Notable data and AI papers

627 papers · 45 labs

DiffusionGemma Technical Report research paper by Google DeepMind, 2026

Google DeepMind · Foundation models · Jul 31, 2026 · 14 citations · 40 upvotes · unverified

Read on arXiv

What it shows

DiffusionGemma is a fine-tuned mixture-of-experts language model that uses discrete diffusion to generate text blocks in parallel, achieving high speed while preserving capabilities like multimodal inputs and reasoning.

By DiffusionGemma Team, Adrien Ali Taïga, James Assiene and 41 more · arXiv 2608.00146 · PDF

UnverifiedHugging Face's summary; not yet checked by hand.

More from Google DeepMind

All 12
Foundation modelsJul 2, 2026Gemma 4 Technical ReportOpen multimodal models from 2.3B to 31B parameters, with a thinking mode and image and audio input.Google DeepMind356 citations81 upvotesRead →Inference and efficiencyUnverifiedMay 17, 2026LiteFrame: Efficient Vision Encoders Unlock Frame Scaling in Video LLMsLiteFrame, a lightweight video encoder with Compressed Token Distillation training method, reduces latency and increases frame processing capacity for long-form video understanding in Video LLMs while maintaining accuracy.Google DeepMind2 citations26 upvotesRead →Foundation modelsUnverifiedMar 25, 2026Understanding the Challenges in Iterative Generative Optimization with LLMsGenerative optimization using large language models faces challenges due to implicit design decisions about artifact modification and learning evidence that significantly impact success across different applications.Google DeepMind11 citations27 upvotesRead →ReasoningUnverifiedMar 3, 2026LoGeR: Long-Context Geometric Reconstruction with Hybrid MemoryLoGeR enables long-term 3D video reconstruction by combining bidirectional priors with a hybrid memory system that includes parametric Test-Time Training and non-parametric sliding window attention mechanisms.Google DeepMind46 citations63 upvotesRead →Agents and evaluationUnverifiedDec 4, 2025SIMA 2: A Generalist Embodied Agent for Virtual WorldsSIMA 2, built on a Gemini foundation model, interacts in 3D virtual worlds, reasons about goals, handles complex instructions, and autonomously learns new skills through open-ended self-improvement.Google DeepMind27 citations26 upvotesRead →Multimodal and roboticsUnverifiedNov 10, 2025Robot Learning from a Physical World ModelPhysWorld integrates video generation and physical world modeling to enable accurate robotic manipulation from visual demonstrations without real robot data.Google DeepMind23 citations32 upvotesRead →Agents and evaluationUnverifiedOct 8, 2025Vibe Checker: Aligning Code Evaluation with Human PreferenceVibe Checker evaluates LLMs by combining functional correctness and instruction following to better align with human coding preferences.Google DeepMind2 citations34 upvotesRead →Multimodal and roboticsUnverifiedSep 24, 2025Video models are zero-shot learners and reasonersVeo 3, a generative video model, exhibits zero-shot capabilities across various visual tasks, suggesting a trajectory towards becoming a unified, generalist vision foundation model.Google DeepMind237 citations100 upvotesRead →
Topic
About this paper
Citations
14, 1 influential · Semantic Scholar
Upvotes
40 · Hugging Face
Lab
Google DeepMind · on Companies · on Acquisitions

Changes

CitationsNov 2, 2026Citations rose from 6 to 14.
CitationsOct 12, 2026Citations rose from 5 to 6.
CitationsOct 5, 2026Citations rose from 1 to 5.
CitationsSep 25, 2026A first count of 1 influential citations.
CitationsSep 25, 2026A first count of 1 citations.
New paperSep 25, 2026Found by the weekly Hugging Face scan; not yet checked by hand.