mlsanityData to 7 Oct 2026

DanceHA: A Multi-Agent Framework for Document-Level Aspect-Based Sentiment Analysis

arXiv 2603.16546 ↗First posted 17 Mar 2026cs.CL cs.AIcited by 0

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Abstract (arXiv)

Aspect-Based Sentiment Intensity Analysis (ABSIA) has garnered increasing attention, though research largely focuses on domain-specific, sentence-level settings. In contrast, document-level ABSIA--particularly in addressing complex tasks like extracting Aspect-Category-Opinion-Sentiment-Intensity (ACOSI) tuples--remains underexplored. In this work, we introduce DanceHA, a multi-agent framework designed for open-ended, document-level ABSIA with informal writing styles. DanceHA has two main components: Dance, which employs a divide-and-conquer strategy to decompose the long-context ABSIA task into smaller, manageable sub-tasks for collaboration among specialized agents; and HA, Human-AI collaboration for annotation. We release Inf-ABSIA, a multi-domain document-level ABSIA dataset featuring fine-grained and high-accuracy labels from DanceHA. Extensive experiments demonstrate the effectiveness of our agentic framework and show that the multi-agent knowledge in DanceHA can be effectively transferred into student models. Our results highlight the importance of the overlooked informal styles in ABSIA, as they often intensify opinions tied to specific aspects.

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References · 20

  1. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  2. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,393
  3. 2023Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debatecited by 995
  4. 2023Sentiment Analysis in the Era of Large Language Models: A Reality Checkcited by 262
  5. 2019BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment Analysiscited by 176
  6. 2024RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectorscited by 157
  7. 2021Aspect Sentiment Quad Prediction as Paraphrase Generationcited by 99
  8. 2024Chain of Preference Optimization: Improving Chain-of-Thought Reasoning in LLMscited by 94
  9. 2024AgentReview: Exploring Peer Review Dynamics with LLM Agentscited by 92
  10. 2023MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Predictioncited by 49
  11. 2025ResearchQA: Evaluating Scholarly Question Answering at Scale Across 75 Fields with Survey-Mined Questions and Rubricscited by 44
  12. 2017Satirical News Detection and Analysis using Attention Mechanism and Linguistic Featurescited by 14
8 more
  1. 2023Human-in-the-Loop Schema Inductioncited by 13
  2. 2025Probabilistic Soundness Guarantees in LLM Reasoning Chainscited by 13
  3. 2024Self-Consistent Reasoning-based Aspect-Sentiment Quad Prediction with Extract-Then-Assign Strategycited by 12
  4. 2024Rethinking LLM Uncertainty: A Multi-Agent Approach to Estimating Black-Box Model Uncertaintycited by 11
  5. 2022Challenges for Open-domain Targeted Sentiment Analysiscited by 9
  6. 2025Overhearing LLM Agents: A Survey, Taxonomy, and Roadmapcited by 3
  7. 2023Document-Level Supervision for Multi-Aspect Sentiment Analysis Without Fine-grained Labelscited by 1
  8. 2025A Dataset for Distilling Knowledge Priors from Literature for Therapeutic Designcited by 1

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  1. 2026Label-Consistent Data Generation for Aspect-Based Sentiment Analysis Using LLM Agents
  2. 2025Are You Sure You're Positive? Consolidating Chain-of-Thought Agents with Uncertainty Quantification for Aspect-Category Sentiment Analysis
  3. 2026MASTE: A Multi-Agent Pipeline for Zero-Shot Aspect Sentiment Triplet Extraction
  4. 2023On the Robustness of Aspect-based Sentiment Analysis: Rethinking Model, Data, and Training
  5. 2026Large-Scale Aspect-Based Sentiment Analysis with Reasoning-Infused LLMs
  6. 2025From Annotation to Adaptation: Metrics, Synthetic Data, and Aspect Extraction for Aspect-Based Sentiment Analysis with Large Language Models
  7. 2026AnnoABSA: A Web-Based Annotation Tool for Aspect-Based Sentiment Analysis with Retrieval-Augmented Suggestions
  8. 2024Enhancing Long-Range Dependency with State Space Model and Kolmogorov-Arnold Networks for Aspect-Based Sentiment Analysis