KB국민은행에서 제공하는 경제/금융 도메인에 특화된 한국어 ALBERT 모델

A symbolic benchmark for verifiable chain-of-thought financial reasoning. Includes executable templates, 58 topics across 12 domains, and ChainEval metrics.

Research on all kind of NLP in market forecasting, expert estimation, etc.

🎯 Fine-tuning LLMs using LlamaFactory for financial intent understanding | Evaluating open-source models on OpenFinData benchmark | Full implementation with multiple models (Qwen2.5/ChatGLM3/Baichuan2/Llama3)

7-signal financial text classifier for Reddit posts and market news — sentiment, directionality, quality, sarcasm, relevance, sector rotation. Free tier, no credit card.

An open-source sell-side analyst that never sleeps. Screens stocks, runs DCF + reverse DCF, extracts earnings call signals, and ships an institutional-grade research note ;automatically.

Resource-efficient LLM distillation: Improving sustainability and reducing computational costs of Large Language Models in financial analytics through knowledge distillation.

This repository contains code for fine-tuning a BERT-based model for financial sentiment analysis. The project uses the Financial PhraseBank dataset to train a model that can classify financial texts as positive, neutral, or negative.

Living Literature Review on Memestock identification using NLP

AI-powered crypto sentiment analysis platform with real-time news monitoring, dual VADER/FinBERT models, FastAPI backend, Next.js dashboard, and Flutter mobile app.

NLP pipeline that detects linguistic deception in earnings calls using FinBERT, sentence-BERT Q&A evasion scoring, and XGBoost trained on SEC restatement history.

Regime-based evaluation framework for financial NLP stability. Implements chronological cross-validation, semantic drift quantification via Jensen-Shannon divergence, and multi-faceted robustness profiling. Replicates Sun et al.'s (2025) methodology with modular, auditable Python codebase.

SEC FinDoc File Extraction

A structured evaluation pipeline for LLM-generated outputs in financial supervision contexts. Combines PRA-aligned prompts, thread-type detection, and metric-level meta-review to assess relevance, justification, and actionability across 50+ regulatory and conversational metrics.

Fine-grained transformer ABSA with financial and clinical domain adaptation

Official implementation of OrgSense — a theory-grounded LLM prompting framework for detecting strategic drift in corporate earnings calls and 10-K filings, with the StratDrift-10K annotation corpus and downstream predictive validity analyses.

Financial sentiment analysis API with fine-tuned FinBERT achieving 88.57% accuracy on Financial PhraseBank dataset

Financial NER and number extraction over four engines (regex, spaCy, word2number, BERT) exposed through a Flask API with a comparison view. Docker-packaged backend + Node/Express frontend.

Deterministic computation experts integrated into sparse MoE transformer routing for exact financial calculations in a single forward pass

Fine-tuning small LLMs (Phi-3.5, LLaMA-3.2) with QLoRA for summarizing earnings call transcripts. Evaluated with ROUGE and BERTScore. Part of NLP for Finance coursework.