mlsanityData to 7 Oct 2026

Challenges and Applications of Large Language Models

arXiv 2307.10169 ↗First posted 19 Jul 2023cs.CL cs.AI cs.LGcited by 251

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Cited by 29 in LLM reasoning, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Large Language Models (LLMs) went from non-existent to ubiquitous in the machine learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify the remaining challenges and already fruitful application areas. In this paper, we aim to establish a systematic set of open problems and application successes so that ML researchers can comprehend the field's current state more quickly and become productive.

Key facts. Cited by 251 papers in the map (data through 7 Oct 2026). Builds on 290 of its 686 references that are in the map. First posted on arXiv 19 Jul 2023.

Builds on

290 of 686 references.

References · 290

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38 more
  1. 2023Lost in the Middle: How Language Models Use Long Contextscited by 3,383
  2. 2023QLoRA: Efficient Finetuning of Quantized LLMscited by 3,355
  3. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,155
  4. 2022Constitutional AI: Harmlessness from AI Feedbackcited by 2,950
  5. 2021TruthfulQA: Measuring How Models Mimic Human Falsehoodscited by 2,919
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  8. 2020The Pile: An 800GB Dataset of Diverse Text for Language Modelingcited by 2,346
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  10. 2019Fine-Tuning Language Models from Human Preferencescited by 2,124
  11. 2023Voyager: An Open-Ended Embodied Agent with Large Language Modelscited by 2,081
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  16. 2019Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelismcited by 1,829
  17. 2022Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Themcited by 1,767
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  22. 2023Jailbroken: How Does LLM Safety Training Fail?cited by 1,565
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  33. 2023SparseGPT: Massive Language Models Can Be Accurately Pruned in One-Shotcited by 1,090
  34. 2023LIMA: Less Is More for Alignmentcited by 1,080
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50 most cited of 290 All 290 (JSON)

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Citing papers per year: 2023: 34; 2024: 116; 2025: 78; 2026: 23.

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  1. 2023Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotationscited by 895
  2. 2023Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Modelscited by 695
  3. 2024Large Language Models: A Surveycited by 506
  4. 2024AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agentscited by 450
  5. 2023Efficient Large Language Models: A Surveycited by 183
  6. 2024Security and Privacy Challenges of Large Language Models: A Surveycited by 179
  7. 2024Are We Done with MMLU?cited by 178
  8. 2024A Comprehensive Study of Knowledge Editing for Large Language Modelscited by 157
  9. 2023Open Sesame! Universal Black Box Jailbreaking of Large Language Modelscited by 128
  10. 2024Benchmarking LLMs via Uncertainty Quantificationcited by 124
  11. 2025REASONING GYM: Reasoning Environments for Reinforcement Learning with Verifiable Rewardscited by 121
  12. 2024AutoSurvey: Large Language Models Can Automatically Write Surveyscited by 116
38 more
  1. 2025MLGym: A New Framework and Benchmark for Advancing AI Research Agentscited by 111
  2. 2025A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deploymentcited by 110
  3. 2024ClashEval: Quantifying the tug-of-war between an LLM's internal prior and external evidencecited by 109
  4. 2024A Survey on Large Language Model-Based Game Agentscited by 106
  5. 2024Faithfulness vs. Plausibility: On the (Un)Reliability of Explanations from Large Language Modelscited by 104
  6. 2024Large Language Models Meet NLP: A Surveycited by 102
  7. 2024On-Device Language Models: A Comprehensive Reviewcited by 101
  8. 2024ARGS: Alignment as Reward-Guided Searchcited by 99
  9. 2023EasyEdit: An Easy-to-use Knowledge Editing Framework for Large Language Modelscited by 97
  10. 2023Jatmo: Prompt Injection Defense by Task-Specific Finetuningcited by 89
  11. 2024Large Language Models for Robotics: Opportunities, Challenges, and Perspectivescited by 88
  12. 2023Use of LLMs for Illicit Purposes: Threats, Prevention Measures, and Vulnerabilitiescited by 76
  13. 2024KV Cache is 1 Bit Per Channel: Efficient Large Language Model Inference with Coupled Quantizationcited by 74
  14. 2023Unleashing the potential of prompt engineering for large language modelscited by 72
  15. 2023Alignment for Honestycited by 72
  16. 2025SafeVLA: Towards Safety Alignment of Vision-Language-Action Model via Constrained Learningcited by 69
  17. 2024Rejection Improves Reliability: Training LLMs to Refuse Unknown Questions Using RL from Knowledge Feedbackcited by 64
  18. 2023Making Large Language Models Better Reasoners with Alignmentcited by 63
  19. 2023Compressing LLMs: The Truth is Rarely Pure and Never Simplecited by 59
  20. 2024Understanding LLMs: A Comprehensive Overview from Training to Inferencecited by 58
  21. 2024Determinants of LLM-assisted Decision-Makingcited by 55
  22. 2023From Sparse to Dense: GPT-4 Summarization with Chain of Density Promptingcited by 52
  23. 2024MathOdyssey: Benchmarking Mathematical Problem-Solving Skills in Large Language Models Using Odyssey Math Datacited by 51
  24. 2024Fine Tuning vs. Retrieval Augmented Generation for Less Popular Knowledgecited by 49
  25. 2024Financial Report Chunking for Effective Retrieval Augmented Generationcited by 46
  26. 2024Using AI-Based Coding Assistants in Practice: State of Affairs, Perceptions, and Ways Forwardcited by 44
  27. 2024In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigationcited by 43
  28. 2024In-Context Principle Learning from Mistakescited by 42
  29. 2024On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Modelscited by 42
  30. 2024Detecting Hallucinations in Large Language Model Generation: A Token Probability Approachcited by 40
  31. 2024UDA: A Benchmark Suite for Retrieval Augmented Generation in Real-world Document Analysiscited by 40
  32. 2024Cascade Reward Sampling for Efficient Decoding-Time Alignmentcited by 38
  33. 2023When does In-context Learning Fall Short and Why? A Study on Specification-Heavy Taskscited by 37
  34. 2024Automatic Interactive Evaluation for Large Language Models with State Aware Patient Simulatorcited by 36
  35. 2024IRCAN: Mitigating Knowledge Conflicts in LLM Generation via Identifying and Reweighting Context-Aware Neuronscited by 36
  36. 2023Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysiscited by 34
  37. 2024Best Practices for Text Annotation with Large Language Modelscited by 34
  38. 2024Large Language Models for UAVs: Current State and Pathways to the Futurecited by 33

50 most cited of 251 All 251 (JSON)