An alignment assessment of the UK AISI cybertesting incident
An alignment assessment of model actions that exceeded the intended scope of a cybersecurity evaluation.
THE RESEARCH ATLAS
AI Papers & Technical Reports
Important research organized by date. Catalog snapshot 2026-10-25; a selection, not a live exhaustive database.
65 research records
Using thousands of AI agents to uncover new leads in biological data
A research overview of distributed agents linking large biological datasets with scientific literature. Proposed connections still require experimental follow-up.
Advancing coding in low-resource programming languages
Official research discussion of improving coding capabilities in languages with less available training material.
Scaling Misuse Detection with Self-Assessment
Models assess their own conversations as an additional misuse-detection layer, reusing cached context to limit overhead.
Gemini 4 Argon — Model Card
Official model documentation covering evaluation, limitations and safety considerations. The date records the listed model-card update.
PointWalker: Mapless Quadruped Locomotion Directly From Raw LiDAR Point Clouds
Fuses LiDAR point clouds and proprioception through attention, connecting terrain perception with a reinforcement-learned quadruped policy.
Investigating unintended model actions in our evaluations and internal use
A report of unintended actions observed during model evaluation and internal use, with discussion of safeguards.
Advancing computer use with Ironclad
An official account of progress in computer-use agents. Read the original methods and evaluations separately from deployment claims.
Nano Banana 2.1 — Model Card
Official documentation for an image-and-text model, including inputs, outputs, architecture dependencies and safety evaluation.
FACT: A Multimodal Force-Action-Track Foundation Model for Human-to-Robot Dexterity
Human and robot demonstrations are combined with force-aware planning for dexterous manipulation.
What work can robots do?
A task-level analysis of robot exposure that distinguishes demonstrated capability in limited settings from general deployment.
UnifoLM-WLA-1.0: One Model Driven, Whole-Body Coordination
Connects embodied understanding, interaction-centric world modeling and action learning for tabletop and whole-body humanoid manipulation.
Qwen-Audio-Agent Technical Report
A foreground-background architecture separates voice interaction from asynchronous task execution, coordinating authorization, state and delivery.
DeepSeek-V4.1-Flash: smarter, faster, more efficient
Official release introducing an asymmetric causal encoder-decoder architecture and linking its technical report and model resources.
Introducing Grok 4.6
An official technical release describing supplemental training, regenerated SFT trajectories and agentic reinforcement learning.
Qwen-Image-2.0-RL Technical Report
A diffusion-model post-training pipeline combines task-specific rewards, reinforcement learning and on-policy distillation.
Qwen-RobotWorld Technical Report: Unifying Embodied World Modeling through Language-Conditioned Video Generation
A language-conditioned video world model predicts future visual trajectories across manipulation, navigation and driving settings.
XPeng X-World: Controllable Multi-View Generative World Model for Autonomous Driving
Describes a controllable multi-view world model used for driving simulation, scenario generation, and evaluation.
Qwen3.5-Omni Technical Report
The report explores an omni-modal model family and training over heterogeneous visual, textual and audio data.
Qwen3-Coder-Next Technical Report
An open-weight model for coding agents explores strong training recipes with a small active parameter footprint.
UniDex: A Robot Foundation Suite for Universal Dexterous Hand Control from Egocentric Human Videos
A dataset, VLA policy and capture setup connect human demonstrations to control across different dexterous hands.
A “diff” tool for AI: Finding behavioral differences in new models
An interpretability research overview explores ways to identify behavior differences between AI models beyond predefined tests.
Kimi K2.5: Visual Agentic Intelligence
Studies joint visual-language training and multi-agent task decomposition in an open multimodal model.
Scaling social science research
An open-source toolkit uses language models to help turn qualitative text and image data into measurable variables.
UnifoLM-VLA-0: A Vision-Language-Action (VLA) Framework under UnifoLM Family
Continues training on robot manipulation data, connecting visual-language understanding and spatial instructions to action prediction.
Qwen3-ASR Technical Report
A speech-recognition family and a forced-alignment model address multilingual transcription and timestamp prediction.
DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models
Sparse attention and post-training methods are combined to improve efficiency, reasoning and agent-oriented behavior.
Qwen3-VL Technical Report
The Qwen vision-language family integrates text, image and video understanding across several model sizes.
Alpamayo-R1: Bridging Reasoning and Action Prediction for Generalizable Autonomous Driving in the Long Tail
Connects driving reasoning and action prediction through Cosmos-Reason and a diffusion trajectory decoder, studying reasoning-action consistency.
