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https://www.alphaxiv.org/abs/2604.15726
LLM Reasoning Is Latent, Not the Chain of Thought | alphaXiv
View recent discussion. Abstract: This position paper argues that large language model (LLM) reasoning should be studied as latent-state trajectory formation...
llm reasoningthought alphaxivlatentchain
https://dev.to/backboardio/why-llm-reasoning-is-breaking-ai-infrastructure-and-how-to-fix-it-2aik
Why LLM Reasoning Is Breaking AI Infrastructure (And How to Fix It) - DEV Community
Apr 24, 2026 - If you've tried building anything serious on top of large language models (LLMs) recently, you've... Tagged with ai, webdev, programming, machinelearning.
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https://iclr.cc/virtual/2026/poster/10008605
ICLR Poster Thought Branches: Interpreting LLM Reasoning Requires Resampling
iclr posterllm reasoningthoughtbranchesinterpreting
https://simonwillison.net/tags/llm-reasoning/
Simon Willison on llm-reasoning
98 posts tagged ‘llm-reasoning’. Improving performance of LLMs through spending more tokens
simon willisonllm reasoning
https://intuitionlabs.ai/articles/humanitys-last-exam-ai-benchmark
Humanity's Last Exam: The AI Benchmark for LLM Reasoning | IntuitionLabs
Mar 4, 2026 - Learn about Humanity's Last Exam (HLE), the Nature-published AI benchmark testing true LLM reasoning with 2,500 expert-level questions. Updated with 2026...
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https://www.alphaxiv.org/overview/2604.15726
LLM Reasoning Is Latent, Not the Chain of Thought | alphaXiv
Research demonstrates that the core mechanism of Large Language Model reasoning is primarily driven by internal latent-state trajectories, rather than sole
llm reasoningthought alphaxivlatentchain
https://research.google/pubs/chain-of-table-evolves-tables-in-the-llm-reasoning-chain-for-table-understanding/
Chain-of-Table: Evolves Tables in the LLM Reasoning Chain for Table Understanding
llm reasoningchaintableevolvesunderstanding
https://www.informit.com/store/reinforcement-learning-for-llm-alignment-and-reasoning-9780135565025
Reinforcement Learning for LLM Alignment and Reasoning (Video Course) | InformIT
More Than 4 Hours of Video Instruction Learn the post-training techniques that make modern LLMs safe, aligned, and capable of complex reasoning. Overview...
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https://arxiv.org/abs/2503.01781
[2503.01781] Cats Confuse Reasoning LLM: Query Agnostic Adversarial Triggers for Reasoning Models
Abstract page for arXiv paper 2503.01781: Cats Confuse Reasoning LLM: Query Agnostic Adversarial Triggers for Reasoning Models
250301781catsconfusereasoning
https://arxiv.org/abs/2601.10332
[2601.10332] Think-Then-Generate: Reasoning-Aware Text-to-Image Diffusion with LLM Encoders
Abstract page for arXiv paper 2601.10332: Think-Then-Generate: Reasoning-Aware Text-to-Image Diffusion with LLM Encoders
image diffusion260110332thinkgenerate
https://arxiv.org/abs/2505.12717
[2505.12717] ToTRL: Unlock LLM Tree-of-Thoughts Reasoning Potential through Puzzles Solving
Abstract page for arXiv paper 2505.12717: ToTRL: Unlock LLM Tree-of-Thoughts Reasoning Potential through Puzzles Solving
2505unlockllmtreethoughts
https://epoch.ai/frontiermath/tiers-1-4
FrontierMath: LLM Benchmark for Advanced AI Math Reasoning | Epoch AI
FrontierMath Tiers 1-4 is an AI benchmark of hundreds of unpublished and extremely challenging math problems.
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