mlsanityData to 14 Oct 2026

Instruction-Tuning LLMs for Event Extraction with Annotation Guidelines

arXiv 2502.16377 ↗First posted 22 Feb 2025cs.CLcited by 18

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Abstract (arXiv)

In this work, we study the effect of annotation guidelines -- textual descriptions of event types and arguments, when instruction-tuning large language models for event extraction. We conducted a series of experiments with both human-provided and machine-generated guidelines in both full- and low-data settings. Our results demonstrate the promise of annotation guidelines when there is a decent amount of training data and highlight its effectiveness in improving cross-schema generalization and low-frequency event-type performance.

Key facts. Cited by 18 papers in the map (data through 14 Oct 2026). Builds on 25 of its 52 references that are in the map. First posted on arXiv 22 Feb 2025.

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25 of 52 references.

References · 25

  1. 2024The Llama 3 Herd of Modelscited by 14,715
  2. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  3. 2023QLoRA: Efficient Finetuning of Quantized LLMscited by 3,418
  4. 2024Qwen2.5-Coder Technical Reportcited by 1,203
  5. 2022Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Taskscited by 1,076
  6. 2023A Rank Stabilization Scaling Factor for Fine-Tuning with LoRAcited by 243
  7. 2023Large Language Models for Generative Information Extraction: A Surveycited by 185
  8. 2023InstructUIE: Multi-task Instruction Tuning for Unified Information Extractioncited by 170
  9. 2021Document-Level Event Argument Extraction by Conditional Generationcited by 155
  10. 2023Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulnesscited by 130
  11. 2023GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extractioncited by 119
  12. 2023Exploring the Feasibility of ChatGPT for Event Extractioncited by 76
13 more
  1. 2022Code4Struct: Code Generation for Few-Shot Event Structure Predictioncited by 70
  2. 2023CodeIE: Large Code Generation Models are Better Few-Shot Information Extractorscited by 68
  3. 2023Retrieval-Augmented Code Generation for Universal Information Extractioncited by 40
  4. 2023Instruct and Extract: Instruction Tuning for On-Demand Information Extractioncited by 36
  5. 2024KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extractioncited by 34
  6. 2023TextEE: Benchmark, Reevaluation, Reflections, and Future Challenges in Event Extractioncited by 28
  7. 2023Guideline Learning for In-context Information Extractioncited by 24
  8. 2023Don't Stop Pretraining? Make Prompt-based Fine-tuning Powerful Learnercited by 23
  9. 2023InstructIE: A Bilingual Instruction-based Information Extraction Datasetcited by 9
  10. 2024Improving Event Definition Following For Zero-Shot Event Detectioncited by 7
  11. 2024Are LLMs Good Annotators for Discourse-level Event Relation Extraction?cited by 7
  12. 2024SPEED++: A Multilingual Event Extraction Framework for Epidemic Prediction and Preparednesscited by 7
  13. 2023MAILEX: Email Event and Argument Extractioncited by 6

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 9; 2026: 9.

18 papers.

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  1. 2025Revisiting Prompt Optimization with Large Reasoning Models-A Case Study on Event Extractioncited by 6
  2. 2025Event Extraction in Large Language Modelcited by 5
  3. 2025DiCoRe: Enhancing Zero-shot Event Detection via Divergent-Convergent LLM Reasoningcited by 2
  4. 2025Extracting Events Like Code: A Multi-Agent Programming Framework for Zero-Shot Event Extractioncited by 2
  5. 2025Multimodal Event Detection: Current Approaches and Defining the New Playground through LLMs and VLMscited by 1
  6. 2025When Does Meaning Backfire? Investigating the Role of AMRs in NLIcited by 1
  7. 2025Batch Prompting Suppresses Overthinking Reasoning Under Constraint: How Batch Prompting Suppresses Overthinking in Reasoning Modelscited by 1
  8. 2026Improving Information Extraction with Learned Queriescited by 1
  9. 2025Reflective Agreement: Combining Self-Mixture of Agents with a Sequence Tagger for Robust Event Extractioncited by 0
  10. 2025ChunkLLM: A Lightweight Pluggable Framework for Accelerating LLMs Inferencecited by 0
  11. 2026RMPL: Relation-aware Multi-task Progressive Learning with Stage-wise Training for Multimedia Event Extractioncited by 0
  12. 2026Refining and Reusing Annotation Guidelines for LLM Annotationcited by 0
6 more
  1. 2026SL-BiLEM: Structured Learnable Behavior-in-the-Loop Epidemic Modeling for Forecasting and Policy Evaluationcited by 0
  2. 2026Applicability Condition Extraction for Therapeutic Drug-Disease Relationscited by 0
  3. 2026Beyond Clean Text: Evaluating Encoder and Decoder Robustness for Bangla Event Detection in Noisy Textcited by 0
  4. 2026A Multi-Domain and Multi-Task Generative Framework with Explicit Task and Domain Conditioning for Cross-Domain Event Extractioncited by 0
  5. 2026EAGER: Enhancing Generative Event Extraction via Reinforcement Learning with Verifiable Rewardscited by 0
  6. 2026ARGUS: Role-Aware Event Knowledge Graphs for U.S. Employment-Discrimination Complaintscited by 0