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Papers.

Foundation models

Technical reports for new model families. 9 papers from 6 labs.

9 of 9 papers, newest first

PaperCitations
Gemma 4 Technical ReportOpen multimodal models from 2.3B to 31B parameters, with a thinking mode and image and audio input.Google DeepMind · Jul 2026106
The Llama 3 Herd of ModelsOpen models up to 405B parameters that match leading closed models on many tasks.Meta · Jul 202418.8k
Nemotron-4 340B Technical ReportOpen models sized for one 8-GPU server, aligned with over 98% synthetic data.NVIDIA · Jun 2024138
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your PhoneSmall models trained on filtered and synthetic data that run on a phone and rival much larger ones.Microsoft · Apr 20242,497
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextRecalls details across millions of tokens of text, hours of video and days of audio.Google DeepMind · Mar 20244,002
GPT-4 Technical ReportA multimodal model that passes a simulated bar exam with a score around the top 10% of test takers.OpenAI · Mar 202327.3k
LLaMA: Open and Efficient Foundation Language ModelsOpen models from 7B to 65B trained only on public data; the 13B model beats GPT-3 on most benchmarks.Meta · Feb 202321.7k
Language Models are Few-Shot LearnersGPT-3, a 175B-parameter model, does new tasks from a few examples in the prompt, with no fine-tuning.OpenAI · May 202063.6k
BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingPre-training a Transformer to fill in masked words, then fine-tuning it, beat task-specific models across language understanding tests.Google · Oct 2018121k

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

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