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https://tldr.takara.ai/p/2504.01903 STAR-1: Safer Alignment of Reasoning LLMs with 1K Data | Takara TLDR This paper introduces STAR-1, a high-quality, just-1k-scale safety dataset specifically designed for large reasoning models (LRMs) like DeepSeek-R1. Built on... reasoning llms https://arxiv.org/abs/2605.02933 [2605.02933] Relation Reasoning with LLMs in Expensive Optimization Abstract page for arXiv paper 2605.02933: Relation Reasoning with LLMs in Expensive Optimization relation reasoning llms expensive optimization https://www.nexairi.com/article/Technology/llm-reasoning-fragility-benchmark-2026/ Why Open-Weight LLMs Fail at Reasoning: The 55%... | Nexairi Apr 15, 2026 - New benchmark reveals open-weight reasoning models suffer catastrophic accuracy collapses when problems are paraphrased or reformatted. Frontier models show ... open weight llms fail reasoning https://arxiv.org/abs/2406.17961v2 [2406.17961v2] NormTab: Improving Symbolic Reasoning in LLMs Through Tabular Data Normalization Abstract page for arXiv paper 2406.17961v2: NormTab: Improving Symbolic Reasoning in LLMs Through Tabular Data Normalization symbolic reasoning https://www.aibase.com/news/3573 Large Language Models (LLMs) Struggle to Detect Errors in Reasoning but Can Correct Them This year, large language models (LLMs) have garnered significant attention in the AI community, particularly for their remarkable progress in natural language large language models https://www.adaline.ai/blog/what-is-chain-of-thought-reasoning-in-llms Chain-of-Thought Reasoning in LLMs: Techniques, Evolution, and Real-World Application | Adaline Apr 24, 2025 - How Chain-of-Thought reasoning enhances AI problem-solving capabilities chain of thought https://scipapermill.com/2025/08/03/unpacking-chain-of-thought-how-llms-are-leveling-up-reasoning-detection-and-domain-specific-intelligence-aug-3-2025/ Unpacking Chain-of-Thought: How LLMs Are Leveling Up Reasoning, Detection, and Domain-Specific... Aug 3, 2025 - Unpacking Chain-of-Thought: How LLMs Are Leveling Up Reasoning, Detection, and Domain-Specific Intelligence https://aicourse.nlp.town/docs/reasoning-models/ 4. Reasoning Models | Working with LLMs Reasoning models # During the first years of LLM development, the largest quality improvements originated from scaling up the training data. However, this... reasoning models working with llms https://www.antirez.com/news/146 Reasoning models are just LLMs - antirez reasoning models llms antirez https://fcmo.seamandan.com/ai/are-llms-just-fluent-nonsense-insights-into-chain-of-thought-limitations LLMs Generate Fluent Nonsense: Insights on AI Reasoning Limits Explore how LLMs generate fluent nonsense in reasoning. Discover insights on Chain-of-Thought limitations and practical guidance for developers. ai reasoning llms generate fluent nonsense https://www.promptingguide.ai/zh/prompts/reasoning Reasoning with LLMs | Prompt Engineering Guide!-- -- A Comprehensive Overview of Prompt Engineering prompt engineering reasoning llms guide https://labelbox.com/blog/multi-step-reasoning-teach-llms-to-think-critically/ Multi-step reasoning: Teach LLMs to think critically multi step reasoning teach llms https://arxiv.org/abs/2605.04906 [2605.04906] Strat-Reasoner: Reinforcing Strategic Reasoning of LLMs in Multi-Agent Games Abstract page for arXiv paper 2605.04906: Strat-Reasoner: Reinforcing Strategic Reasoning of LLMs in Multi-Agent Games