MemGuard-Alpha: Limits of Membership Inference for Detecting and Filtering Memorization-Contaminated Signals in LLM-Based Financial Forecasting
cs.LG
Submitted: 2026-03-26
Updated: 2026-09-24
Terminology
Sources
- Evaluating LLMs in Finance Requires Explicit Bias Consideration
- The Memorization Problem: Can We Trust LLMs' Economic Forecasts?
- Look-Ahead-Bench: a Standardized Benchmark of Look-ahead Bias in Point-in-Time LLMs for Finance
- Chronologically Consistent Large Language Models
- Can Blindfolded LLMs Still Trade? An Anonymization-First Framework for Portfolio Optimization
- Anonymization and Information Loss
- A Fast and Effective Solution to the Problem of Look-ahead Bias in LLMs
- Detecting Lookahead Bias in LLM Forecasts
- Assessing Look-Ahead Bias in Stock Return Predictions Generated By GPT Sentiment Analysis
- Your AI, Not Your View: The Bias of LLMs in Investment Analysis
- Posterior-Calibrated Causal Circuits in Variational Autoencoders: Why Image-Domain Interpretability Fails on Tabular Data
- DatedGPT: Preventing Lookahead Bias in Large Language Models with Time-Aware Pretraining
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