mlsanityData to 14 Oct 2026

Evaluating Large Language Models: A Comprehensive Survey

arXiv 2310.19736 ↗First posted 30 Oct 2023cs.CL cs.AIcited by 202

Not on the map. Why?

Cited by 21 in LLM agents and tool use, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Large language models (LLMs) have demonstrated remarkable capabilities across a broad spectrum of tasks. They have attracted significant attention and been deployed in numerous downstream applications. Nevertheless, akin to a double-edged sword, LLMs also present potential risks. They could suffer from private data leaks or yield inappropriate, harmful, or misleading content. Additionally, the rapid progress of LLMs raises concerns about the potential emergence of superintelligent systems without adequate safeguards. To effectively capitalize on LLM capacities as well as ensure their safe and beneficial development, it is critical to conduct a rigorous and comprehensive evaluation of LLMs. This survey endeavors to offer a panoramic perspective on the evaluation of LLMs. We categorize the evaluation of LLMs into three major groups: knowledge and capability evaluation, alignment evaluation and safety evaluation. In addition to the comprehensive review on the evaluation methodologies and benchmarks on these three aspects, we collate a compendium of evaluations pertaining to LLMs' performance in specialized domains, and discuss the construction of comprehensive evaluation platforms that cover LLM evaluations on capabilities, alignment, safety, and applicability. We hope that this comprehensive overview will stimulate further research interests in the evaluation of LLMs, with the ultimate goal of making evaluation serve as a cornerstone in guiding the responsible development of LLMs. We envision that this will channel their evolution into a direction that maximizes societal benefit while minimizing potential risks. A curated list of related papers has been publicly available at https://github.com/tjunlp-lab/Awesome-LLMs-Evaluation-Papers.

Key facts. Cited by 202 papers in the map (data through 14 Oct 2026). Builds on 138 of its 393 references that are in the map. First posted on arXiv 30 Oct 2023.

Builds on

138 of 393 references.

References · 138

  1. 2023GPT-4 Technical Reportcited by 18,396
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  3. 2021Training Verifiers to Solve Math Word Problemscited by 10,109
  4. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
  5. 2021Evaluating Large Language Models Trained on Codecited by 8,320
  6. 2018Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challengecited by 4,886
  7. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
  8. 2021Program Synthesis with Large Language Modelscited by 3,637
  9. 2022OPT: Open Pre-trained Transformer Language Modelscited by 3,512
  10. 2022Constitutional AI: Harmlessness from AI Feedbackcited by 3,050
  11. 2023G-Eval: NLG Evaluation using GPT-4 with Better Human Alignmentcited by 2,276
  12. 2023WebArena: A Realistic Web Environment for Building Autonomous Agentscited by 2,006
38 more
  1. 2022Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelscited by 1,998
  2. 2023ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIscited by 1,947
  3. 2022Language Models (Mostly) Know What They Knowcited by 1,856
  4. 2022Large Language Models Encode Clinical Knowledgecited by 1,830
  5. 2021WebGPT: Browser-assisted question-answering with human feedbackcited by 1,745
  6. 2023Jailbroken: How Does LLM Safety Training Fail?cited by 1,651
  7. 2023LongBench: A Bilingual, Multitask Benchmark for Long Context Understandingcited by 1,417
  8. 2023Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generationcited by 1,391
  9. 2023Gorilla: Large Language Model Connected with Massive APIscited by 1,332
  10. 2023FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generationcited by 1,282
  11. 2023AgentBench: Evaluating LLMs as Agentscited by 1,267
  12. 2023A Survey on Evaluation of Large Language Modelscited by 1,242
  13. 2022LaMDA: Language Models for Dialog Applicationscited by 1,220
  14. 2022Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Taskscited by 1,076
  15. 2021A General Language Assistant as a Laboratory for Alignmentcited by 1,055
  16. 2023BloombergGPT: A Large Language Model for Financecited by 939
  17. 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivitycited by 894
  18. 2023SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for Generative Large Language Modelscited by 810
  19. 2023AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedbackcited by 748
  20. 2023AGIEval: A Human-Centric Benchmark for Evaluating Foundation Modelscited by 716
  21. 2023C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Modelscited by 708
  22. 2017Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learningcited by 687
  23. 2023The Internal State of an LLM Knows When It's Lyingcited by 659
  24. 2023Capabilities of GPT-4 on Medical Challenge Problemscited by 638
  25. 2023API-Bank: A Comprehensive Benchmark for Tool-Augmented LLMscited by 591
  26. 2023Jailbreaking ChatGPT via Prompt Engineering: An Empirical Studycited by 498
  27. 2023CMMLU: Measuring massive multitask language understanding in Chinesecited by 449
  28. 2023Is ChatGPT a Good NLG Evaluator? A Preliminary Studycited by 422
  29. 2023Augmented Language Models: a Surveycited by 403
  30. 2023Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignmentcited by 401
  31. 2023ToolAlpaca: Generalized Tool Learning for Language Models with 3000 Simulated Casescited by 393
  32. 2019FinBERT: Financial Sentiment Analysis with Pre-trained Language Modelscited by 385
  33. 2023Towards Expert-Level Medical Question Answering with Large Language Modelscited by 384
  34. 2023GPTScore: Evaluate as You Desirecited by 361
  35. 2023Toxicity in ChatGPT: Analyzing Persona-assigned Language Modelscited by 360
  36. 2023Chameleon: Plug-and-Play Compositional Reasoning with Large Language Modelscited by 356
  37. 2023Large Language Models as Tool Makerscited by 303
  38. 2023Tool Learning with Foundation Modelscited by 302

50 most cited of 138 All 138 (JSON)

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 7; 2024: 103; 2025: 71; 2026: 21.

