LONSREX introduces a metric-based pipeline to identify necessary and sufficient rationales when creating training data for fine-tuning LLMs on explainable misinformation detection, addressing limitations of naive label-based filtering.
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2 Pith papers cite this work. Polarity classification is still indexing.
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OOWM models the world as an explicit symbolic tuple with UML diagrams and trains via SFT plus GRPO to outperform text-based CoT on embodied planning benchmarks.
citing papers explorer
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Are Rationales Necessary and Sufficient? Tuning LLMs for Explainable Misinformation Detection
LONSREX introduces a metric-based pipeline to identify necessary and sufficient rationales when creating training data for fine-tuning LLMs on explainable misinformation detection, addressing limitations of naive label-based filtering.
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OOWM: Structuring Embodied Reasoning and Planning via Object-Oriented Programmatic World Modeling
OOWM models the world as an explicit symbolic tuple with UML diagrams and trains via SFT plus GRPO to outperform text-based CoT on embodied planning benchmarks.