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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. 2026

    Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces

    arXiv

    Terminal-Bench 2.0 is a curated benchmark of 89 hard tasks carried out in computer terminal environments, built to measure how well AI agents handle realistic command-line work; frontier models and agents score below 65% on it.

    Research historyAgents & tool useCode

  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

    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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 2023

    SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

    arXiv

    A benchmark of 2,294 real software engineering problems taken from GitHub issues and the pull requests that resolved them, in which a model must edit a codebase to fix an issue; on release the best model solved under 2% of them.

    Research historyAgents & tool useData & datasets

  17. 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

  18. 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

  19. 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

  20. 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