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Papers Explained 394: OpenThoughtsThe goal of the OpenThoughts project is to create open-source datasets for training reasoning models. The OpenThoughts2–1M dataset led to…12h ago12h ago
Papers Explained 393: Gemini 2.5The Gemini 2.X model family, including Gemini 2.5 Pro, Gemini 2.5 Flash, Gemini 2.0 Flash, and Gemini 2.0 Flash-Lite, represents Google’s…1d ago1d ago
Papers Explained 392: Hard Negative Mining for Domain-Specific RetrievalThis paper addresses the challenge of retrieving accurate, domain-specific information in enterprise search systems, by dynamically…4d ago4d ago
Papers Explained 391: Adaptive Reasoning ModelAdaptive Reasoning Model (ARM) is a reasoning model capable of adaptively selecting appropriate reasoning formats based on the task at…5d ago5d ago
Papers Explained 390: Perplexity-based Importance Refinement (PIR)PIR (Perplexity-based Importance Refinement) is a framework that quantitatively evaluates the importance of each reasoning step based on…6d ago6d ago
Papers Explained 389: short-m@kIn this work, the assumption that long thinking chains result in better reasoning capabilities is challenged. It is first demonstrated that…Jun 17Jun 17
Papers Explained 388: MagistralMagistral is Mistral AI’s first reasoning model, designed for domain-specific, transparent, and multilingual reasoning. It comes in two…Jun 16Jun 16
Papers Explained 387: Sarvam-TranslateSarvam-Translate is trained by fine-tuning Gemma3–4B-IT. It supports 22 Indian languages — Hindi, Bengali, Marathi, Telugu, Tamil…Jun 13Jun 13
