Paper Citation Record · LEDGER

Evaluating the Performance of Large Language Models on GAOKAO Benchmark

As of 6 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 33 inbound Pith citation observations for arXiv:2305.12474.

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

pith.paper-citation-record.v1
2305.12474 v3

Coverage vector

measured 19 of 19 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-17T12:28:32.395213Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 33 of 33 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T23:21:25.985017Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

19 of 19 outbound references displayed

verified exact1
verified fuzzy12
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch1

External citation measurements

19
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 5da42aed-6caf-46c4-a61f-bfa49b6d6a31 · outbound

This paper cites Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:28:32.495884Z

Source-reported events for the cited work

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Observation 1a8e6288-784b-4c65-83d3-4f31f40cdeb7 · outbound

This paper cites GPT-4 Technical Report.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark GPT-4 Technical Report

Reference 2

Resolution: metadata mismatch; local_arxiv, observed 2026-05-17T12:28:32.420686Z

Source-reported events for the cited work

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Observation c48315cd-a1d6-454d-9eb1-1eb430b1ae93 · outbound

This paper cites Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-17T12:28:32.430613Z

Source-reported events for the cited work

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Observation 2e12e333-9264-4843-8436-8c52a50f0f68 · outbound

This paper cites an unresolved cited work.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark Unresolved cited work

Reference 4

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Source-reported events for the cited work

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Observation 8ee23b33-4950-482b-9801-a2a255f74204 · outbound

This paper cites an unresolved cited work.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark Unresolved cited work

Reference 5

Resolution: unresolved; raw_fallback, observed 2026-05-17T12:28:32.437185Z

Source-reported events for the cited work

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Observation 7f894159-50dc-4532-88d9-738449ee9e38 · outbound

This paper cites an unresolved cited work.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark Unresolved cited work

Reference 6

Resolution: unresolved; raw_fallback, observed 2026-05-17T12:28:32.441022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2dc7f7f6-d212-4254-919e-b62a1eb59f3d · outbound

This paper cites In order to protect this heritage while also developing tourism activities, measures need to be taken to protect the tourism resources.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark In order to protect this heritage while also developing tourism activities, measures need to be taken to protect the tourism resources

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:28:32.446123Z

Source-reported events for the cited work

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Observation fdace3f6-08ac-41dd-ad0a-e5043aa0912e · outbound

This paper cites an unresolved cited work.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-05-17T12:28:32.449944Z

Source-reported events for the cited work

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Observation 4e33bdc9-1f4b-4351-98dc-0e868daf10c2 · outbound

This paper cites This will enhance the cultural literacy and environmental awareness of the tourists and reduce the damage to the terraces.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark This will enhance the cultural literacy and environmental awareness of the tourists and reduce the damage to the terraces

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:28:32.453796Z

Source-reported events for the cited work

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Observation 39dada78-c3c9-4183-869c-eca92b621828 · outbound

This paper cites an unresolved cited work.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-05-17T12:28:32.457230Z

Source-reported events for the cited work

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Observation 7cd947d7-4ba4-49b6-88d3-2d4f26dc2c62 · outbound

This paper cites At the same time, these facilities should be planned judiciously to avoid damage to the terraces.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark At the same time, these facilities should be planned judiciously to avoid damage to the terraces

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:28:32.462517Z

Source-reported events for the cited work

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Observation a3ac400a-ca29-4c75-9286-86e27fc02386 · outbound

This paper cites 完善景区规划、依法保护生态环境.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark 完善景区规划、依法保护生态环境

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:28:32.466212Z

Source-reported events for the cited work

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Observation d84ba65c-aabf-45ed-ae82-c06c3f386dff · outbound

This paper cites 普及旅游文化环境保护教育，提高游客对旅游资源环境保护的意识.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark 普及旅游文化环境保护教育，提高游客对旅游资源环境保护的意识

