mlsanityData to 7 Oct 2026

LitLLM: A Toolkit for Scientific Literature Review

arXiv 2402.01788 ↗First posted 2 Feb 2024cs.CL cs.AI cs.IRcited by 61

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Abstract (arXiv)

Conducting literature reviews for scientific papers is essential for understanding research, its limitations, and building on existing work. It is a tedious task which makes an automatic literature review generator appealing. Unfortunately, many existing works that generate such reviews using Large Language Models (LLMs) have significant limitations. They tend to hallucinate-generate non-factual information-and ignore the latest research they have not been trained on. To address these limitations, we propose a toolkit that operates on Retrieval Augmented Generation (RAG) principles, specialized prompting and instructing techniques with the help of LLMs. Our system first initiates a web search to retrieve relevant papers by summarizing user-provided abstracts into keywords using an off-the-shelf LLM. Authors can enhance the search by supplementing it with relevant papers or keywords, contributing to a tailored retrieval process. Second, the system re-ranks the retrieved papers based on the user-provided abstract. Finally, the related work section is generated based on the re-ranked results and the abstract. There is a substantial reduction in time and effort for literature review compared to traditional methods, establishing our toolkit as an efficient alternative. Our project page including the demo and toolkit can be accessed here: https://litllm.github.io

Key facts. Cited by 61 papers in the map (data through 7 Oct 2026). Builds on 27 of its 40 references that are in the map. First posted on arXiv 2 Feb 2024.

Builds on

27 of 40 references.

References · 27

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  3. 2022Large Language Models are Zero-Shot Reasonerscited by 4,323
  4. 2021Prefix-Tuning: Optimizing Continuous Prompts for Generationcited by 3,878
  5. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,747
  6. 2023Retrieval-Augmented Generation for Large Language Models: A Surveycited by 2,185
  7. 2023A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questionscited by 1,582
  8. 2022Large Language Models Are Human-Level Prompt Engineerscited by 1,020
  9. 2022Galactica: A Large Language Model for Sciencecited by 736
  10. 2021Learning How to Ask: Querying LMs with Mixtures of Soft Promptscited by 376
  11. 2023Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agentscited by 356
  12. 2023Large Language Models for Information Retrieval: A Surveycited by 331
15 more
  1. 2023Large Language Models are Zero-Shot Rankers for Recommender Systemscited by 307
  2. 2021WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learningcited by 285
  3. 2019Gradio: Hassle-Free Sharing and Testing of ML Models in the Wildcited by 176
  4. 2022OpenAlex: A fully-open index of scholarly works, authors, venues, institutions, and conceptscited by 166
  5. 2023RankZephyr: Effective and Robust Zero-Shot Listwise Reranking is a Breeze!cited by 151
  6. 2021Retrieval Augmented Code Generation and Summarizationcited by 148
  7. 2023The Semantic Scholar Open Data Platformcited by 109
  8. 2020Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articlescited by 96
  9. 2020Retrieval-Augmented Generation for Code Summarization via Hybrid GNNcited by 89
  10. 2022Self-Prompting Large Language Models for Zero-Shot Open-Domain QAcited by 39
  11. 2021Efficient Retrieval Augmented Generation from Unstructured Knowledge for Task-Oriented Dialogcited by 33
  12. 2023Agent Instructs Large Language Models to be General Zero-Shot Reasonerscited by 32
  13. 2022EditEval: An Instruction-Based Benchmark for Text Improvementscited by 30
  14. 2022MAMO: Masked Multimodal Modeling for Fine-Grained Vision-Language Representation Learningcited by 11
  15. 2022Do DALL-E and Flamingo Understand Each Other?cited by 7

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 14; 2025: 31; 2026: 16.

61 papers.

