Large language models (LLMs) have rapidly transformed the landscape of artificial intelligence, driving breakthroughs in natural language processing, reasoning, and a wide range of downstream applications. The unprecedented pace of research in this area has led to an explosion of literature, with new papers and comprehensive surveys published almost every week.
This repository provides a curated and up-to-date collection of survey papers covering all major aspects of LLMs. The aim is to help researchers, practitioners, and newcomers quickly navigate the vast and fast-evolving body of work in this field. The surveys are organized by topic-including model architectures, alignment, prompt learning, evaluation, societal impact, efficiency, multimodal models, applications, and more-making it easy to find in-depth overviews on any subdomain of interest.
Whether you are seeking foundational knowledge, tracking the latest trends, or exploring specialized applications of LLMs, this resource is intended to serve as a comprehensive starting point for your research and development efforts.
Contributions and suggestions for additional surveys are welcome!
| Sr. No | Category | Title | Paper Link |
|---|---|---|---|
| 1 | General Surveys | Large Language Models: A Survey | Paper |
| 2 | General Surveys | A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT | Paper |
| 3 | General Surveys | A Survey of Large Language Models | Paper |
| 4 | General Surveys | Foundations of Large Language Models | Paper |
| 5 | General Surveys | Challenges and Applications of Large Language Models | Paper |
| 6 | General Surveys | Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond | Paper |
| 7 | General Surveys | A Survey on Large Language Models: Applications, Challenges, Limitations, and Practical Usage | Paper |
| 8 | General Surveys | A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT | Paper |
| 9 | General Surveys | A Comprehensive Overview of Large Language Models | Paper |
| 10 | General Surveys | Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing | Paper |
| 11 | Transformers | A survey of transformers | Paper |
| 12 | Transformers | Introduction to Transformers: an NLP Perspective | Paper |
| 13 | Transformers | Efficient Transformers: A Survey | Paper |
| 14 | Transformers | A Practical Survey on Faster and Lighter Transformers | Paper |
| 15 | Transformers | Attention Mechanism, Transformers, BERT, and GPT: Tutorial and Survey | Paper |
| 16 | Alignment | Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation | Paper |
| 17 | Alignment | AI Alignment: A Comprehensive Survey | Paper |
| 18 | Alignment | Large Language Model Alignment: A Survey | Paper |
| 19 | Alignment | From Instructions to Intrinsic Human Values -- A Survey of Alignment Goals for Big Models | Paper |
| 20 | Alignment | Aligning Large Language Models with Human: A Survey | Paper |
| 21 | Alignment | Instruction Tuning for Large Language Models: A Survey | Paper |
| 22 | Alignment | A Comprehensive Survey on Instruction Following | Paper |
| 23 | Prompt Learning | A Practical Survey on Zero-shot Prompt Design for In-context Learning | Paper |
| 24 | Prompt Learning | A Survey on In-context Learning | Paper |
| 25 | Chain of Thought | A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future | Paper |
| 26 | Chain of Thought | Towards Better Chain-of-Thought Prompting Strategies: A Survey | Paper |
| 27 | Chain of Thought | Igniting Language Intelligence: The Hitchhiker's Guide From Chain-of-Thought Reasoning to Language Agents | Paper |
| 28 | Prompt Engineering | Prompting Frameworks for Large Language Models: A Survey | Paper |
| 29 | Prompt Engineering | Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review | Paper |
| 30 | Reasoning | Towards Reasoning in Large Language Models: A Survey | Paper |
| 31 | Reasoning | A Survey of Reasoning with Foundation Models | Paper |
