mlsanityData to 14 Oct 2026

InstructABSA: Instruction Learning for Aspect Based Sentiment Analysis

arXiv 2302.08624 ↗First posted 16 Feb 2023cs.CL cs.LGcited by 23

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Abstract (arXiv)

We introduce InstructABSA, an instruction learning paradigm for Aspect-Based Sentiment Analysis (ABSA) subtasks. Our method introduces positive, negative, and neutral examples to each training sample, and instruction tune the model (Tk-Instruct) for ABSA subtasks, yielding significant performance improvements. Experimental results on the Sem Eval 2014, 15, and 16 datasets demonstrate that InstructABSA outperforms the previous state-of-the-art (SOTA) approaches on Term Extraction (ATE), Sentiment Classification(ATSC) and Sentiment Pair Extraction (ASPE) subtasks. In particular, InstructABSA outperforms the previous state-of-the-art (SOTA) on the Rest14 ATE subtask by 5.69% points, the Rest15 ATSC subtask by 9.59% points, and the Lapt14 AOPE subtask by 3.37% points, surpassing 7x larger models. We also get competitive results on AOOE, AOPE, and AOSTE subtasks indicating strong generalization ability to all subtasks. Exploring sample efficiency reveals that just 50% train data is required to get competitive results with other instruction tuning approaches. Lastly, we assess the quality of instructions and observe that InstructABSA's performance experiences a decline of ~10% when adding misleading examples.

Key facts. Cited by 23 papers in the map (data through 14 Oct 2026). Builds on 53 of its 89 references that are in the map. First posted on arXiv 16 Feb 2023.

Builds on

53 of 89 references.

References · 53

  1. 2022Training language models to follow instructions with human feedbackcited by 15,971
  2. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  3. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,780
  4. 2022Self-Instruct: Aligning Language Models with Self-Generated Instructionscited by 2,724
  5. 2020DeBERTa: Decoding-enhanced BERT with Disentangled Attentioncited by 2,181
  6. 2022Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answeringcited by 1,919
  7. 2021Multitask Prompted Training Enables Zero-Shot Task Generalizationcited by 1,470
  8. 2020CodeBERT: A Pre-Trained Model for Programming and Natural Languagescited by 1,310
  9. 2022Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Taskscited by 868
  10. 2021Cross-Task Generalization via Natural Language Crowdsourcing Instructionscited by 699
  11. 2019CodeSearchNet Challenge: Evaluating the State of Semantic Code Searchcited by 654
  12. 2021MetaICL: Learning to Learn In Contextcited by 454
38 more
  1. 2021AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Promptscited by 268
  2. 2018code2vec: Learning Distributed Representations of Codecited by 250
  3. 2017Learning to Represent Programs with Graphscited by 220
  4. 2021Reframing Instructional Prompts to GPTk's Languagecited by 176
  5. 2016DeepCoder: Learning to Write Programscited by 149
  6. 2021Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collectionscited by 128
  7. 2019Knowing What, How and Why: A Near Complete Solution for Aspect-based Sentiment Analysiscited by 123
  8. 2021A Unified Generative Framework for Aspect-Based Sentiment Analysiscited by 97
  9. 2020The Turking Test: Can Language Models Understand Instructions?cited by 82
  10. 2020Learning from Task Descriptionscited by 78
  11. 2021When Can Models Learn From Explanations? A Formal Framework for Understanding the Roles of Explanation Datacited by 75
  12. 2018Aspect Based Sentiment Analysis with Gated Convolutional Networkscited by 65
  13. 2021A Joint Training Dual-MRC Framework for Aspect Based Sentiment Analysiscited by 62
  14. 2021Hierarchical Task Learning from Language Instructions with Unified Transformers and Self-Monitoringcited by 53
  15. 2019Open-Domain Targeted Sentiment Analysis via Span-Based Extraction and Classificationcited by 50
  16. 2017Code Completion with Neural Attention and Pointer Networkscited by 49
  17. 2021Bidirectional Machine Reading Comprehension for Aspect Sentiment Triplet Extractioncited by 40
  18. 2018Neural-Guided Deductive Search for Real-Time Program Synthesis from Examplescited by 39
  19. 2022Is a Question Decomposition Unit All We Need?cited by 37
  20. 2018Learning to Represent Editscited by 34
  21. 2022InstructionNER: A Multi-Task Instruction-Based Generative Framework for Few-shot NERcited by 31
  22. 2021Learning to Generate Task-Specific Adapters from Task Descriptioncited by 28
  23. 2020Minimize Exposure Bias of Seq2Seq Models in Joint Entity and Relation Extractioncited by 27
  24. 2021Open Aspect Target Sentiment Classification with Natural Language Promptscited by 20
  25. 2022Less is More: Summary of Long Instructions is Better for Program Synthesiscited by 17
  26. 2022HELP ME THINK: A Simple Prompting Strategy for Non-experts to Create Customized Content with Modelscited by 17
  27. 2022How Many Data Samples is an Additional Instruction Worth?cited by 16
  28. 2022Instruction Tuning for Few-Shot Aspect-Based Sentiment Analysiscited by 16
  29. 2020Introducing Syntactic Structures into Target Opinion Word Extraction with Deep Learningcited by 15
  30. 2022"John is 50 years old, can his son be 65?" Evaluating NLP Models' Understanding of Feasibilitycited by 15
  31. 2022BioTABQA: Instruction Learning for Biomedical Table Question Answeringcited by 13
  32. 2022Generative Aspect-Based Sentiment Analysis with Contrastive Learning and Expressive Structurecited by 13
  33. 2020GRACE: Gradient Harmonized and Cascaded Labeling for Aspect-based Sentiment Analysiscited by 12
  34. 2021Context-NER : Contextual Phrase Generation at Scalecited by 11
  35. 2019A Novel Aspect-Guided Deep Transition Model for Aspect Based Sentiment Analysiscited by 8
  36. 2021LSA: Modeling Aspect Sentiment Coherency via Local Sentiment Aggregationcited by 8
  37. 2022A Generative Language Model for Few-shot Aspect-Based Sentiment Analysiscited by 7
  38. 2021Empirical Analysis on Effectiveness of NLP Methods for Predicting Code Smellcited by 4

