mlsanityData to 7 Oct 2026

Can we trust the evaluation on ChatGPT?

arXiv 2303.12767 ↗First posted 22 Mar 2023cs.CL cs.AI cs.LGcited by 63

Not on the map. Why?

Abstract (arXiv)

ChatGPT, the first large language model (LLM) with mass adoption, has demonstrated remarkable performance in numerous natural language tasks. Despite its evident usefulness, evaluating ChatGPT's performance in diverse problem domains remains challenging due to the closed nature of the model and its continuous updates via Reinforcement Learning from Human Feedback (RLHF). We highlight the issue of data contamination in ChatGPT evaluations, with a case study of the task of stance detection. We discuss the challenge of preventing data contamination and ensuring fair model evaluation in the age of closed and continuously trained models.

Key facts. Cited by 63 papers in the map (data through 7 Oct 2026). Builds on 13 of its 34 references that are in the map. First posted on arXiv 22 Mar 2023.

Builds on

13 of 34 references.

References · 13

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2023GPT-4 Technical Reportcited by 18,132
  3. 2017Proximal Policy Optimization Algorithmscited by 14,441
  4. 2020Extracting Training Data from Large Language Modelscited by 2,144
  5. 2022Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelscited by 1,970
  6. 2022Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?cited by 1,413
  7. 2022What Can Transformers Learn In-Context? A Case Study of Simple Function Classescited by 700
  8. 2021Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpuscited by 481
  9. 2023Mathematical Capabilities of ChatGPTcited by 263
  10. 2023ChatGPT: Jack of all trades, master of nonecited by 204
  11. 2023An Analysis of the Automatic Bug Fixing Performance of ChatGPTcited by 108
  12. 2022How would Stance Detection Techniques Evolve after the Launch of ChatGPT?cited by 76
1 more
  1. 2016Stance and Sentiment in Tweetscited by 62

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 30; 2024: 23; 2025: 6; 2026: 4.

63 papers.

Sort:

By area:

  1. 2023A Survey of Large Language Modelscited by 2,537
  2. 2023How is ChatGPT's behavior changing over time?cited by 265
  3. 2024Leak, Cheat, Repeat: Data Contamination and Evaluation Malpractices in Closed-Source LLMscited by 224
  4. 2023Don't Make Your LLM an Evaluation Benchmark Cheatercited by 194
  5. 2024OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Datacited by 194
  6. 2023Investigating Data Contamination in Modern Benchmarks for Large Language Modelscited by 136
  7. 2023A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasetscited by 123
  8. 2023Shepherd: A Critic for Language Model Generationcited by 96
  9. 2023A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validationcited by 91
  10. 2023Can ChatGPT Reproduce Human-Generated Labels? A Study of Social Computing Taskscited by 88
  11. 2023A Survey of Graph Meets Large Language Model: Progress and Future Directionscited by 84
  12. 2024ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphscited by 83
38 more
  1. 2023TrueTeacher: Learning Factual Consistency Evaluation with Large Language Modelscited by 82
  2. 2023Large language models effectively leverage document-level context for literary translation, but critical errors persistcited by 80
  3. 2023AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZcited by 74
  4. 2023GPTEval: A Survey on Assessments of ChatGPT and GPT-4cited by 73
  5. 2023ICE-Score: Instructing Large Language Models to Evaluate Codecited by 50
  6. 2024GraphArena: Evaluating and Exploring Large Language Models on Graph Computationcited by 48
  7. 2024Hallucination Detection: Robustly Discerning Reliable Answers in Large Language Modelscited by 44
  8. 2023Data Contamination Through the Lens of Timecited by 39
  9. 2024GLBench: A Comprehensive Benchmark for Graph with Large Language Modelscited by 36
  10. 2023Can LLMs Effectively Leverage Graph Structural Information through Prompts, and Why?cited by 31
  11. 2024Unveiling the Spectrum of Data Contamination in Language Models: A Survey from Detection to Remediationcited by 30
  12. 2024RepLiQA: A Question-Answering Dataset for Benchmarking LLMs on Unseen Reference Contentcited by 26
  13. 2023People Make Better Edits: Measuring the Efficacy of LLM-Generated Counterfactually Augmented Data for Harmful Language Detectioncited by 25
  14. 2024A Philosophical Introduction to Language Models -- Part I: Continuity With Classic Debatescited by 22
  15. 2024xFinder: Large Language Models as Automated Evaluators for Reliable Evaluationcited by 18
  16. 2023Causal Reasoning: Charting a Revolutionary Course for Next-Generation AI-Native Wireless Networkscited by 16
  17. 2023Prompting and Fine-Tuning Open-Sourced Large Language Models for Stance Classificationcited by 16
  18. 2023Automated stance detection in complex topics and small languages: the challenging case of immigration in polarizing news mediacited by 14
  19. 2024PiCO: Peer Review in LLMs based on the Consistency Optimizationcited by 14
  20. 2023Machine-assisted quantitizing designs: augmenting humanities and social sciences with artificial intelligencecited by 13
  21. 2024PertEval: Unveiling Real Knowledge Capacity of LLMs with Knowledge-Invariant Perturbationscited by 13
  22. 2023ChatLog: Carefully Evaluating the Evolution of ChatGPT Across Timecited by 12
  23. 2025VeriContaminated: Assessing LLM-Driven Verilog Coding for Data Contaminationcited by 12
  24. 2023Language Models as a Service: Overview of a New Paradigm and its Challengescited by 10
  25. 2023AI, write an essay for me: A large-scale comparison of human-written versus ChatGPT-generated essayscited by 9
  26. 2024Large Models of What? Mistaking Engineering Achievements for Human Linguistic Agencycited by 9
  27. 2023Fine-tuning Language Models with Generative Adversarial Reward Modellingcited by 8
  28. 2025VIS-Shepherd: Constructing Critic for LLM-based Data Visualization Generationcited by 8
  29. 2024UNO Arena for Evaluating Sequential Decision-Making Capability of Large Language Modelscited by 6
  30. 2025Generative Evaluation of Complex Reasoning in Large Language Modelscited by 6
  31. 2024Stance Detection on Social Media with Fine-Tuned Large Language Modelscited by 5
  32. 2024Reinforcement Tuning for Detecting Stances and Debunking Rumors Jointly with Large Language Modelscited by 5
  33. 2025Is Your Benchmark Still Useful? Dynamic Benchmarking for Code Language Modelscited by 5
  34. 2023Enhancing Stance Classification on Social Media Using Quantified Moral Foundationscited by 4
  35. 2023ConDefects: A New Dataset to Address the Data Leakage Concern for LLM-based Fault Localization and Program Repaircited by 4
  36. 2024APT-Pipe: A Prompt-Tuning Tool for Social Data Annotation using ChatGPTcited by 4
  37. 2024Identifying the Achilles' Heel: An Iterative Method for Dynamically Uncovering Factual Errors in Large Language Modelscited by 3
  38. 2024Questionable practices in machine learningcited by 3

50 most cited of 63 All 63 (JSON)

Similar, not cited

Close in wording, no citation either way

  1. 2023Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models
  2. 2024Testing and Evaluation of Large Language Models: Correctness, Non-Toxicity, and Fairness
  3. 2023Consistency Analysis of ChatGPT
  4. 2023ChatGPT's One-year Anniversary: Are Open-Source Large Language Models Catching up?
  5. 2023Reliability Check: An Analysis of GPT-3's Response to Sensitive Topics and Prompt Wording
  6. 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity
  7. 2023Pushing the Limits of ChatGPT on NLP Tasks
  8. 2024How Good is ChatGPT at Face Biometrics? A First Look into Recognition, Soft Biometrics, and Explainability