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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

    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

  3. 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

  4. 2025

    ARC-AGI-2: A New Challenge for Frontier AI Reasoning Systems

    arXiv

    A 2025 paper introducing ARC-AGI-2, a benchmark of input-output puzzle tasks built to measure abstract reasoning in frontier AI systems, with human testing as a baseline and a task set designed to give a more granular signal of progress.

    Research historyReasoningSimulation

  5. 2025

    Humanity's Last Exam (HLE)

    arXiv

    Humanity's Last Exam (HLE) is a 2,500-question, multi-modal benchmark spanning dozens of academic subjects, built by experts worldwide so that frontier language models can still be measured after saturating older tests.

    Research historyMultimodalReasoning

  6. 2024

    SAM 2: Segment Anything in Images and Videos

    arXiv

    SAM 2 is a Meta FAIR foundation model that segments objects in images and videos from simple prompts such as points, boxes or masks, released together with a large video segmentation dataset and training code.

    Research historyDeep learningMultimodal

  7. 2024

    OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments

    arXiv

    OSWorld is a benchmark and environment for testing multimodal agents on 369 real computer tasks in Ubuntu, Windows and macOS; humans complete over 72.36% of the tasks, while the best model reaches only 12.24%.

    Research historyAgents & tool useMultimodal

  8. 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

  9. 2023

    GAIA: a benchmark for General AI Assistants

    arXiv

    GAIA is a benchmark of real-world questions that are easy for humans but hard for AI assistants, testing reasoning, multimodality, web browsing, and tool use. It compares AI progress against average human performance.

    Research historyAgents & tool useMultimodal

  10. 2023

    WebArena: A Realistic Web Environment for Building Autonomous Agents

    arXiv

    WebArena is a reproducible environment of four fully functional websites — e-commerce, a social forum, collaborative software development and content management — built for testing language-guided web agents. Its best GPT-4 agent completed 14.41% of tasks; humans completed 78.24%.[^1]

    Research historyAgents & tool useMultimodal

  11. 2023

    GPT-4 Technical Report

    arXiv 2303.08774

    OpenAI's technical report on GPT-4, submitted to arXiv in March 2023, describes a large multimodal Transformer model, reports human-level results on several professional benchmarks, and explains how the team made scaling behaviour predictable.

    Large language modelsResearch historyMultimodal

  12. 2022

    Learning skillful medium-range global weather forecasting

    Science

    GraphCast is a graph neural network trained on four decades of reanalysis data that produces 10-day global weather forecasts at 0.25 degree resolution in under a minute, outperforming the leading operational deterministic systems on most verification targets.

    Deep learningScienceSimulation

  13. 2022

    LAION-5B: An open large-scale dataset for training next generation image-text models

    arXiv

    LAION-5B is an openly available dataset of 5.85 billion CLIP-filtered image-text pairs, released so that researchers outside a handful of labs could study and reproduce large vision-language models.

    Open sourceMultimodalData & datasets

  14. 2022

    Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding (Imagen)

    arXiv

    Imagen is a text-to-image diffusion model that uses a large pretrained language model to encode prompts; it reached a zero-shot FID of 7.27 on COCO and introduced the DrawBench benchmark.

    Research historyMultimodalGenerative models

  15. 2022

    Magnetic control of tokamak plasmas through deep reinforcement learning

    Nature

    A 2022 Nature paper by Degrave, Felici and colleagues showing that a deep reinforcement learning controller can learn on its own to command all of a tokamak's magnetic control coils, producing and holding a range of plasma shapes.

    Deep learningHardware & computeScience

  16. 2021

    Zero-Shot Text-to-Image Generation (DALL·E)

    arXiv

    A 2021 OpenAI paper describing a single 12-billion-parameter autoregressive transformer trained on 250 million image-text pairs, which generates images from text and, evaluated zero-shot, is competitive with domain-specific models.

    Research historyMultimodalGenerative models

  17. 2021

    Learning Transferable Visual Models From Natural Language Supervision (CLIP)

    ICML

    CLIP is an OpenAI model trained on 400 million image-text pairs to map pictures and sentences into one shared space, so it can classify images zero-shot from a written description.

    Foundation modelsMultimodalComputer vision

  18. 2020

    NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis

    arXiv

    A 2020 paper by Mildenhall, Srinivasan, Tancik, Barron, Ramamoorthi and Ng that represents a scene as a neural radiance field: a network mapping 5D coordinates to density and colour, optimized from a sparse set of images with known camera poses.

    Research historyGenerative modelsComputer vision

  19. 2019

    Mastering Atari, Go, chess and shogi by planning with a learned model

    Nature

    MuZero is a DeepMind reinforcement-learning algorithm that learns a model of its environment and plans inside that model, mastering Atari, Go, chess and shogi without being given the rules of those games.

    Research historyDeep learningScience

  20. 2019

    On the Measure of Intelligence (ARC-AGI)

    arXiv

    A 2019 paper by Francois Chollet that defines intelligence as skill-acquisition efficiency and introduces the Abstraction and Reasoning Corpus (ARC), a benchmark of grid tasks that assumes no specialised knowledge or language.

    Research historyReasoningSimulation