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Citing papers per year: 2023: 5; 2024: 6; 2025: 5; 2026: 7.

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  1. 2024Affective Computing in the Era of Large Language Models: A Survey from the NLP Perspectivecited by 25
  2. 2023TarGEN: Targeted Data Generation with Large Language Modelscited by 17
  3. 2024MEMO-Bench: A Multiple Benchmark for Text-to-Image and Multimodal Large Language Models on Human Emotion Analysiscited by 11
  4. 2025OpinioRAG: Towards Generating User-Centric Opinion Highlights from Large-scale Online Reviewscited by 4
  5. 2023EDM3: Event Detection as Multi-task Text Generationcited by 3
  6. 2023A Novel Counterfactual Data Augmentation Method for Aspect-Based Sentiment Analysiscited by 3
  7. 2024Fine-tuning multilingual language models in Twitter/X sentiment analysis: a study on Eastern-European V4 languagescited by 2
  8. 2024Instruct-DeBERTa: A Hybrid Approach for Aspect-based Sentiment Analysis on Textual Reviewscited by 2
  9. 2025When LLMs Team Up: The Emergence of Collaborative Affective Computingcited by 2
  10. 2025From Annotation to Adaptation: Metrics, Synthetic Data, and Aspect Extraction for Aspect-Based Sentiment Analysis with Large Language Modelscited by 1
  11. 2023Efficacy of Machine-Generated Instructionscited by 0
  12. 2023Towards a Unified Multimodal Reasoning Frameworkcited by 0
11 more
  1. 2024Extensible Multi-Granularity Fusion Network and Transferable Curriculum Learning for Aspect-based Sentiment Analysiscited by 0
  2. 2024SILC-EFSA: Self-aware In-context Learning Correction for Entity-level Financial Sentiment Analysiscited by 0
  3. 2025Leveraging Deep Neural Networks for Aspect-Based Sentiment Classificationcited by 0
  4. 2025Multi-domain Multilingual Sentiment Analysis in Industry: Predicting Aspect-based Opinion Quadruplescited by 0
  5. 2026Large-Scale Aspect-Based Sentiment Analysis with Reasoning-Infused LLMscited by 0
  6. 2026Label-Consistent Data Generation for Aspect-Based Sentiment Analysis Using LLM Agentscited by 0
  7. 2026From Prediction to Justification: Aligning Sentiment Reasoning with Human Rationale via Reinforcement Learningcited by 0
  8. 2026Task-Routed Mixture-of-Experts with Cognitive Appraisal for Implicit Sentiment Analysiscited by 0
  9. 2026Shifting from Discrete to Continuous Reference Data: QSM-Derived Horizontal Tree Biomass Distribution for Deep Learning Biomass Estimationcited by 0
  10. 2026STAR-OPD: Structured Aspect-Cascade-Aware On-Policy Reward Distillation for ABSA Quadruple Extractioncited by 0
  11. 2026Dependency Reasoning for Aspect Sentiment Quadruple Predictioncited by 0