mlsanityData to 7 Oct 2026

Designing Heterogeneous LLM Agents for Financial Sentiment Analysis

arXiv 2401.05799 ↗First posted 11 Jan 2024cs.CL cs.AI cs.MAcited by 48

On the map: LLM agents and tool use → Financial trading and forecasting agents

Abstract (arXiv)

Large language models (LLMs) have drastically changed the possible ways to design intelligent systems, shifting the focuses from massive data acquisition and new modeling training to human alignment and strategical elicitation of the full potential of existing pre-trained models. This paradigm shift, however, is not fully realized in financial sentiment analysis (FSA), due to the discriminative nature of this task and a lack of prescriptive knowledge of how to leverage generative models in such a context. This study investigates the effectiveness of the new paradigm, i.e., using LLMs without fine-tuning for FSA. Rooted in Minsky's theory of mind and emotions, a design framework with heterogeneous LLM agents is proposed. The framework instantiates specialized agents using prior domain knowledge of the types of FSA errors and reasons on the aggregated agent discussions. Comprehensive evaluation on FSA datasets show that the framework yields better accuracies, especially when the discussions are substantial. This study contributes to the design foundations and paves new avenues for LLMs-based FSA. Implications on business and management are also discussed.

Key facts. Cited by 48 papers in the map (data through 7 Oct 2026). Placed in Financial trading and forecasting agents, one of 16 directions in LLM agents and tool use. Builds on 19 of its 56 references that are in the map. First posted on arXiv 11 Jan 2024.

Builds on

19 of 56 references.

References · 19

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2020Measuring Massive Multitask Language Understandingcited by 7,768
  3. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,155
  4. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,222
  5. 2023Improving Factuality and Reasoning in Language Models through Multiagent Debatecited by 1,739
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7 more
  1. 2022An Information-theoretic Approach to Prompt Engineering Without Ground Truth Labelscited by 88
  2. 2023Reasoning Implicit Sentiment with Chain-of-Thought Promptingcited by 79
  3. 2023Enhancing Financial Sentiment Analysis via Retrieval Augmented Large Language Modelscited by 67
  4. 2022What do LLMs Know about Financial Markets? A Case Study on Reddit Market Sentiment Analysiscited by 27
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 17; 2025: 23; 2026: 8.

48 papers.