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:28:32.469890Z

Source-reported events for the cited work

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Observation 299c4ed3-e7e0-43e1-a9a8-f4b8798faa69 · outbound

This paper cites 评定该‘生态博物馆’的环境容量，对人口数量的容纳程度，限制客流量.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark 评定该‘生态博物馆’的环境容量，对人口数量的容纳程度，限制客流量

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:28:32.473506Z

Source-reported events for the cited work

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Observation b92bfb5d-8eac-4c8e-86f8-4e7640a18f7c · outbound

This paper cites 尽可能保证新建设施与景区景观相融合.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark 尽可能保证新建设施与景区景观相融合

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:28:32.478599Z

Source-reported events for the cited work

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Observation 113cf6b0-eb19-4257-a3b1-60c8a18062e8 · outbound

This paper cites improve the planning of the scenic area, protect the ecological environment in accordance with the law.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark improve the planning of the scenic area, protect the ecological environment in accordance with the law

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:28:32.482604Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2c8949de-7100-4f53-a883-3c03366751a6 · outbound

This paper cites popularize education on the protection of the tourism cultural environment, raise tourists’ awareness of the protection of tourism resources and environment.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark popularize education on the protection of the tourism cultural environment, raise tourists’ awareness of the protection of tourism resources and environment

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:28:32.487677Z

Source-reported events for the cited work

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Observation 920ba379-6e08-437c-acc4-4c22993a1574 · outbound

This paper cites assess the environmental capacity of this ‘Ecological Museum’, regulate the carrying capacity in terms of population, limit the flow of visitors.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark assess the environmental capacity of this ‘Ecological Museum’, regulate the carrying capacity in terms of population, limit the flow of visitors

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:28:32.491874Z

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Observation ea8ba8d1-5dab-498d-99f4-bc6d9ff60ae4 · outbound

This paper cites ensure new facilities blend harmoniously with the scenic landscape.

Evaluating the Performance of Large Language Models on GAOKAO Benchmark ensure new facilities blend harmoniously with the scenic landscape

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-17T12:28:32.503672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Pith citing papers

Observation 42c25863-cfe0-47a6-94c5-2b7f29e04c1c · inbound

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

DeepSeek LLM: Scaling Open-Source Language Models with Longtermism Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 129

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Observation 1cd82ad0-a844-4020-973b-484bf5de6693 · inbound

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

Yi: Open Foundation Models by 01.AI Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 92

Resolution: verified exact; arxiv_id, observed 2026-05-17T12:28:32.509177Z

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Observation 0ec704b1-b80c-474d-926c-be559c777325 · inbound

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

DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 121

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Observation ae6bd359-f7f9-4914-8730-115862034a40 · inbound

Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization cites this paper.

Enhancing the Reasoning Ability of Multimodal Large Language Models via Mixed Preference Optimization Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 116

Resolution: verified exact; arxiv_id, observed 2026-05-17T12:28:32.509177Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8613c96b-2375-4646-93c4-24db5a62c5c3 · inbound

InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models cites this paper.

InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 150

Resolution: verified exact; arxiv_id, observed 2026-05-17T12:28:32.509177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 3f5a99a0-ade0-42fc-a449-04d9131a51f9 · inbound

Mixture-of-Experts Can Surpass Dense LLMs Under Strictly Equal Resource cites this paper.

Mixture-of-Experts Can Surpass Dense LLMs Under Strictly Equal Resource Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 45

Resolution: verified exact; local_arxiv, observed 2026-05-22T00:05:47.729661Z

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Observation 03dd5117-4e25-478c-8bb9-bfd808dda126 · inbound

Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning cites this paper.

Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 207

Resolution: verified exact; local_arxiv, observed 2026-05-19T01:01:10.027080Z

Source-reported events for the cited work

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Observation e9f3f8a1-0dd0-48bb-80cc-36c9b19869cf · inbound

TASE: Token Awareness and Structured Evaluation for Multilingual Language Models cites this paper.

