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Papers that changed AI, with a plain-language explainer for each.

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  1. 2026

    Kimi K3: Open Frontier Intelligence

    arXiv

    Kimi K3 is Moonshot AI's 2.8-trillion-parameter open mixture-of-experts model with native vision and a one-million-token context, released with full weights. Its report describes the architecture, training and serving work behind it, and reports frontier-level results that still trail the strongest proprietary models.

    Large language modelsOpen sourceChina

  2. 2026

    Muse Spark Safety & Preparedness Report

    arXiv

    Meta's safety and preparedness report for Muse Spark, the model behind Meta AI, sets out the catastrophic-risk evaluations behind its launch and argues that, with mitigations applied, residual risk is acceptable.

    Large language modelsFoundation modelsSafety & governance

  3. 2026

    DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence

    arXiv

    A preview report on the DeepSeek-V4 series, describing a 1.6-trillion-parameter Pro model and a 284-billion-parameter Flash model, both with one-million-token context, plus the attention, connection and optimization changes that make that length affordable.

    Large language modelsOpen sourceChina

  4. 2026

    Qwen3.5-Omni Technical Report

    arXiv

    The Qwen3.5-Omni Technical Report documents Alibaba's Qwen3.5-Omni, a hundreds-of-billions-parameter model that understands long audio and video and generates speech across 10 languages, reporting state-of-the-art results on 215 audio and audio-visual benchmarks.

    Large language modelsOpen sourceChina

  5. 2026

    GLM-5: from Vibe Coding to Agentic Engineering

    arXiv

    Zhipu's GLM-5 report describes a 744-billion-parameter mixture-of-experts model built on sparse attention and asynchronous reinforcement learning, aimed at moving AI-assisted programming from vibe coding toward agentic engineering.

    Large language modelsChinaAgents & tool use

  6. 2025

    Kimi K2: Open Agentic Intelligence

    arXiv

    Kimi K2 is Moonshot AI's trillion-parameter mixture-of-experts model, pre-trained with the MuonClip optimizer and post-trained on large-scale agentic data plus reinforcement learning; the report reports state-of-the-art results among open-source non-thinking models and releases base and post-trained checkpoints.

    Large language modelsOpen sourceChina

  7. 2025

    Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

    arXiv

    The Gemini 2.5 technical report, submitted to arXiv on 7 July 2025, documents Google's Gemini 2.5 Pro and 2.5 Flash models: their reasoning, long-context video handling, and cost-versus-capability positioning.

    Large language modelsFoundation modelsMultimodal

  8. 2025

    The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text

    arXiv

    An eight-terabyte collection of public domain and openly licensed text for pretraining language models, released together with two 7B-parameter models trained on it to show the data is enough.

    Large language modelsOpen sourceData & datasets

  9. 2025

    Qwen3 Technical Report

    arXiv

    The Qwen3 Technical Report presents Alibaba's Qwen3 family of dense and mixture-of-experts language models, which unify thinking and non-thinking modes, add a controllable thinking budget, and are released under the Apache 2.0 licence.

    Large language modelsOpen sourceChina

  10. 2025

    s1: Simple test-time scaling

    arXiv

    A paper showing that a 32B model fine-tuned on 1,000 carefully chosen questions and run with a simple "budget forcing" trick can beat o1-preview on competition maths by up to 27%, with model, data and code released.

    Large language modelsResearch historyDeep learning

  11. 2025

    DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

    arXiv

    The DeepSeek-R1 report described how a reasoning model was trained largely with reinforcement learning, rewarding correct answers, and reached performance comparable to OpenAI's o1 on math, code and reasoning benchmarks. Its weights were released openly.

    Large language modelsOpen sourceChina

  12. 2024

    DeepSeek-V3 Technical Report

    arXiv

    A technical report from DeepSeek-AI on DeepSeek-V3, a mixture-of-experts language model with 671 billion total parameters, describing its architecture, training pipeline, and evaluations, including a full training run of 2.788 million H800 GPU hours.

    Large language modelsOpen sourceChina

  13. 2024

    The Llama 3 Herd of Models

    arXiv

    Meta's 2024 paper describing Llama 3 as a family of foundation models — 8B, 70B and 405B parameters — trained on about 15 trillion tokens and reported to match leading models such as GPT-4 across a wide range of tasks.

    Large language modelsResearch historyOpen source

  14. 2024

    The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

    arXiv

    FineWeb is a 15-trillion-token pretraining dataset built from 96 Common Crawl snapshots and released in 2024 with its curation code and ablation models; its educational subset, FineWeb-Edu, improves results on knowledge- and reasoning-heavy benchmarks.

    Large language modelsOpen sourceData & datasets

  15. 2024

    τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains

    arXiv

    τ-bench is a benchmark, submitted to arXiv in June 2024, that tests language agents in dynamic conversations with a simulated user, with domain-specific API tools and policy rules, and scores them by database state rather than by the text of their replies.

    Large language modelsResearch historyAgents & tool use

  16. 2024

    MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

    arXiv

    MMLU-Pro is a 2024 benchmark that makes the widely used MMLU knowledge test harder: its questions are reasoning-focused and each has ten answer options instead of four.

    Large language modelsResearch historyReasoning

  17. 2024

    LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

    arXiv

    A benchmark for code LLMs that keeps collecting fresh contest problems from LeetCode, AtCoder and CodeForces, so that scores reflect ability rather than memorised test data, and that also tests code repair and execution reasoning.

    Large language modelsResearch historyData & datasets

  18. 2024

    Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

    arXiv

    A report from Google's Gemini Team introducing the Gemini 1.5 family, multimodal models built around very long context, with Gemini 1.5 Pro recalling information across up to 10 million tokens.[^1]

    Large language modelsResearch historyFoundation models

  19. 2024

    Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research

    arXiv

    Dolma is an openly released English corpus of three trillion tokens, built from web text, papers, code, books, social media and Wikipedia, with a paper documenting both the dataset and the pipeline used to curate it.

    Large language modelsOpen sourceData & datasets

  20. 2024

    Mixtral of Experts

    arXiv

    Mixtral 8x7B is a sparse mixture-of-experts language model from Mistral AI. A router sends each token to two of eight experts per layer, so the model holds 47B parameters but uses 13B during inference.

    Large language modelsResearch historyOpen source