Can LLMs Catch a Rigged Backtest? A Clean-Control Calibration Benchmark

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Can LLMs Catch a Rigged Backtest? A Clean-Control Calibration Benchmark. It centres on Benchmarks, and also names DeepSeek. Reported by arXiv. Bharat Hunt files it under AI Models and AI Research — the section covering a new or updated model, its capabilities, benchmarks or availability.

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arXivCan LLMs Catch a Rigged Backtest? A Clean-Control Calibration BenchmarkYesterdayMakar Ulesov

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Cross-Scale Transfer Learning for Depression Severity Prediction: From PHQ-8 to HAMD-17 Across Languages and Clinical Paradigms

Cross-Scale Transfer Learning for Depression Severity Prediction: From PHQ-8 to HAMD-17 Across Languages and Clinical Paradigms. It centres on Fine-tuning, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.

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AI Models36

SkillGym: Internalizing Human Skills into LLMs for Real-World Problem Solving

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Can LLMs Catch a Rigged Backtest? A Clean-Control Calibration Benchmark

Companies, models and people in this story

Reported by arXiv

Cross-Scale Transfer Learning for Depression Severity Prediction: From PHQ-8 to HAMD-17 Across Languages and Clinical Paradigms

SkillGym: Internalizing Human Skills into LLMs for Real-World Problem Solving

MWE-ECL: Recoverable Long-Range Context Does Not Always Override Local Lexical Priors

FeatLens: Feature-Guided Dynamic Code Graph Construction and Retrieval for Repository-Level Code Generation

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Reported by arXiv

Related AI coverage

Cross-Scale Transfer Learning for Depression Severity Prediction: From PHQ-8 to HAMD-17 Across Languages and Clinical Paradigms

SkillGym: Internalizing Human Skills into LLMs for Real-World Problem Solving

MWE-ECL: Recoverable Long-Range Context Does Not Always Override Local Lexical Priors

FeatLens: Feature-Guided Dynamic Code Graph Construction and Retrieval for Repository-Level Code Generation