| 32 | Data | Data Management For Large Language Models: A Survey | Paper |
| 33 | Data | A Survey on Data Selection for Language Models | Paper |
| 34 | Data | Datasets for Large Language Models: A Comprehensive Survey | Paper |
| 35 | Data | Large Language Models for Data Annotation: A Survey | Paper |
| 36 | Data | A Survey on Data Selection for LLM Instruction Tuning | Paper |
| 37 | Data | A Survey on Knowledge Distillation of Large Language Models | Paper |
| 38 | Evaluation | Evaluating Large Language Models: A Comprehensive Survey | Paper |
| 39 | Evaluation | A Survey on Evaluation of Large Language Models | Paper |
| 40 | Evaluation | Baby steps in evaluating the capacities of large language models | Paper |
| 41 | Societal Issues | A Survey on Fairness in Large Language Models | Paper |
| 42 | Societal Issues | Large Language Models as Subpopulation Representative Models: A Review | Paper |
| 43 | Societal Issues | Perception, performance, and detectability of conversational artificial intelligence across 32 university courses | Paper |
| 44 | Societal Issues | Should chatgpt be biased? challenges and risks of bias in large language models | Paper |
| 45 | Societal Issues | Bias and Fairness in Large Language Models: A Survey | Paper |
| 46 | Source Detection | A Survey on Detection of LLMs-Generated Content | Paper |
| 47 | Source Detection | A Survey on LLM-generated Text Detection: Necessity, Methods, and Future Directions | Paper |
| 48 | Source Detection | Detecting ChatGPT: A Survey of the State of Detecting ChatGPT-Generated Text | Paper |
| 49 | Source Detection | The Science of Detecting LLM-Generated Texts | Paper |
| 50 | Security | Security and Privacy Challenges of Large Language Models: A Survey | Paper |
| 51 | Security | Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks | Paper |
| 52 | Security | A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly | Paper |
| 53 | Security | Tricking LLMs into Disobedience: Formalizing, Analyzing, and Detecting Jailbreaks | Paper |
| 54 | Security | A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation | Paper |
| 55 | Misinformation - Hallucination | Can Knowledge Graphs Reduce Hallucinations in LLMs? : A Survey, arXiv 2023.11 | Paper |
| 56 | Misinformation - Hallucination | A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions, arXiv 2023.11 | Paper |
| 57 | Misinformation - Hallucination | A Survey of Hallucination in “Large” Foundation Models, arXiv 2023.09 | Paper |
| 58 | Misinformation - Hallucination | Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models, arXiv 2023.09 | Paper |
| 59 | Misinformation - Hallucination | Cognitive Mirage: A Review of Hallucinations in Large Language Models, arXiv 2023.09 | Paper |
| 60 | Misinformation - Hallucination | Augmenting LLMs with Knowledge: A survey on hallucination prevention, arXiv 2023.09 | Paper |
| 61 | Misinformation - Hallucination | A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models, arXiv 2024.01 | Paper |
| 62 | Misinformation - Factuality | Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment, arXiv 2023.08 | Paper |
| 63 | Misinformation - Factuality | Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity, arXiv 2023.10 | Paper |
| 64 | Misinformation - Factuality | Give Me the Facts! A Survey on Factual Knowledge Probing in Pre-trained Language Models, arXiv 2023.10 | Paper |
| 65 | Attributes of LLMs | Explainability for Large Language Models: A Survey, arXiv 2023.09 | Paper |
| 66 | Attributes of LLMs | The Mystery and Fascination of LLMs: A Comprehensive Survey on the Interpretation and Analysis of Emergent Abilities, arXiv 2023.11 | Paper |
| 67 | Attributes of LLMs | From Understanding to Utilization: A Survey on Explainability for Large Language Models, arXiv 2024.01 | Paper |
