Language Models Model Language research paper by Snowflake, 2025
Snowflake · Foundation models · Oct 14, 2025 · 0 citations · 26 upvotes · unverified
What it shows
The paper advocates for an empiricist approach to evaluating language models, emphasizing frequency of use over traditional theoretical frameworks.
By Łukasz Borchmann · arXiv 2510.12766 · PDF
UnverifiedHugging Face's summary; not yet checked by hand.
More from Snowflake
All 5Strategic Navigation or Stochastic Search? How Agents and Humans Reason Over Document CollectionsOn 2,250 questions over 800 PDFs, the best agents match human accuracy but lean on brute-force search rather than planning.
Snowflake3 citations66 upvotesRead →Agent World Model: Infinity Synthetic Environments for Agentic Reinforcement LearningLarge language model agents trained in synthetic environments with code-driven simulations and database-backed state transitions demonstrate superior out-of-distribution generalization compared to traditional benchmark-specific approaches.
Snowflake81 citations53 upvotesRead →SwiftKV: Fast Prefill-Optimized Inference with Knowledge-Preserving Model TransformationSwiftKV lets prompt tokens skip later layers and merges KV caches, cutting prefill cost for long-prompt workloads.
Snowflake21 citations2 upvotesRead →Arctic-Embed: Scalable, Efficient, and Accurate Text Embedding ModelsOpen text embedding models from 22M to 334M parameters that led MTEB retrieval for their size at release.
Snowflake84 citations2 upvotesRead →
Other foundation models papers
TopicBERT: 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.
Google125k citations33 upvotesRead →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.
OpenAI66.4k citations21 upvotesRead →GPT-4 Technical ReportA multimodal model that passes a simulated bar exam with a score around the top 10% of test takers.
OpenAI28.4k citations7 upvotesRead →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.
Meta22.6k citations25 upvotesRead →The Llama 3 Herd of ModelsOpen models up to 405B parameters that match leading closed models on many tasks.
Meta20.8k citations119 upvotesRead →Qwen3 Technical ReportQwen3, a unified series of large language models, integrates thinking and non-thinking modes, reduces computational resources, and achieves state-of-the-art performance across various tasks and languages.
Alibaba (Qwen)10.1k citations339 upvotesRead →
About this paper
- Venue
- arXiv.org
- Citations
- 0, 0 influential · Semantic Scholar
- Upvotes
- 26 · Hugging Face
- Lab
- Snowflake · on Companies · on Acquisitions · on Quarterly · on Paydays · on Releases · on TechConf
Changes
A first count of 0 influential citations.
A first count of 0 citations.
Found by the weekly Hugging Face scan; not yet checked by hand.