TASE: Token Awareness and Structured Evaluation for Multilingual Language Models Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 51

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Towards Reliable Generative AI-Driven Scaffolding: Reducing Hallucinations and Enhancing Quality in Self-Regulated Learning Support cites this paper.

Towards Reliable Generative AI-Driven Scaffolding: Reducing Hallucinations and Enhancing Quality in Self-Regulated Learning Support Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 99

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MME-SCI: A Comprehensive and Challenging Science Benchmark for Multimodal Large Language Models cites this paper.

MME-SCI: A Comprehensive and Challenging Science Benchmark for Multimodal Large Language Models Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 4

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InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency cites this paper.

InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 178

Resolution: verified exact; arxiv_id, observed 2026-05-17T12:28:32.509177Z

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Observation 6ac50c29-e589-40b4-bb08-54936b5c90b9 · inbound

Simultaneous Multi-objective Alignment Across Verifiable and Non-verifiable Rewards cites this paper.

Simultaneous Multi-objective Alignment Across Verifiable and Non-verifiable Rewards Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 74

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LLaDA2.0: Scaling Up Diffusion Language Models to 100B cites this paper.

LLaDA2.0: Scaling Up Diffusion Language Models to 100B Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 41

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Observation b598bf54-1b21-4e92-a36c-aca177dcc8e8 · inbound

GradingAttack: Exposing Security Vulnerabilities in LLM Based Educational Grading Agents cites this paper.

GradingAttack: Exposing Security Vulnerabilities in LLM Based Educational Grading Agents Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 28

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Source-reported events for the cited work

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Observation 55e59d7a-4086-49e2-9e72-39ecb8321610 · inbound

Cognitive Mismatch in Multimodal Large Language Models for Discrete Symbol Understanding cites this paper.

Cognitive Mismatch in Multimodal Large Language Models for Discrete Symbol Understanding Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 121

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Observation 35fe28d5-b4bb-45b2-a6f0-ccbf62ff98e3 · inbound

TaxPraBen: A Scalable Benchmark for Structured Evaluation of LLMs in Chinese Real-World Tax Practice cites this paper.

TaxPraBen: A Scalable Benchmark for Structured Evaluation of LLMs in Chinese Real-World Tax Practice Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 61

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Source-reported events for the cited work

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Observation 92b3a011-13f8-41b1-980d-0c82dc16e045 · inbound

SFT-GRPO Data Overlap as a Post-Training Hyperparameter for Autoformalization cites this paper.

SFT-GRPO Data Overlap as a Post-Training Hyperparameter for Autoformalization Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-17T12:28:32.509177Z

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No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation eabcf859-5c2b-4db3-8fa3-4864e67a1e31 · inbound

RoMathExam: A Longitudinal Dataset of Romanian Math Exams (1895-2025) with a Seven-Decade Core (1957-2025) cites this paper.

RoMathExam: A Longitudinal Dataset of Romanian Math Exams (1895-2025) with a Seven-Decade Core (1957-2025) Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 33

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Observation 5cdbe6e8-0a71-4fde-86f8-073a2554e6d1 · inbound

HiPO: Hierarchical Preference Optimization for Adaptive Reasoning in LLMs cites this paper.

HiPO: Hierarchical Preference Optimization for Adaptive Reasoning in LLMs Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-17T12:28:32.509177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 534afaf3-715d-452a-b419-7f00bad02d07 · inbound

When to Vote, When to Rewrite: Disagreement-Guided Strategy Routing for Test-Time Scaling cites this paper.

When to Vote, When to Rewrite: Disagreement-Guided Strategy Routing for Test-Time Scaling Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-17T12:28:32.509177Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 456f76f0-19c1-4c20-8436-2b23c688c80b · inbound

When to Vote, When to Rewrite: Disagreement-Guided Strategy Routing for Test-Time Scaling cites this paper.