Gemini Robotics 1.5: Pushing the Frontier of Generalist Robots with Advanced Embodied Reasoning, Thinking, and Motion Transfer
The report combines embodied reasoning, interleaved thinking and motion transfer across robot embodiments.
gpt-oss-120b & gpt-oss-20b Model Card
Open-weight reasoning models are described through their architecture, training, capabilities and safety evaluations.
MolmoAct: Action Reasoning Models that can Reason in Space
Depth-aware perception, spatial planning and low-level action prediction are organized into an explicit action-reasoning pipeline.
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
An industrial model-family report covering reasoning, multimodal input, long contexts and agent-related evaluations.
SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
A compact vision-language-action model explores accessible robot learning and an efficient inference pipeline.
Qwen3 Technical Report
Dense and mixture-of-experts models integrate thinking and non-thinking behavior, with configurable inference-time reasoning.
Huawei Qiankun ADS 4: World Engine and World Behavior Model (WEWA)
Huawei's official WEWA description links generated scenarios in a cloud world engine with an on-vehicle world behavior model.
π0.5: a Vision-Language-Action Model with Open-World Generalization
A vision-language-action system studies generalization across environments and tasks using varied sources of supervision.
GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
A coupled vision-language and diffusion architecture combines reasoning with continuous robot-action generation.
Gemini Robotics: Bringing AI into the Physical World
Gemini-based models address robot manipulation and embodied reasoning, connecting multimodal understanding with physical control.
Cosmos World Foundation Model Platform for Physical AI
A platform of video curation, tokenizers, pretrained world models and post-training for physical-AI applications.
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reinforcement learning is used to develop reasoning behavior, with additional pipelines for usable models and distillation.
DeepSeek-V3 Technical Report
A mixture-of-experts language model combines architectural and training-efficiency techniques, including latent attention and multi-token prediction.
EMMA: End-to-End Multimodal Model for Autonomous Driving
Builds on Gemini to predict driving trajectories, perception objects and road structure from camera inputs and text.
π0: A Vision-Language-Action Flow Model for General Robot Control
A pretrained vision-language backbone is combined with flow-based action generation for diverse robot tasks.
SAM 2: Segment Anything in Images and Videos
Extends promptable segmentation from images to video using streaming memory and interactive data collection.
OpenVLA: An Open-Source Vision-Language-Action Model
An open vision-language-action model and adaptation framework make generalist robot policy research more accessible.
Mixtral of Experts
Introduces a sparse mixture-of-experts model exploring model capacity and activated computation.
GAIA-1: A Generative World Model for Autonomous Driving
Models video, text and vehicle actions as sequences to generate conditioned driving scenes and possible futures.
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
Vision-language models are trained to produce robot actions, exploring transfer from web-scale learning to robotic control.
Direct Preference Optimization: Your Language Model is Secretly a Reward Model
A preference-based objective optimizes a language model directly, avoiding a separate reward-model training stage.
GPT-4 Technical Report
The report describes GPT-4’s capabilities, evaluation results and limitations while leaving important training details undisclosed.
Diffusion Policy: Visuomotor Policy Learning via Action Diffusion
Robot control is formulated as conditional denoising of action sequences, linking diffusion models to visuomotor learning.
Planning-oriented Autonomous Driving
Unifies perception, prediction and planning around the driving objective, using query interfaces to coordinate tasks.
Constitutional AI: Harmlessness from AI Feedback
A set of written principles guides critique, revision and AI-generated preference feedback during alignment.
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness
An IO-aware attention algorithm reduces memory transfers while computing exact attention.
Training language models to follow instructions with human feedback
Human demonstrations and preference feedback are used to improve how a language model follows instructions.
Training Compute-Optimal Large Language Models
The study examines how to allocate a training-compute budget between model size and training data.
LoRA: Low-Rank Adaptation of Large Language Models
Low-rank trainable updates adapt a frozen pretrained model without updating all of its parameters.
Learning Transferable Visual Models From Natural Language Supervision
Contrastive training aligns images with natural-language descriptions, enabling transfer to new visual categories.
Denoising Diffusion Probabilistic Models
A generative model learns to reverse a gradual noise process, establishing an influential approach to image synthesis.
Language Models are Few-Shot Learners
GPT-3 studies how larger autoregressive language models perform new tasks through examples in their input context.
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
Masked-language pretraining learns bidirectional representations that can be adapted to language-understanding tasks.
The ApolloScape Open Dataset for Autonomous Driving and its Application
Documents a driving dataset and applications for sensor fusion, semantic understanding, and localization.
Attention Is All You Need
The Transformer replaces recurrent sequence processing with attention, creating a foundation for many later language and multimodal models.
ImageNet Classification with Deep Convolutional Neural Networks
A deep convolutional network demonstrated how data, GPU computation and learned representations could transform visual recognition.
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