Paper Citation Record · LEDGER

Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 42 inbound Pith citation observations for arXiv:2311.04850.

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

pith.paper-citation-record.v1
2311.04850 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 42 of 42 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T18:19:46.939354Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

7
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 26dde097-e60d-47b9-ba7b-9ca5f4315064 · inbound

Benchmark Data Contamination of Large Language Models: A Survey cites this paper.

Benchmark Data Contamination of Large Language Models: A Survey Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 170

Resolution: verified exact; arxiv_id, observed 2026-05-22T23:10:41.134008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 79ffe552-61e5-4673-bf9b-bc4fde5114c9 · inbound

DataComp-LM: In search of the next generation of training sets for language models cites this paper.

DataComp-LM: In search of the next generation of training sets for language models Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 208

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T22:58:17.334977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d04fd98e-06bd-41e4-af68-e6b519a0ec47 · inbound

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

ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:08:09.653347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 721c1b03-93f3-4b00-a4dc-c92cdd4ae55f · inbound

Can We Trust AI Benchmarks? An Interdisciplinary Review of Current Issues in AI Evaluation cites this paper.

Can We Trust AI Benchmarks? An Interdisciplinary Review of Current Issues in AI Evaluation Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 136

Resolution: unresolved; no resolver link, observed 2026-08-08T15:06:55.384462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 246859ee-fbaf-4caa-ba72-24d790e7d46a · inbound

Unbiased Evaluation of Large Language Models from a Causal Perspective cites this paper.

Unbiased Evaluation of Large Language Models from a Causal Perspective Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-08T14:51:15.489455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 775566c9-a666-4c3c-a592-902782fcb963 · inbound

CapBencher: Give Your LLM Benchmark a Built-in Alarm for Test-Set Overfitting cites this paper.

CapBencher: Give Your LLM Benchmark a Built-in Alarm for Test-Set Overfitting Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T14:44:35.529969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb1ad3e0-5e03-4ab1-aeff-d7c4f5f9f56d · inbound

SwiftEval: Developing a Language-Specific Benchmark for LLM-generated Code Evaluation cites this paper.

SwiftEval: Developing a Language-Specific Benchmark for LLM-generated Code Evaluation Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T12:29:18.525978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0a0588e0-0c37-4bd2-95fb-f1c7e168d36e · inbound

BenchHub: A Unified Benchmark Suite for Holistic and Customizable LLM Evaluation cites this paper.

BenchHub: A Unified Benchmark Suite for Holistic and Customizable LLM Evaluation Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-07T12:08:17.369531Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b690f495-6cb2-4638-a9e5-a77112b77557 · inbound

OpenCodeReasoning-II: A Simple Test Time Scaling Approach via Self-Critique cites this paper.

OpenCodeReasoning-II: A Simple Test Time Scaling Approach via Self-Critique Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-06T18:11:20.143746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1bb22ce2-c68b-422d-948d-2f1f77c32e39 · inbound

League of LLMs: A Benchmark-Free Paradigm for Mutual Evaluation of Large Language Models cites this paper.

League of LLMs: A Benchmark-Free Paradigm for Mutual Evaluation of Large Language Models Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-19T03:22:01.341453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 8fca8ffb-2cd4-4adf-b168-b5219a677eb7 · inbound

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report cites this paper.

Llama-3.1-FoundationAI-SecurityLLM-8B-Instruct Technical Report Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-06T05:57:29.511258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54c99d7c-0932-4665-88df-4cafaffd7561 · inbound

LogitTrace: Detecting Benchmark Contamination via Layerwise Logit Trajectories cites this paper.

LogitTrace: Detecting Benchmark Contamination via Layerwise Logit Trajectories Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 26

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T14:36:28.943124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1cf0bda5-0b6e-4ddb-b0ff-0793c0142615 · inbound

Correcting Prompt Dependence in LLM Benchmarks: A Bayesian Hierarchical Model with Embedding-Space Clustering cites this paper.

Correcting Prompt Dependence in LLM Benchmarks: A Bayesian Hierarchical Model with Embedding-Space Clustering Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-04T11:19:51.012398Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d25e5c67-f333-4fda-b471-faf6e2b0bdff · inbound

Compiled AI: Deterministic Code Generation for LLM-Based Workflow Automation cites this paper.

Compiled AI: Deterministic Code Generation for LLM-Based Workflow Automation Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 22

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T23:40:51.520975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 548a2693-0ac5-442b-aac0-89d3bec954ea · inbound

DRBENCHER: Can Your Agent Identify the Entity, Retrieve Its Properties and Do the Math? cites this paper.