When to Vote, When to Rewrite: Disagreement-Guided Strategy Routing for Test-Time Scaling Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 42

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Source-reported events for the cited work

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Observation 70da74c3-a614-47bb-909c-1164359e15da · inbound

Validity-Calibrated Reasoning Distillation cites this paper.

Validity-Calibrated Reasoning Distillation Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 56

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Source-reported events for the cited work

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Observation 4a4a2f6e-99c8-48e3-a917-0bfa2a78aede · inbound

Validity-Calibrated Reasoning Distillation cites this paper.

Validity-Calibrated Reasoning Distillation Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-17T12:28:32.509177Z

Source-reported events for the cited work

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Observation d8ca5f37-c0f4-41ab-8928-51e0d3ccc0aa · inbound

OPT-BENCH: Evaluating the Iterative Self-Optimization of LLM Agents in Large-Scale Search Spaces cites this paper.

OPT-BENCH: Evaluating the Iterative Self-Optimization of LLM Agents in Large-Scale Search Spaces Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 63

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Source-reported events for the cited work

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Observation 0c80e584-942d-45ed-92bb-461def9eac17 · inbound

K12-KGraph: A Curriculum-Aligned Knowledge Graph for Benchmarking and Training Educational LLMs cites this paper.

K12-KGraph: A Curriculum-Aligned Knowledge Graph for Benchmarking and Training Educational LLMs Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-17T12:28:32.509177Z

Source-reported events for the cited work

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Observation 5cf0c92e-db2f-428c-8fda-99a551535990 · inbound

K12-KGraph: A Curriculum-Aligned Knowledge Graph for Benchmarking and Training Educational LLMs cites this paper.

K12-KGraph: A Curriculum-Aligned Knowledge Graph for Benchmarking and Training Educational LLMs Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 29

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Observation d3f92752-2110-4304-a475-22c015ef5c2e · inbound

LiveK12Bench: Have Large Multimodal Models Truly Conquered High School-level Examinations? cites this paper.

LiveK12Bench: Have Large Multimodal Models Truly Conquered High School-level Examinations? Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-06-29T17:33:45.008370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1b7ea2fe-d53d-4601-a505-9f236ce6229f · inbound

Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale cites this paper.

Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 125

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:17:24.928692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e29a27f3-24a8-4962-837b-10c619cf0093 · inbound

Enhancing Fitness Intelligence through Domain-Specific LLM Post-Training cites this paper.

Enhancing Fitness Intelligence through Domain-Specific LLM Post-Training Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 51

Resolution: verified exact; local_arxiv, observed 2026-07-03T13:18:12.265550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9a1ecbb9-838e-406b-acd3-c244cf0f52fc · inbound

Off-Context GRPO: Learning to Reason on Hard Problems using Privileged Information cites this paper.

Off-Context GRPO: Learning to Reason on Hard Problems using Privileged Information Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-01T12:54:36.403464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 753a4f1e-a2c1-4cdb-ae93-c89f93ad31be · inbound

Learning as Reasoning Unfolds: Progressive Rollout Allocation for Efficient Reinforcement Learning cites this paper.

Learning as Reasoning Unfolds: Progressive Rollout Allocation for Efficient Reinforcement Learning Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-01T06:14:29.370407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5e85653-5570-4a7e-956f-0437e5891064 · inbound

EduZone: A Framework for Evaluating LLM Safety for K-12 Students and Teachers cites this paper.

EduZone: A Framework for Evaluating LLM Safety for K-12 Students and Teachers Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-04T16:29:18.638135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation feebda8d-256e-41e7-8181-d1053c14fbc5 · inbound

ParVL: Parallel Scaling and Expandable Compute Allocation for Multimodal LLMs cites this paper.

ParVL: Parallel Scaling and Expandable Compute Allocation for Multimodal LLMs Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-05T04:16:08.481230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.