332e790-72a3-4434-ac38-195cd9d7d6db · outbound

This paper cites PediaBench: A Comprehensive Chinese Pediatric Dataset for Benchmarking Large Language Models.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology PediaBench: A Comprehensive Chinese Pediatric Dataset for Benchmarking Large Language Models

Reference 44

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unresolved
no resolver link, observed 2026-08-09T16:10:24.844582Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.844582Z digest=sha256:e642f0de7c0f5931a138004bff58e075d91e6551eb4d9ec224e2e94f79bf9dfd

Observation 29c9148e-3065-47be-b73e-47d86c0a9184 · outbound

This paper cites Diagnostic reasoning prompts reveal the potential for large language model interpretability in medicine.NPJ Digital Medicine, 7(1):20, 2024.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Diagnostic reasoning prompts reveal the potential for large language model interpretability in medicine.NPJ Digital Medicine, 7(1):20, 2024

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.383395Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.848907Z digest=sha256:50f21ea056a4b758dbc837a50c28fe08e25105e06d6b59363372d9da3de1a63e

Observation a03514cf-7089-4836-a45a-84fffe257f78 · outbound

This paper cites Large language models and their impact in ophthalmology.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Large language models and their impact in ophthalmology

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.368559Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.852615Z digest=sha256:3b8668b41fd8338bc394dc6324d50daaaf58fa6cdffb5445cbf41e6a5ea23c2c

Observation 95626846-fcc5-4360-afec-46667e25a53b · outbound

This paper cites How i won singapore’s gpt-4 prompt engineering competition.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology How i won singapore’s gpt-4 prompt engineering competition

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.356894Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.856125Z digest=sha256:0cd63d93e11445995a118ca99f9d7ce4b9599b3cd4d4feb7609f6cfd619ab36e

Observation e2adcad7-6b1f-4bca-811c-b457c87c2e4e · outbound

This paper cites Alignbench: Benchmarking chinese alignment of large language models.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Alignbench: Benchmarking chinese alignment of large language models

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.344774Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.859553Z digest=sha256:9e6afef2a8faba55251c3c4b053f24d3db2666cb62890bc25eb38ee4f9787b41

Observation 7867d21b-fc2c-4486-8ce2-cd684a6d88ef · outbound

This paper cites Baichuan 2: Open Large-scale Language Models.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Baichuan 2: Open Large-scale Language Models

Reference 49

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unresolved
no resolver link, observed 2026-08-09T16:10:24.863235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.863235Z digest=sha256:fae62f1fd73e98b25cbbb7a6fffdb27116297ebaca49074fe34e6b216c542347

Observation c66560ef-6cd1-4834-9e99-49d37cb6c9f6 · outbound

This paper cites HuatuoGPT, towards Taming Language Model to Be a Doctor.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology HuatuoGPT, towards Taming Language Model to Be a Doctor

Reference 50

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no resolver link, observed 2026-08-09T16:10:24.867232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.867232Z digest=sha256:7e48d413b9996336577fafd2db6d518d00ccdcbd4512c991bbf20712d2228984

Observation 49c815b8-5cbb-4294-b0d1-7533aea3b265 · outbound

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

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs

Reference 51

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no resolver link, observed 2026-08-09T16:10:24.871252Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.871252Z digest=sha256:ea68d8618211b837daeb69024540193e832e2b99577450e4f2d180791c4aeb32

Observation 38af74d0-459f-4dcf-8bda-8b5ab6c35937 · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 52

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no resolver link, observed 2026-08-09T16:10:24.875085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.875085Z digest=sha256:70acdc06dc6d8a7ad3042f78725f89ff9d240656ac520befbe72c55453f59300

Observation e6d5d9ff-993a-41a4-b20b-8023d6e0f0cd · outbound

This paper cites The Llama 3 Herd of Models.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology The Llama 3 Herd of Models

Reference 53

Resolution
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no resolver link, observed 2026-08-09T16:10:24.879671Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.879671Z digest=sha256:f35f6e466c17668b762d2988533c61076e0e7b7dfd128efd242fa69fbf34507f

Observation 04f9f1ef-dd9e-4ef3-b304-73b2124f4664 · outbound

This paper cites Mistral 7B.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Mistral 7B

Reference 54

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no resolver link, observed 2026-08-09T16:10:24.884551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.884551Z digest=sha256:59875a7c2a76615c7181b191227d5c0181c082648a05260e585fc5e4a1a4579d

Observation 92b88e27-3741-40ac-a3f7-066036cc0196 · outbound

This paper cites Pulse: Pretrained and unified language service engine.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Pulse: Pretrained and unified language service engine

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.333032Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.888627Z digest=sha256:f4dd01acaab325ea410d902ac16fa18d63365b236e23fc28f3fddcb53a1e0ef1

Observation 0ffc44dc-3f9e-4072-ad93-5047c867595e · outbound

This paper cites Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone

Reference 56

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no resolver link, observed 2026-08-09T16:10:24.892214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.892214Z digest=sha256:529e5342ae7fd7744375e3fed4d16538c51744a942f7eec4b30df2161c24c5ed