DRBENCHER: Can Your Agent Identify the Entity, Retrieve Its Properties and Do the Math? Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:11:04.832167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 47e2479c-fb1f-496d-827e-eaaf883b2921 · inbound

TPS-CalcBench: A Benchmark and Diagnostic Evaluation Framework for LLM Analytical Calculation Competence in Hypersonic Thermal Protection System Engineering cites this paper.

TPS-CalcBench: A Benchmark and Diagnostic Evaluation Framework for LLM Analytical Calculation Competence in Hypersonic Thermal Protection System Engineering Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-10T09:23:37.514127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 22b7cd4d-8090-460d-9758-5f01a02de39b · inbound

When Prompt Under-Specification Improves Code Correctness: An Exploratory Study of Prompt Wording and Structure Effects on LLM-Based Code Generation cites this paper.

When Prompt Under-Specification Improves Code Correctness: An Exploratory Study of Prompt Wording and Structure Effects on LLM-Based Code Generation Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 44

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T22:17:06.819446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6fd5b37e-9661-4f13-97f0-0af6e7d0b045 · inbound

Measuring AI Reasoning: A Guide for Researchers cites this paper.

Measuring AI Reasoning: A Guide for Researchers Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:05:36.959600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1b15f2a6-e35a-4bde-a1ba-9bf71adfead8 · inbound

Agent Island: A Saturation- and Contamination-Resistant Benchmark from Multiagent Games cites this paper.

Agent Island: A Saturation- and Contamination-Resistant Benchmark from Multiagent Games Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:46:17.276350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9d53cd78-ddd4-4c96-9571-3b76c9fa1010 · inbound

Measuring Evaluation-Context Divergence in Open-Weight LLMs: A Paired-Prompt Protocol with Pilot Evidence of Alignment-Pipeline-Specific Heterogeneity cites this paper.

Measuring Evaluation-Context Divergence in Open-Weight LLMs: A Paired-Prompt Protocol with Pilot Evidence of Alignment-Pipeline-Specific Heterogeneity Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-05-08T22:04:18.090953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1c5fe167-2a6f-4ffc-b264-cb3a266a33fe · inbound

GSM-SEM: Benchmark and Framework for Generating Semantically Variant Augmentations cites this paper.

GSM-SEM: Benchmark and Framework for Generating Semantically Variant Augmentations Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:55:59.899239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bcaeda91-673a-474a-8963-2564111db7eb · inbound

GSM-SEM: Benchmark and Framework for Generating Semantically Variant Augmentations cites this paper.

GSM-SEM: Benchmark and Framework for Generating Semantically Variant Augmentations Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-06-30T23:45:07.976186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ec4241e4-e7c0-4b4c-8c06-4660896cd370 · inbound

Can Agent Benchmarks Support Their Scores? Evidence-Supported Bounds for Interactive-Agent Evaluation cites this paper.

Can Agent Benchmarks Support Their Scores? Evidence-Supported Bounds for Interactive-Agent Evaluation Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:41:23.900869Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation abfb013e-e714-4037-85ac-acc881089016 · inbound

Decaf: Improving Neural Decompilation with Automatic Feedback and Search cites this paper.

Decaf: Improving Neural Decompilation with Automatic Feedback and Search Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 32

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T02:07:08.093098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 481aa828-3a0e-498f-9f0b-f56df90e7622 · inbound

Do Androids Dream of Breaking the Game? Systematically Auditing AI Agent Benchmarks with BenchJack cites this paper.

Do Androids Dream of Breaking the Game? Systematically Auditing AI Agent Benchmarks with BenchJack Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-14T20:32:56.862291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a0f175ac-6597-48d7-9bf4-51fc3977f5ec · inbound

LLM Benchmark Datasets Should Be Contamination-Resistant cites this paper.

LLM Benchmark Datasets Should Be Contamination-Resistant Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 90

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T07:23:07.058655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ae61037a-4a0c-4149-9764-5047fc27a22e · inbound

Provable Joint Decontamination for Benchmarking Multiple Large Language Models cites this paper.

Provable Joint Decontamination for Benchmarking Multiple Large Language Models Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 172

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T00:44:29.489044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e50e38d5-a330-4082-9fc1-b47897ecc449 · inbound

The Illusion of Reasoning: Exposing Evasive Data Contamination in LLMs via Zero-CoT Truncation cites this paper.

The Illusion of Reasoning: Exposing Evasive Data Contamination in LLMs via Zero-CoT Truncation Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T08:06:15.310194Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 81a8cf3c-06b8-49b8-bbd7-3da728bad548 · inbound

How Hard is it to Rig a Benchmark? A Social Choice Analysis of Leaderboard Robustness cites this paper.

