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Papers that changed AI, with a plain-language explainer for each.
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- 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.
- 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.
- 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.
- 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.
- 2025
Absolute Zero: Reinforced Self-play Reasoning with Zero Data
arXiv
A 2025 paper proposing Absolute Zero, a reinforcement-learning paradigm in which one model writes its own code-reasoning tasks and then solves them, with a code executor as the only judge, reaching state of the art on coding and maths without external training data.
- 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.
- 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.
- 2024
FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision
arXiv
FlashAttention-3 is an attention algorithm for NVIDIA Hopper (H100) GPUs that reaches up to 75% utilization in FP16 and close to 1.2 PFLOPs/s in FP8, using asynchronous execution and low-precision techniques.
- 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.
- 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.
- 2024
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
ICML
Tri Dao and Albert Gu's paper introduces state space duality, a framework showing that structured state space models and attention variants are closely related, and uses it to derive Mamba-2, whose core layer runs 2 to 8 times faster than Mamba's.
- 2024
Accurate structure prediction of biomolecular interactions with AlphaFold 3
Nature
AlphaFold 3, published in Nature in May 2024, extends structure prediction to biomolecular interactions, reporting greater accuracy than docking tools for protein–ligand binding and than AlphaFold-Multimer v.2.3 for antibody–antigen complexes.
- 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%.
- 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.
- 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.
- 2023
Mamba: Linear-Time Sequence Modeling with Selective State Spaces
arXiv
Mamba is a sequence-model architecture introduced by Albert Gu and Tri Dao that replaces attention with selective state space models, giving linear-time scaling, faster inference, and language-model quality competitive with Transformers twice its size.
- 2023
Scaling deep learning for materials discovery
Nature
A 2023 Nature paper from researchers at Google DeepMind presenting a scaled-up deep-learning approach to predicting stable crystal structures, screening 2.2 million candidates and reporting a large jump in stability-prediction accuracy.
- 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.
- 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.
- 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]