202 papers.

Sort:

By area:

  1. 2024A Survey on the Memory Mechanism of Large Language Model based Agentscited by 634
  2. 2024LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methodscited by 465
  3. 2024Benchmarking LLMs via Uncertainty Quantificationcited by 126
  4. 2023T-Eval: Evaluating the Tool Utilization Capability of Large Language Models Step by Stepcited by 93
  5. 2024Safeguarding Large Language Models: A Surveycited by 78
  6. 2024Large Language Model Safety: A Holistic Surveycited by 59
  7. 2024Fairness in Large Language Models: A Taxonomic Surveycited by 58
  8. 2025xVerify: Efficient Answer Verifier for Reasoning Model Evaluationscited by 55
  9. 2025Which of These Best Describes Multiple Choice Evaluation with LLMs? A) Forced B) Flawed C) Fixable D) All of the Abovecited by 52
  10. 2025ToolHop: A Query-Driven Benchmark for Evaluating Large Language Models in Multi-Hop Tool Usecited by 50
  11. 2024A Comprehensive Evaluation of Quantization Strategies for Large Language Modelscited by 48
  12. 2024IRCAN: Mitigating Knowledge Conflicts in LLM Generation via Identifying and Reweighting Context-Aware Neuronscited by 38
38 more
  1. 2024A Survey on Generative AI and LLM for Video Generation, Understanding, and Streamingcited by 37
  2. 2024KIEval: A Knowledge-grounded Interactive Evaluation Framework for Large Language Modelscited by 36
  3. 2024Evaluating Language Models as Synthetic Data Generatorscited by 33
  4. 2024Examining the robustness of LLM evaluation to the distributional assumptions of benchmarkscited by 31
  5. 2024Self-Pluralising Culture Alignment for Large Language Modelscited by 31
  6. 2025ReSo: A Reward-driven Self-organizing LLM-based Multi-Agent System for Reasoning Taskscited by 31
  7. 2025The Bitter Lesson Learned from 2,000+ Multilingual Benchmarkscited by 31
  8. 2024A Survey of Useful LLM Evaluationcited by 29
  9. 2024Undesirable Memorization in Large Language Models: A Surveycited by 29
  10. 2025SurveyX: Academic Survey Automation via Large Language Modelscited by 29
  11. 2024Arena Learning: Build Data Flywheel for LLMs Post-training via Simulated Chatbot Arenacited by 26
  12. 2025The Scales of Justitia: A Comprehensive Survey on Safety Evaluation of LLMscited by 26
  13. 2024LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMscited by 25
  14. 2024Causality for Large Language Modelscited by 25
  15. 2024Exploring Multilingual Concepts of Human Value in Large Language Models: Is Value Alignment Consistent, Transferable and Controllable across Languages?cited by 24
  16. 2024When LLMs Meet Cunning Texts: A Fallacy Understanding Benchmark for Large Language Modelscited by 22
  17. 2024Khayyam Challenge (PersianMMLU): Is Your LLM Truly Wise to The Persian Language?cited by 22
  18. 2024Evaluating Large Language Models with Grid-Based Game Competitions: An Extensible LLM Benchmark and Leaderboardcited by 22
  19. 2024Towards Trustworthy AI: A Review of Ethical and Robust Large Language Modelscited by 22
  20. 2023RoleEval: A Bilingual Role Evaluation Benchmark for Large Language Modelscited by 21
  21. 2025Revisiting Entropy in Reinforcement Learning for Large Reasoning Modelscited by 21
  22. 2024Open Models, Closed Minds? On Agents Capabilities in Mimicking Human Personalities through Open Large Language Modelscited by 20
  23. 2024Sowing the Wind, Reaping the Whirlwind: The Impact of Editing Language Modelscited by 20
  24. 2024Spanish and LLM Benchmarks: is MMLU Lost in Translation?cited by 20
  25. 2024Grounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned (Survey)cited by 20
  26. 2024From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalitiescited by 19
  27. 2024xFinder: Large Language Models as Automated Evaluators for Reliable Evaluationcited by 19
  28. 2024Sample-Efficient Human Evaluation of Large Language Models via Maximum Discrepancy Competitioncited by 18
  29. 2024The Challenges of Evaluating LLM Applications: An Analysis of Automated, Human, and LLM-Based Approachescited by 18
  30. 2023BatchEval: Towards Human-like Text Evaluationcited by 17
  31. 2024A Comprehensive Survey on Evaluating Large Language Model Applications in the Medical Industrycited by 17
  32. 2024TREC iKAT 2023: A Test Collection for Evaluating Conversational and Interactive Knowledge Assistantscited by 17
  33. 2025Encouraging Good Processes Without the Need for Good Answers: Reinforcement Learning for LLM Agent Planningcited by 17
  34. 2024Assessing and Verifying Task Utility in LLM-Powered Applicationscited by 16
  35. 2025Leveraging LLMs as Meta-Judges: A Multi-Agent Framework for Evaluating LLM Judgmentscited by 16
  36. 2024The RL/LLM Taxonomy Tree: Reviewing Synergies Between Reinforcement Learning and Large Language Modelscited by 15
  37. 2024MBIAS: Mitigating Bias in Large Language Models While Retaining Contextcited by 15
  38. 2025MedArabiQ: Benchmarking Large Language Models on Arabic Medical Taskscited by 15

50 most cited of 202 All 202 (JSON)