How Hard is it to Rig a Benchmark? A Social Choice Analysis of Leaderboard Robustness Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-25T04:40:24.444660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e11c3d40-017b-429b-8690-ff2370e45d98 · inbound

TRACER: A Semantic-Aware Framework for Fine-Grained Contamination Detection in Code LLMs cites this paper.

TRACER: A Semantic-Aware Framework for Fine-Grained Contamination Detection in Code LLMs Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-06-30T15:34:47.895008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 04ea9e21-1c59-4575-a510-f812fd2b7aeb · inbound

Towards Evaluation Engineering: An Empirical Study of ML Evaluation Harnesses in the Wild cites this paper.

Towards Evaluation Engineering: An Empirical Study of ML Evaluation Harnesses in the Wild Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-06-30T14:44:45.155954Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6c2dc137-5f7d-4787-b49a-71cbffd49ef8 · inbound

Measuring Reasoning Quality in LLMs: A Multi-Dimensional Behavioral Framework cites this paper.

Measuring Reasoning Quality in LLMs: A Multi-Dimensional Behavioral Framework Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 26

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T13:34:40.588543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b5a659b1-05df-4a48-8f38-913a67b3cfe8 · inbound

Measuring Reasoning Quality in LLMs: A Multi-Dimensional Behavioral Framework cites this paper.

Measuring Reasoning Quality in LLMs: A Multi-Dimensional Behavioral Framework Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 26

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T08:05:31.914578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 73c90e48-132c-4c28-9ee1-a4949e9206f0 · inbound

Measuring Reasoning Quality in LLMs: A Multi-Dimensional Behavioral Framework cites this paper.

Measuring Reasoning Quality in LLMs: A Multi-Dimensional Behavioral Framework Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 26

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T23:27:26.731890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation dab2454a-666d-4842-b07a-aed17edf3fd0 · inbound

TSFMAudit: Data Contamination Auditing in Forecasting Time Series Foundation Models cites this paper.

TSFMAudit: Data Contamination Auditing in Forecasting Time Series Foundation Models Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-06-30T12:04:38.780577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 429ec9d5-66e8-4def-a403-8144313ea449 · inbound

Embodied-BenchClaw: An Autonomous Multi-Agent System for Embodied Spatial Intelligence Benchmark Construction cites this paper.

Embodied-BenchClaw: An Autonomous Multi-Agent System for Embodied Spatial Intelligence Benchmark Construction Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T10:48:02.880656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation dcbed4ea-62a8-48a1-b727-be0d3cb6004e · inbound

Which Models Are Our Models Built On? Auditing Invisible Dependencies in Modern LLMs cites this paper.

Which Models Are Our Models Built On? Auditing Invisible Dependencies in Modern LLMs Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 75

Resolution: verified exact; arxiv_id, observed 2026-07-03T10:37:56.593959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation df54faea-0bd2-4570-a54c-c347743948f7 · inbound

SrDetection: A Self-Referential Framework for Data Leakage Detection in Code Large Language Models cites this paper.

SrDetection: A Self-Referential Framework for Data Leakage Detection in Code Large Language Models Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T06:24:18.367339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e34d5daa-ff82-4dcf-8c9b-19274d08c5d6 · inbound

Do Agent Benchmarks Measure Capability? Protocol Validity in the Age of Agentic AI cites this paper.

Do Agent Benchmarks Measure Capability? Protocol Validity in the Age of Agentic AI Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-01T05:03:42.877641Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 372bad00-77da-4547-981f-6351c5a94418 · inbound

Temporal Leakage in LLM Backtesting: Measurement, Validation, and Adjusted Scores cites this paper.

Temporal Leakage in LLM Backtesting: Measurement, Validation, and Adjusted Scores Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T04:31:04.418737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f312928c-1d49-415a-bc1e-92f5c4a57e6c · inbound

EuroExec: Frontier Language Models Fall Short of Expert Judgment on European Executive Decision Tasks cites this paper.

EuroExec: Frontier Language Models Fall Short of Expert Judgment on European Executive Decision Tasks Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-06T22:23:05.614586Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1fd6bd95-accd-4fa4-b360-c9160579218f · inbound

EuroExec: Frontier Language Models Fall Short of Expert Judgment on European Executive Decision Tasks cites this paper.

EuroExec: Frontier Language Models Fall Short of Expert Judgment on European Executive Decision Tasks Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-08T18:19:46.939354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.