Observation 5089a42f-448a-4ab3-b802-ee31256a8587 · outbound

This paper cites Qwen2.5 Technical Report.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Qwen2.5 Technical Report

Reference 57

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no resolver link, observed 2026-08-09T16:10:24.896839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.896839Z digest=sha256:6518d9fd085d47ef6a9e9da9f9f42ec55c4ddf4885c968ffaeabd94bf42cc6e4

Observation 2ba5ce7a-fd94-459e-8e69-a54ec54bef7f · outbound

This paper cites Sunsimiao: Chinese medicine llm.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Sunsimiao: Chinese medicine llm

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-09T16:10:25.320401Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-09T16:10:24.901000Z digest=sha256:d25d44fbfe1c3cfb2ef671ca982cacc0cefb2eac894c370c9a316727ec7d3681

Observation d0c82835-991b-431f-be27-acdbc325c613 · outbound

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

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Yi: Open Foundation Models by 01.AI

Reference 59

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no resolver link, observed 2026-08-09T16:10:24.906158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.906158Z digest=sha256:704a61b3c5f5eb659f961f37053e5c48980cac3330f648d105982ced4aaffd07

Observation 787bc067-66e8-493d-aa49-09e26bf4665c · outbound

This paper cites DeepSeek LLM: Scaling Open-Source Language Models with Longtermism.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

Reference 60

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unresolved
no resolver link, observed 2026-08-09T16:10:24.910143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.910143Z digest=sha256:c8338f2dcfa65948053fe8c342f04ae833f373a99e8d524079af88fc2ee04094

Observation 63b8aace-8179-418c-a570-6e8ba37b641e · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Gemma 2: Improving Open Language Models at a Practical Size

Reference 61

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no resolver link, observed 2026-08-09T16:10:24.914543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.914543Z digest=sha256:db05f78be7b2ff87a55d0ed1043f14652aa18ba37ee92ddc392404dc53df7a08

Observation c39933b6-4b92-4ea4-a584-cef701fc2252 · outbound

This paper cites Granite 3.0 language models, 2024.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Granite 3.0 language models, 2024

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-09T16:10:24.919428Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.919428Z digest=sha256:386315c8e365e735bd14d354ab913aea67ffb9328391123a5f6d58f4915f0d85

Observation c080ce6c-7d1b-468a-801a-5a99007e2d3f · outbound

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

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools

Reference 63

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unresolved
no resolver link, observed 2026-08-09T16:10:24.923476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.923476Z digest=sha256:2f18a833637de76732e220b3ea14ae70b687c8aba5774c2884ff30c8a8b2f2d4

Observation 33d9a44c-321b-4024-a45e-3c6d7aea7a3f · outbound

This paper cites InternLM2 Technical Report.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology InternLM2 Technical Report

Reference 64

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unresolved
no resolver link, observed 2026-08-09T16:10:24.927331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.927331Z digest=sha256:7115042d4bdd5d6f41b245e0b5a4b41f87cffd8421d47e11cf9fc2eb7701b4e7

Observation 7071e68a-a6a1-400c-b327-0df162bf3b31 · outbound

This paper cites DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

Reference 65

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unresolved
no resolver link, observed 2026-08-09T16:10:24.931071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.931071Z digest=sha256:3e1aaa0e59e6d2a87fac78ddf1490a4912efde51d7e27d053a1e0ff08480c463

Observation 5a68a059-4596-4287-89b4-b991232b8963 · outbound

This paper cites Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by Tencent.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by Tencent

Reference 66

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no resolver link, observed 2026-08-09T16:10:24.934912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.934912Z digest=sha256:6a747c7ca29be590d9b70f8453b346804b2544f2ffc94443e9fa9584585b1ca8

Observation 9cda63fa-7b6c-4bb5-9f13-9021b92ca758 · outbound

This paper cites DeepSeek-V3 Technical Report.

OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology DeepSeek-V3 Technical Report

Reference 67

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unresolved
no resolver link, observed 2026-08-09T16:10:24.939025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T16:10:24.939025Z digest=sha256:8473391a75f8dd17544112a1e9f63d307df5d2d863493458c1bacae40ea5b520

Pith citing papers

Observation 71bd979c-52ef-432c-96cc-8e3fa3c7fbc4 · inbound

BEnchmarking LLMs for Ophthalmology (BELO) for Ophthalmological Knowledge and Reasoning cites this paper.

BEnchmarking LLMs for Ophthalmology (BELO) for Ophthalmological Knowledge and Reasoning OphthBench: A Comprehensive Benchmark for Evaluating Large Language Models in Chinese Ophthalmology

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:28:49.862916Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-06T15:28:47.559357Z digest=sha256:8f3c067be3ad5bfca07ff98fc287e42ee686bc35f4493e69f2988ebcb4c54cc7