| 68 | Attributes of LLMs | A Survey of Large Language Models Attribution, arXiv 2023.11 | Paper |
| 69 | Attributes of LLMs | A Survey of Language Model Confidence Estimation and Calibration, arXiv 2023.11 | Paper |
| 70 | Attributes of LLMs | Shortcut Learning of Large Language Models in Natural Language Understanding, COMMUN ACM 2023.12 | Paper |
| 71 | Attributes of LLMs | Automatically Correcting Large Language Models: Surveying the landscape of diverse self-correction strategies, arXiv 2023.08 | Paper |
| 72 | Efficient LLMs | Efficient Large Language Models: A Survey, arXiv 2023.12 | Paper |
| 73 | Efficient LLMs | LLM Inference Unveiled: Survey and Roofline Model Insights, arXiv 2024.03 | Paper |
| 74 | Efficient LLMs | Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems, arXiv 2023.12 | Paper |
| 75 | Efficient LLMs | A Survey on Model Compression for Large Language Models, arXiv 2023.08 | Paper |
| 76 | Efficient LLMs | A Comprehensive Survey of Compression Algorithms for Language Models, arXiv 2024.01 | Paper |
| 77 | Efficient LLMs | The Efficiency Spectrum of Large Language Models: An Algorithmic Survey, arXiv 2023.10 | Paper |
| 78 | Efficient LLMs | Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment, arXiv 2023.12 | Paper |
| 79 | Efficient LLMs | Model Compression and Efficient Inference for Large Language Models: A Survey, arXiv 2024.02 | Paper |
| 80 | Efficient LLMs | Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding, arXiv 2024.01 | Paper |
| 81 | Efficient LLMs | A Survey on Hardware Accelerators for Large Language Models, arXiv 2024.01 | Paper |
| 82 | Learning Methods for LLMs | Knowledge Unlearning for LLMs: Tasks, Methods, and Challenges, arXiv 2023.11 | Paper |
| 83 | Learning Methods for LLMs | Continual Learning with Pre-Trained Models: A Survey, arXiv 2024.01 | Paper |
| 84 | Learning Methods for LLMs | Continual Learning for Large Language Models: A Survey, arXiv 2024.02 | Paper |
| 85 | Learning Methods for LLMs | Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning, arXiv 2023.03 | Paper |
| 86 | Multimodal LLMs | Vision-Language Instruction Tuning: A Review and Analysis, arXiv 2023.11 | Paper |
| 87 | Multimodal LLMs | Large Language Models Meet Computer Vision: A Brief Survey, arXiv 2023.11 | Paper |
| 88 | Multimodal LLMs | Foundational Models Defining a New Era in Vision: A Survey and Outlook, arXiv 2023.07 | Paper |
| 89 | Multimodal LLMs | Video Understanding with Large Language Models: A Survey, arXiv 2023.12 | Paper |
| 90 | Multimodal LLMs | Large Models for Time Series and Spatio-Temporal Data: A Survey and Outlook, arXiv 2023.10 | Paper |
| 91 | Multimodal LLMs | Sparks of large audio models: A survey and outlook, arXiv 2023.08 | Paper |
| 92 | Multimodal LLMs | How to Bridge the Gap between Modalities: A Comprehensive Survey on Multimodal Large Language Model, arXiv 2023.11 | Paper |
| 93 | Multimodal LLMs | A Survey on Multimodal Large Language Models, arXiv 2023.06 | Paper |
| 94 | Multimodal LLMs | Multimodal Large Language Models: A Survey, arXiv 2023.11 | Paper |
| 95 | Knowledge Based LLMs - Retrieval-Augmented | Building trust in conversational ai: A comprehensive review and solution architecture for explainable, privacy-aware systems using llms and knowledge graph | Paper |
| 96 | Knowledge Based LLMs - Retrieval-Augmented | A Survey on Retrieval-Augmented Text Generation | Paper |
| 97 | Knowledge Based LLMs - Retrieval-Augmented | Retrieval-Augmented Generation for Large Language Models: A Survey | Paper |
| 98 | Knowledge Based LLMs - Knowledge Editing | Trends in Integration of Knowledge and Large Language Models: A Survey and Taxonomy of Methods, Benchmarks, and Applications | Paper |
| 99 | Knowledge Based LLMs - Knowledge Editing | Knowledge Editing for Large Language Models: A Survey | Paper |
| 100 | Knowledge Based LLMs - Knowledge Editing | Editing Large Language Models: Problems, Methods, and Opportunities | Paper |
