Paper Citation Record · LEDGER

Evaluating the Performance of Large Language Models on GAOKAO Benchmark

As of 23 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 53 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 72 of 72 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 53 of 53 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:13:25.067403Z

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

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+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

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+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

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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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+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

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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

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

Source-reported events for the cited work

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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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Observation dc451ee2-1095-4b4b-9517-6ec65f0781e4 · inbound

Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation cites this paper.

Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 97

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Observation 66afb50f-3d1f-46ca-9669-24b7d6baeaa3 · inbound

GAOKAO-Eval: Does high scores truly reflect strong capabilities in LLMs? cites this paper.

GAOKAO-Eval: Does high scores truly reflect strong capabilities in LLMs? Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 45

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Observation 638e21c2-aa9c-4581-8b88-c5f62bd91e0b · inbound

CDS: Knowledge Component-Driven Data Synthesis Guided by Cognitive Diagnosis Theory cites this paper.

CDS: Knowledge Component-Driven Data Synthesis Guided by Cognitive Diagnosis Theory Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 55

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Observation 4854b141-2be6-49bd-86a6-f6021cf02d0e · inbound

O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning cites this paper.

O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 29

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UGPhysics: A Comprehensive Benchmark for Undergraduate Physics Reasoning with Large Language Models cites this paper.

UGPhysics: A Comprehensive Benchmark for Undergraduate Physics Reasoning with Large Language Models Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 75

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Improving Natural Language Understanding for LLMs via Large-Scale Instruction Synthesis cites this paper.

Improving Natural Language Understanding for LLMs via Large-Scale Instruction Synthesis Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 84

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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

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QualBench: Benchmarking Chinese LLMs with Localized Professional Qualifications for Vertical Domain Evaluation cites this paper.

QualBench: Benchmarking Chinese LLMs with Localized Professional Qualifications for Vertical Domain Evaluation Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 41

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SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models cites this paper.

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 34

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Can reasoning models comprehend mathematical problems in Chinese ancient texts? An empirical study based on data from Suanjing Shishu cites this paper.

Can reasoning models comprehend mathematical problems in Chinese ancient texts? An empirical study based on data from Suanjing Shishu Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 2023

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Concise Reasoning, Big Gains: Pruning Long Reasoning Trace with Difficulty-Aware Prompting cites this paper.

Concise Reasoning, Big Gains: Pruning Long Reasoning Trace with Difficulty-Aware Prompting Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 36

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Don't Think Longer, Think Wisely: Optimizing Thinking Dynamics for Large Reasoning Models cites this paper.

Don't Think Longer, Think Wisely: Optimizing Thinking Dynamics for Large Reasoning Models Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 43

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Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning cites this paper.

Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 20

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Can LLMs Reason Abstractly Over Math Word Problems Without CoT? Disentangling Abstract Formulation From Arithmetic Computation cites this paper.

Can LLMs Reason Abstractly Over Math Word Problems Without CoT? Disentangling Abstract Formulation From Arithmetic Computation Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 37

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Observation 4df059e3-555e-4593-9baf-d468eea40bea · inbound

From Objectives to Questions: A Planning-based Framework for Educational Mathematical Question Generation cites this paper.

From Objectives to Questions: A Planning-based Framework for Educational Mathematical Question Generation Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 2024

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Source-reported events for the cited work

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Observation 7c5974ad-f0e9-423e-8360-06266f88d0fe · inbound

Temporalizing Confidence: Evaluation of Chain-of-Thought Reasoning with Signal Temporal Logic cites this paper.

Temporalizing Confidence: Evaluation of Chain-of-Thought Reasoning with Signal Temporal Logic Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 26

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SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning cites this paper.

SwS: Self-aware Weakness-driven Problem Synthesis in Reinforcement Learning for LLM Reasoning Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 71

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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

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Observation 5e9d4b98-9a5e-4136-ba7c-94d16b4bbfc6 · inbound

MinosEval: Distinguishing Factoid and Non-Factoid for Tailored Open-Ended QA Evaluation with LLMs cites this paper.

MinosEval: Distinguishing Factoid and Non-Factoid for Tailored Open-Ended QA Evaluation with LLMs Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 65

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Enterprise Large Language Model Evaluation Benchmark cites this paper.

Enterprise Large Language Model Evaluation Benchmark Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 24

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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

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Observation 9435e165-90f4-4332-b5e9-359316fbaa19 · inbound

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training cites this paper.

WSM: Decay-Free Learning Rate Schedule via Checkpoint Merging for LLM Pre-training Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 69

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Technical Report of TeleChat2, TeleChat2.5 and T1 cites this paper.

Technical Report of TeleChat2, TeleChat2.5 and T1 Evaluating the Performance of Large Language Models on GAOKAO Benchmark

Reference 66

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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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Observation 310061f6-30b1-4ac3-ba9b-a8151a1c8305 · inbound

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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Observation dac95634-5e48-4fae-897d-b95e50e70bcc · inbound

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

Resolution: unresolved; no resolver link, observed 2026-08-05T18:53:05.214761Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca6715dc-d740-4dac-ab4f-437a436c501e · inbound

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-04T13:15:48.547800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea268b62-2206-4296-8766-bdf9dc750395 · inbound

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

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 2026-08-23T06:30:58.430688+00:00.

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

Resolution: verified exact; local_arxiv, observed 2026-05-25T07:05:26.681888Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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

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 2026-08-23T06:30:58.430688+00:00.

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

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 2026-08-23T06:30:58.430688+00:00.

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+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

Resolution: malformed identifier; 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 2026-08-23T06:30:58.430688+00:00.

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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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

Resolution: unresolved; no resolver link, observed 2026-08-04T05:23:31.540079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

Resolution: metadata mismatch; 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 2026-08-23T06:30:58.430688+00:00.

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

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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

Resolution: metadata mismatch; 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 2026-08-23T06:30:58.430688+00:00.

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

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

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

Resolution: unresolved; no resolver link, observed 2026-08-02T14:31:12.591994Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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 2026-08-23T06:30:58.430688+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.