From the 1 of 7 linked papers with an AI index.
7 papers
SkillSmith: Learning to Compose Parametric Skills and Textual Knowledge
Lucio M. Dery, Benedict Aaron Tjandra, Siavash Samiei +4
SkillSmith is a method that lets a large language model reason over both textual knowledge and prefix‑tuned model weights, enabling it to generate new parametric skill prefixes for…
Context Training with Active Information Seeking
Zeyu Huang, Adhiguna Kuncoro, Qixuan Feng +4
Most existing large language models (LLMs) are expensive to adapt after deployment, especially when a task requires newly produced information or niche domain knowledge. Recent wor…
Decoupled DiLoCo for Resilient Distributed Pre-training
Arthur Douillard, Keith Rush, Yani Donchev +14
Modern large-scale language model pre-training relies heavily on the single program multiple data (SPMD) paradigm, which requires tight coupling across accelerators. Due to this co…
Latent Space Communication via K-V Cache Alignment
Lucio M. Dery, Zohar Yahav, Henry Prior +3
Solving increasingly complex problems with large language models (LLMs) necessitates a move beyond individual models and towards multi-model systems that can effectively collaborat…
Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Gheorghe Comanici, Eric Bieber, Mike Schaekermann +3431
In this report, we introduce the Gemini 2.X model family: Gemini 2.5 Pro and Gemini 2.5 Flash, as well as our earlier Gemini 2.0 Flash and Flash-Lite models. Gemini 2.5 Pro is our…
Communication-Efficient Language Model Training Scales Reliably and Robustly: Scaling Laws for DiLoCo
Zachary Charles, Gabriel Teston, Lucio Dery +5
As we scale to more massive machine learning models, the frequent synchronization demands inherent in data-parallel approaches create significant slowdowns, posing a critical chall…