| 101 | Extension of LLMs - LLMs with Tools | A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond | Paper |
| 102 | Extension of LLMs - LLMs with Tools | Foundation Models for Decision Making: Problems, Methods, and Opportunities | Paper |
| 103 | Extension of LLMs - LLMs with Tools | Augmented Language Models: a Survey | Paper |
| 104 | Extension of LLMs - LLMs with Tools | Pitfalls in Language Models for Code Intelligence: A Taxonomy and Survey | Paper |
| 105 | Extension of LLMs - LLMs with Tools | Large Language Models Meet NL2Code: A Survey | Paper |
| 106 | Extension of LLMs - LLMs and Interactions | Large Language Models for Robotics: A Survey | Paper |
| 107 | Extension of LLMs - LLMs and Interactions | A Survey on Multimodal Large Language Models for Autonomous Driving | Paper |
| 108 | Extension of LLMs - LLMs and Interactions | LLM4Drive: A Survey of Large Language Models for Autonomous Driving | Paper |
| 109 | Extension of LLMs - LLMs and Interactions | A Survey on Large Language Model based Autonomous Agents | Paper |
| 110 | Extension of LLMs - LLMs and Interactions | The Rise and Potential of Large Language Model Based Agents: A Survey | Paper |
| 111 | Extension of LLMs - LLMs and Interactions | Large Language Models Empowered Agent-based Modeling and Simulation: A Survey and Perspectives | Paper |
| 112 | Extension of LLMs - LLMs and Interactions | Large Multimodal Agents: A Survey | Paper |
| 113 | Extension of LLMs - LLMs and Interactions | Role play with large language models | Paper |
| 114 | Long Sequence LLMs | Advancing Transformer Architecture in Long-Context Large Language Models: A Comprehensive Survey | Paper |
| 115 | Long Sequence LLMs | Length Extrapolation of Transformers: A Survey from the Perspective of Position Encoding | Paper |
| 116 | LLMs Applications - Education | ChatGPT and Beyond: The Generative AI Revolution in Education | Paper |
| 117 | LLMs Applications - Education | ChatGPT and large language models in academia: opportunities and challenges | Paper |
| 118 | LLMs Applications - Education | ChatGPT for good? On opportunities and challenges of large language models for education | Paper |
| 119 | LLMs Applications - Law | Large Language Models in Law: A Survey | Paper |
| 120 | LLMs Applications - Law | A short survey of viewing large language models in legal aspect | Paper |
| 121 | LLMs Applications - Healthcare | A Survey of Large Language Models in Medicine: Progress, Application, and Challenge | Paper |
| 122 | LLMs Applications - Healthcare | Large Language Models Illuminate a Progressive Pathway to Artificial Healthcare Assistant: A Review | Paper |
| 123 | LLMs Applications - Healthcare | Large AI Models in Health Informatics: Applications, Challenges, and the Future | Paper |
| 124 | LLMs Applications - Healthcare | A SWOT (Strengths, Weaknesses, Opportunities, and Threats) Analysis of ChatGPT in the Medical Literature: Concise Review | Paper |
| 125 | LLMs Applications - Healthcare | ChatGPT in Healthcare: A Taxonomy and Systematic Review | Paper |
| 126 | LLMs Applications - Healthcare | A review of the explainability and safety of conversational agents for mental health to identify avenues for improvement | Paper |
| 127 | LLMs Applications - Healthcare | Towards a Psychological Generalist AI: A Survey of Current Applications of Large Language Models and Future Prospects | Paper |
| 128 | LLMs Applications - Healthcare | Large Language Models in Mental Health Care: a Scoping Review | Paper |
| 129 | LLMs Applications - Healthcare | The utility of ChatGPT as an example of large language models in healthcare education, research and practice: Systematic review on the future perspectives and | Paper |
| 130 | LLMs Applications - Healthcare | The imperative for regulatory oversight of large language models (or generative AI) in healthcare | Paper |