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  1. 2024TradingAgents: Multi-Agents LLM Financial Trading Frameworkcited by 182
  2. 2024AI Agents Under Threat: A Survey of Key Security Challenges and Future Pathwayscited by 122
  3. 2024FinCon: A Synthesized LLM Multi-Agent System with Conceptual Verbal Reinforcement for Enhanced Financial Decision Makingcited by 112
  4. 2024A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challengescited by 86
  5. 2024Large Language Model Agent in Financial Trading: A Surveycited by 60
  6. 2024Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologiescited by 44
  7. 2024Social Science Meets LLMs: How Reliable Are Large Language Models in Social Simulations?cited by 26
  8. 2024Affective Computing in the Era of Large Language Models: A Survey from the NLP Perspectivecited by 24
  9. 2025TripTailor: A Real-World Benchmark for Personalized Travel Planningcited by 22
  10. 2024Better to Ask in English: Evaluation of Large Language Models on English, Low-resource and Cross-Lingual Settingscited by 14
  11. 2025LLaMAs Have Feelings Too: Unveiling Sentiment and Emotion Representations in LLaMA Models Through Probingcited by 14
  12. 2025Trading-R1: Financial Trading with LLM Reasoning via Reinforcement Learningcited by 14
36 more
  1. 2024Enhancing Financial Question Answering with a Multi-Agent Reflection Frameworkcited by 12
  2. 2025Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crewscited by 12
  3. 2025PSG-Agent: Personality-Aware Safety Guardrail for LLM-based Agentscited by 12
  4. 2025The Hidden Strength of Disagreement: Unraveling the Consensus-Diversity Tradeoff in Adaptive Multi-Agent Systemscited by 11
  5. 2025TokenFlow: Responsive LLM Text Streaming Serving under Request Burst via Preemptive Schedulingcited by 10
  6. 2025A Simple Ensemble Strategy for LLM Inference: Towards More Stable Text Classificationcited by 8
  7. 2026Replayable Financial Agents: A Determinism-Faithfulness Assurance Harness for Tool-Using LLM Agentscited by 7
  8. 2024Do Large Language Models Speak All Languages Equally? A Comparative Study in Low-Resource Settingscited by 6
  9. 2025Bridging Language Models and Financial Analysiscited by 4
  10. 2025Multi-level Value Alignment in Agentic AI Systems: Survey and Perspectivescited by 4
  11. 2025Finance Language Model Evaluation (FLaME)cited by 4
  12. 2025P2P: A Poison-to-Poison Remedy for Reliable Backdoor Defense in LLMscited by 4
  13. 2025Trade in Minutes! Rationality-Driven Agentic System for Quantitative Financial Tradingcited by 4
  14. 2025Mixup Model Merge: Enhancing Model Merging Performance through Randomized Linear Interpolationcited by 2
  15. 2025When LLMs Team Up: The Emergence of Collaborative Affective Computingcited by 2
  16. 2025AutoQual: An LLM Agent for Automated Discovery of Interpretable Features for Review Quality Assessmentcited by 2
  17. 2026A Scalable Entity-Based Framework for Auditing Bias in Large Language Modelscited by 2
  18. 2026A Review of Large Language Models for Stock Price Forecasting from a Hedge-Fund Perspectivecited by 2
  19. 2024Exploring Accuracy-Fairness Trade-off in Large Language Modelscited by 1
  20. 2025DiffoRA: Enabling Parameter-Efficient Fine-Tuning via Differential Module Selectioncited by 1
  21. 2025When Trust Collides: Decoding Human-LLM Cooperation Dynamics through the Prisoner's Dilemmacited by 1
  22. 2025OMS: On-the-fly, Multi-Objective, Self-Reflective Ad Keyword Generation via LLM Agentcited by 1
  23. 2025Ensembling Multilingual Transformers for Robust Sentiment Analysis of Tweetscited by 1
  24. 2025SCOUT: A Defense Against Data Poisoning Attacks in Fine-Tuned Language Modelscited by 1
  25. 2026AlphaCrafter: Harnessing Multi-Agent Workflows for Cross-Sectional Quantitative Tradingcited by 1
  26. 2024FiSTECH: Financial Style Transfer to Enhance Creativity without Hallucinations in LLMscited by 0
  27. 2024Improving Global Parameter-sharing in Physically Heterogeneous Multi-agent Reinforcement Learning with Unified Action Spacecited by 0
  28. 2024Doppelg"anger's Watch: A Split Objective Approach to Large Language Modelscited by 0
  29. 2024AI Learning Algorithms: Deep Learning, Hybrid Models, and Large-Scale Model Integrationcited by 0
  30. 2024CAPE: A Chinese Dataset for Appraisal-based Emotional Generation using Large Language Modelscited by 0
  31. 2025Stable LLM Ensemble: Interaction between Example Representativeness and Diversitycited by 0
  32. 2025Hierarchical AI Multi-Agent Fundamental Investing: Evidence from China's A-Share Marketcited by 0
  33. 2026APCD: Adaptive Path-Contrastive Decoding for Reliable Large Language Model Generationcited by 0
  34. 2026Leveraging Large Language Models for Sentiment Analysis: Multi-Modal Analysis of Decentraland's MANA Tokencited by 0
  35. 2026Can Agentic Trading Systems Pay for Their Own Intelligence?cited by 0
  36. 2026Poisoning Agentic Alpha: Adversarial Vulnerabilities Across Roles and Architectures in Multi-Agent Trading Systemscited by 0

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  2. 2024Aligning LLMs with Human Instructions and Stock Market Feedback in Financial Sentiment Analysis
  3. 2025Reasoning or Overthinking: Evaluating Large Language Models on Financial Sentiment Analysis
  4. 2025FinDPO: Financial Sentiment Analysis for Algorithmic Trading through Preference Optimization of LLMs
  5. 2025Adaptive Financial Sentiment Analysis for NIFTY 50 via Instruction-Tuned LLMs , RAG and Reinforcement Learning Approaches
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  7. 2023FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character Design
  8. 2024FinRobot: An Open-Source AI Agent Platform for Financial Applications using Large Language Models