LLMs copy biased analyst ratings in investment decisions but a new detection method encourages independent reasoning and can improve stock return predictions beyond human levels.
Fingpt: Democratizing internet-scale data for financial large language models
6 Pith papers cite this work. Polarity classification is still indexing.
6
Pith papers citing it
representative citing papers
FedSDR augments federated self-distillation with dual LoRA streams (local smoothing and global rectification) to produce globally aligned, factually faithful models under statistical heterogeneity.
FedShield-LLM integrates pruning and FHE on LoRA parameters to support secure, scalable federated fine-tuning of LLMs such as Llama-2.
MulFSA combines micro-level firm sentiment, meso-level industry sentiment, and duration-aware smoothing from PLMs/LLMs to extract a daily sentiment index that reduces credit spread forecast errors by 10.25% MAE and 11.94% MAPE on a 1.35M-text Chinese bond corpus.
citing papers explorer
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Fin-Bias: Comprehensive Evaluation for LLM Decision-Making under human bias in Finance Domain
LLMs copy biased analyst ratings in investment decisions but a new detection method encourages independent reasoning and can improve stock return predictions beyond human levels.
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FedSDR: Federated Self-Distillation with Rectification
FedSDR augments federated self-distillation with dual LoRA streams (local smoothing and global rectification) to produce globally aligned, factually faithful models under statistical heterogeneity.
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FedShield-LLM: A Secure and Scalable Federated Fine-Tuned Large Language Model
FedShield-LLM integrates pruning and FHE on LoRA parameters to support secure, scalable federated fine-tuning of LLMs such as Llama-2.
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MulFSA: Multi-level Financial Sentiment Analysis Framework for Bond Market
MulFSA combines micro-level firm sentiment, meso-level industry sentiment, and duration-aware smoothing from PLMs/LLMs to extract a daily sentiment index that reduces credit spread forecast errors by 10.25% MAE and 11.94% MAPE on a 1.35M-text Chinese bond corpus.
- MinT: Managed Infrastructure for Training and Serving Millions of LLMs
- MetaGraph: A Large-Scale Meta-Analysis of GenAI in Financial NLP (2022-2025)