| 131 | LLMs Applications - Healthcare | A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics | Paper |
| 132 | LLMs Applications - Healthcare | The Shaky Foundations of Clinical Foundation Models: A Survey of Large Language Models and Foundation Models for EMRs | Paper |
| 133 | LLMs Applications - Games | Large Language Models and Games: A Survey and Roadmap | Paper |
| 134 | LLMs Applications - Games | Large Language Models and Video Games: A Preliminary Scoping Review | Paper |
| 135 | LLMs Applications - NLP Tasks | Large Language Models for Information Retrieval: A Survey | Paper |
| 136 | LLMs Applications - NLP Tasks | Large Language Models for Generative Information Extraction: A Survey | Paper |
| 137 | LLMs Applications - NLP Tasks | Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey | Paper |
| 138 | LLMs Applications - NLP Tasks | If LLM Is the Wizard, Then Code Is the Wand: A Survey on How Code Empowers Large Language Models to Serve as Intelligent Agents | Paper |
| 139 | LLMs Applications - Software Engineering | Large Language Models for Software Engineering: Survey and Open Problems | Paper |
| 140 | LLMs Applications - Software Engineering | Large Language Models for Software Engineering: A Systematic Literature Review | Paper |
| 141 | LLMs Applications - Software Engineering | Software Testing with Large Language Models: Survey, Landscape, and Vision | Paper |
| 142 | LLMs Applications - Software Engineering | Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Code | Paper |
| 143 | LLMs Applications - Recommender Systems | Foundation Models for Recommender Systems: A Survey and New Perspectives | Paper |
| 144 | LLMs Applications - Recommender Systems | User Modeling in the Era of Large Language Models: Current Research and Future Directions | Paper |
| 145 | LLMs Applications - Recommender Systems | A Survey on Large Language Models for Personalized and Explainable Recommendations | Paper |
| 146 | LLMs Applications - Recommender Systems | Large Language Models for Generative Recommendation: A Survey and Visionary Discussions | Paper |
| 147 | LLMs Applications - Recommender Systems | A Survey on Large Language Models for Recommendation | Paper |
| 148 | LLMs Applications - Recommender Systems | How Can Recommender Systems Benefit from Large Language Models: A Survey | Paper |
| 149 | LLMs Applications - Graphs | A Survey of Graph Meets Large Language Model: Progress and Future Directions | Paper |
| 150 | LLMs Applications - Graphs | Large Language Models on Graphs: A Comprehensive Survey | Paper |
| 151 | LLMs Applications - Graphs | The Contribution of Knowledge in Visiolinguistic Learning: A Survey on Tasks and Challenges | Paper |
| 152 | LLMs Applications - Other | Large Language Models in Finance: A Survey | Paper |
| 153 | LLMs Applications - Other | Mathematical Language Models: A Survey | Paper |
| 154 | LLMs Applications - Other | Recent applications of AI to environmental disciplines: A review | Paper |
| 155 | LLMs Applications - Other | Opportunities and Challenges of Applying Large Language Models in Building Energy Efficiency and Decarbonization Studies: An Exploratory Overview | Paper |
| 156 | LLMs Applications - Other | When Large Language Models Meet Citation: A Survey | Paper |
| 157 | LLMs Applications - Other | A Survey of Text Watermarking in the Era of Large Language Models | Paper |
| 158 | LLMs Applications - Other | The future of gpt: A taxonomy of existing chatgpt research, current challenges, and possible future directions | Paper |
| 159 | LLMs Applications - Other | Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models | Paper |
| 160 | LLMs Applications - Other | Opportunities and Challenges of Applying Large Language Models in Building Energy Efficiency and Decarbonization Studies: An Exploratory Overview | Paper |
