<p>**Abstract:** This paper introduces Causal Contrastive Learning (CCL), a novel framework for generating more robust and interpretable counterfactual explanat...
freederia.com·16h
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“Reasoning with Sampling” — Notes on Karan & Du (2025)
kosti.bearblog.dev·2d
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Only 9% of developers think AI code can be used without human oversight, BairesDev survey reveals
venturebeat.com·12h
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Building an AI-Powered MetaTrader 5 Trading Assistant with Python and Flask
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AI Fatigue: Reflections on the Human Side of AI’s Rapid Advancement
cacm.acm.org·1d
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Explicit Knowledge-Guided In-Context Learning for Early Detection of Alzheimer's Disease
arxiv.org·1d
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LandSegmenter: Towards a Flexible Foundation Model for Land Use and Land Cover Mapping
arxiv.org·3h
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Investigating CoT Monitorability in Large Reasoning Models
arxiv.org·3h
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CAE: Character-Level Autoencoder for Non-Semantic Relational Data Grouping
arxiv.org·3h
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REACT-LLM: A Benchmark for Evaluating LLM Integration with Causal Features in Clinical Prognostic Tasks
arxiv.org·1d
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One Model for All: Universal Pre-training for EEG based Emotion Recognition across Heterogeneous Datasets and Paradigms
arxiv.org·3h
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🧵 Making Proactive Agents with Code Generation
threadreaderapp.com·11h
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EGG-SR: Embedding Symbolic Equivalence into Symbolic Regression via Equality Graph
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