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  1. 2025MultiAgentBench: Evaluating the Collaboration and Competition of LLM agentscited by 169
  2. 2025From Automation to Autonomy: A Survey on Large Language Models in Scientific Discoverycited by 86
  3. 2025From AI for Science to Agentic Science: A Survey on Autonomous Scientific Discoverycited by 74
  4. 2025PaSa: An LLM Agent for Comprehensive Academic Paper Searchcited by 61
  5. 2025Robin: A multi-agent system for automating scientific discoverycited by 57
  6. 2025Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimizationcited by 52
  7. 2025Curie: Toward Rigorous and Automated Scientific Experimentation with AI Agentscited by 31
  8. 2024ChatCite: LLM Agent with Human Workflow Guidance for Comparative Literature Summarycited by 30
  9. 2024The emergence of Large Language Models (LLM) as a tool in literature reviews: an LLM automated systematic reviewcited by 20
  10. 2024MASSW: A New Dataset and Benchmark Tasks for AI-Assisted Scientific Workflowscited by 19
  11. 2024When LLMs Play the Telephone Game: Cultural Attractors as Conceptual Tools to Evaluate LLMs in Multi-turn Settingscited by 17
  12. 2025How Far Are AI Scientists from Changing the World?cited by 15
38 more
  1. 2025Predicting Empirical AI Research Outcomes with Language Modelscited by 14
  2. 2024LitLLMs, LLMs for Literature Review: Are we there yet?cited by 12
  3. 2025AbGen: Evaluating Large Language Models in Ablation Study Design and Evaluation for Scientific Researchcited by 12
  4. 2025Beyond "Not Novel Enough": Enriching Scholarly Critique with LLM-Assisted Feedbackcited by 12
  5. 2025InteractiveSurvey: An LLM-based Personalized and Interactive Survey Paper Generation Systemcited by 11
  6. 2024VISION: A Modular AI Assistant for Natural Human-Instrument Interaction at Scientific User Facilitiescited by 10
  7. 2025ScholarEval: Research Idea Evaluation Grounded in Literaturecited by 10
  8. 2025LLLMs: A Data-Driven Survey of Evolving Research on Limitations of Large Language Modelscited by 9
  9. 2025Evolving Roles of LLMs in Scientific Innovation: Assistant, Collaborator, Scientist, and Evaluatorcited by 9
  10. 2025A Survey of AI Scientistscited by 9
  11. 2026AutoResearch AI: Towards AI-Powered Research Automation for Scientific Discoverycited by 9
  12. 2025From Hypothesis to Publication: A Comprehensive Survey of AI-Driven Research Support Systemscited by 8
  13. 2025GPT-4.1 Sets the Standard in Automated Experiment Design Using Novel Python Librariescited by 8
  14. 2024Automated Review Generation Method Based on Large Language Modelscited by 7
  15. 2025SurveyGen: Quality-Aware Scientific Survey Generation with Large Language Modelscited by 7
  16. 2024Cutting Through the Clutter: The Potential of LLMs for Efficient Filtration in Systematic Literature Reviewscited by 6
  17. 2024Good Idea or Not, Representation of LLM Could Tellcited by 6
  18. 2026Autonomous Research Agents: A Survey of AI Scientists and the Verification Gapcited by 6
  19. 2024LLAssist: Simple Tools for Automating Literature Review Using Large Language Modelscited by 4
  20. 2025Completing A Systematic Review in Hours instead of Months with Interactive AI Agentscited by 4
  21. 2025Can AI Validate Science? Benchmarking LLMs for Accurate Scientific Claim rightarrow Evidence Reasoningcited by 4
  22. 2025SurveyGen-I: Consistent Scientific Survey Generation with Evolving Plans and Memory-Guided Writingcited by 4
  23. 2025SciRAG: Adaptive, Citation-Aware, and Outline-Guided Retrieval and Synthesis for Scientific Literaturecited by 4
  24. 2026The World Won't Stay Still: Programmable Evolution for Agent Benchmarkscited by 4
  25. 2025ScienceMeter: Tracking Scientific Knowledge Updates in Language Modelscited by 3
  26. 2025SGSimEval: A Comprehensive Multifaceted and Similarity-Enhanced Benchmark for Automatic Survey Generation Systemscited by 3
  27. 2025Preserving Cultural Identity with Context-Aware Translation Through Multi-Agent AI Systemscited by 2
  28. 2025Enhancing Agentic Autonomous Scientific Discovery with Vision-Language Model Capabilitiescited by 2
  29. 2026Sci-Reasoning: A Dataset Decoding AI Innovation Patternscited by 2
  30. 2026DeepXiv-SDK: An Agentic Data Interface for Scientific Literaturecited by 2
  31. 2026IntrAgent: An LLM Agent for Content-Grounded Information Retrieval through Literature Reviewcited by 2
  32. 2026Multi-Turn Agentic Scientific Literature Search via Workflow Inductioncited by 2
  33. 2024Contextualized AI for Cyber Defense: An Automated Survey using LLMscited by 1
  34. 2025Leveraging LLMs for Semi-Automatic Corpus Filtration in Systematic Literature Reviewscited by 1
  35. 2025Eliminating Agentic Workflow for Introduction Generation with Parametric Stage Tokenscited by 1
  36. 2026Experiment-as-Code Labs: A Declarative Stack for AI-Driven Scientific Discoverycited by 1
  37. 2026Can AI Evaluate AI Scientists? A Benchmarking Study of Autonomous Research Generation Systems Using Automated Multi-Model Reviewcited by 1
  38. 2026COGTRL: Training LLMs for Scientific Discovery Assistance using Cognitive Traces via Reinforcement Learningcited by 1

50 most cited of 61 All 61 (JSON)

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  5. 2024vitaLITy 2: Reviewing Academic Literature Using Large Language Models
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  8. 2025Accelerating Discovery: Rapid Literature Screening with LLMs ↗