| 161 | LLMs Applications - Other | When Large Language Models Meet Citation: A Survey | Paper |
| 162 | LLMs Applications - Other | A Survey of Text Watermarking in the Era of Large Language Models | Paper |
| 163 | LLMs Applications - Other | The future of gpt: A taxonomy of existing chatgpt research, current challenges, and possible future directions | Paper |
| 164 | LLMs Applications - Other | Summary of ChatGPT-Related Research and Perspective Towards the Future of Large Language Models | Paper |
| 165 | Vision Papers | Nobel Turing Challenge: Creating the Engine for Scientific Discovery | Paper |
| 166 | Vision Papers | Artificial Intelligence to Win the Nobel Prize and Beyond: Creating the Engine for Scientific Discovery | Paper |
| 167 | Vision Papers | The AI Scientist: Towards Fully Automated Open-ended Scientific Discovery | Paper |
| 168 | Vision Papers | Emergent autonomous scientific research capabilities of large language models | Paper |
| 169 | Vision Papers | What is missing in autonomous discovery: open challenges for the community | Paper |
| 170 | Vision Papers | The future of fundamental science led by generative closed-loop artificial intelligence | Paper |
| 171 | Multi-Agent Systems | CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society | Paper |
| 172 | Multi-Agent Systems | Dynamic LLM-Agent Network: An LLM-Agent Collaboration Framework with Agent Team Optimization | Paper |
| 173 | Multi-Agent Systems | AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework | Paper |
| 174 | Reasoning & Knowledge | Graph of Thoughts: Solving Elaborate Problems with Large Language Models | Paper |
| 175 | Reasoning & Knowledge | KnowAgent: Knowledge-augmented Planning for LLM-based Agents | Paper |
| 176 | Reasoning & Knowledge | Improving Factuality and Reasoning in Language Models through Multiagent Debate | Paper |
| 177 | Research Planning | ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models | Paper |
| 178 | Research Planning | SciMon: Scientific Inspiration Machines Optimized for Novelty | Paper |
| 179 | Research Planning | AutoSurvey: Large Language Models Can Automatically Write Surveys | Paper |
| 180 | Experimental Design | DISCOVERYWORLD: A Virtual Environment for Developing and Evaluating Automated Scientific Discovery Agents | Paper |
| 181 | Experimental Design | Genesis: Towards the Automation of Systems Biology Research | Paper |
| 182 | Clinical Decision Support | MDAgents: An Adaptive Collaboration of LLMs for Medical Decision-Making | Paper |
| 183 | Clinical Decision Support | Beyond Direct Diagnosis: LLM-based Multi-Specialist Agent Consultation for Automatic Diagnosis | Paper |
| 184 | Clinical Decision Support | MedAide: Towards an Omni Medical Aide via Specialized LLM-based Multi-Agent Collaboration | Paper |
| 185 | Clinical Decision Support | Large Language Models as Agents in the Clinic | Paper |
| 186 | Clinical Decision Support | MAGDA: Multi-Agent Guideline-Driven Diagnostic Assistance | Paper |
| 187 | Healthcare Systems | ColaCare: Enhancing Electronic Health Record Modeling through Large Language Model-Driven Multi-Agent Collaboration | Paper |
| 188 | Healthcare Systems | Agent Hospital: A Simulacrum of Hospital with Evolvable Medical Agents | Paper |
| 189 | Healthcare Systems | ClinicalLab: Aligning Agents for Multi-Departmental Clinical Diagnostics in the Real World | Paper |
| 190 | Healthcare Systems | AIPatient: Simulating Patients with EHRs and LLM Powered Agentic Workflow | Paper |
| 191 | Medical Education | Medco: Medical education copilots based on a multi-agent framework | Paper |
| 192 | Medical Education | AgentClinic: a multimodal agent benchmark to evaluate AI in simulated clinical environments | Paper |
| 193 | Medical Imaging | CXR-Agent: Vision-language models for chest X-ray interpretation with uncertainty aware radiology reporting | Paper |
| 194 | Medical Imaging | PathGen-1.6M: 1.6 Million Pathology Image-text Pairs Generation through Multi-agent Collaboration | Paper |
| 195 | Genomics | BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments | Paper |
| 196 | Genomics | GeneAgent: Self-verification Language Agent for Gene Set Knowledge Discovery using Domain Databases | Paper |
| 197 | Genomics | Large Language Models as Biomedical Hypothesis Generators: A Comprehensive Evaluation | Paper |
| 198 | Bioinformatics Tools | BIA: BioInformatics Agent - Unleashing the Power of Large Language Models to Reshape Bioinformatics Workflow | Paper |
| 199 | Bioinformatics Tools | CellAgent: An LLM-driven Multi-Agent Framework for Automated Single-cell Data Analysis | Paper |
| 200 | Bioinformatics Tools | SeqMate: A Novel Large Language Model Pipeline for Automating RNA Sequencing | Paper |
| 201 | Drug Discovery | DrugAgent: Explainable Drug Repurposing Agent with Large Language Model-based Reasoning | Paper |
| 202 | Drug Discovery | Malade: Orchestration of LLM-powered agents with retrieval augmented generation for pharmacovigilance | Paper |
| 203 | Molecular Modeling | ChatMol Copilot: An Agent for Molecular Modeling and Computation Powered by LLMs | Paper |
| 204 | Molecular Modeling | A review of large language models and autonomous agents in chemistry | Paper |
| 205 | Earth & Environmental Sci | An LLM Agent for Automatic Geospatial Data Analysis | Paper |
| 206 | Evaluation & Benchmarking | AgentBench: Evaluating LLMs as Agents | Paper |
| 207 | Evaluation & Benchmarking | ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate | Paper |
| 208 | Evaluation & Benchmarking | Benchmarking large language models as ai research agents | Paper |
| 209 | Domain Benchmarks | BioKGBench: A Knowledge Graph Checking Benchmark of AI Agent for Biomedical Science | Paper |
| 210 | Domain Benchmarks | GenoTEX: A Benchmark for Evaluating LLM-Based Exploration of Gene Expression Data | Paper |
| 211 | Domain Benchmarks | IdeaBench: Benchmarking Large Language Models for Research Idea Generation | Paper |
| 212 | Survey & Review | Scientific discovery in the age of artificial intelligence | Paper |
| 213 | Survey & Review | The rise and potential of large language model based agents: A survey | Paper |
| 214 | Survey & Review | Large language model based multi-agents: A survey of progress and challenges | Paper |
| 215 | Survey & Review | A survey on LLM-based multi-agent systems: workflow, infrastructure, and challenges | Paper |
| 216 | Survey & Review | AI for Biomedicine in the Era of Large Language Models | Paper |
| 217 | Survey & Review | A Survey on Medical Large Language Models: Technology, Application, Trustworthiness, and Future Directions | Paper |
| 218 | Survey & Review | From LLMs to LLM-based Agents for Software Engineering: A Survey | Paper |
| 219 | Survey & Review | Large Language Models for Scientific Discovery: A Survey | Paper |
| 220 | Survey & Review | Large Language Models for Scientific Discovery: A Survey of Applications, Opportunities, and Challenges | Paper |
| 221 | Survey & Review | Large Language Models for Scientific Discovery: A Survey of Methods and Tools | Paper |
| 222 | Survey & Review | Large Language Models in Scientific Discovery: A Survey | Paper |
| 223 | Survey & Review | Large Language Models for Scientific Discovery: A Survey of Benchmarks, Datasets, and Evaluation Methods | Paper |
| 224 | Survey & Review | A Survey of LLM-based Agents for Scientific Discovery | Paper |
| 225 | Survey & Review | Large Language Models as Scientific Agents: A Survey | Paper |
| 226 | Survey & Review | Multi-Agent Systems for Scientific Discovery: A Survey | Paper |
| 227 | Survey & Review | LLM-based Agents in Scientific Research: A Survey | Paper |
| 228 | Survey & Review | LLMs for Automated Scientific Discovery: A Survey | Paper |