2 citations · 3 across the 7 of their papers we have counts for
8 papers
MosaicLeaks:Privacy Risks in Querying-in-the-Open for Deep Research Agents
Alexander Gurung, Spandana Gella, Alexandre Drouin +3
Deep research agents increasingly combine private local documents with external tools like web retrieval, creating a privacy risk: an agent's external queries may leak sensitive in…
Super Apriel: One Checkpoint, Many Speeds
SLAM Labs, :, Oleksiy Ostapenko +13
We release Super Apriel, a 15B-parameter supernet in which every decoder layer provides four trained mixer choices -- Full Attention (FA), Sliding Window Attention (SWA), Kimi Delt…
Apriel-Reasoner: RL Post-Training for General-Purpose and Efficient Reasoning
Rafael Pardinas, Ehsan Kamalloo, David Vazquez +1
Building general-purpose reasoning models using reinforcement learning with verifiable rewards (RLVR) across diverse domains has been widely adopted by frontier open-weight models.…
PipelineRL: Faster On-policy Reinforcement Learning for Long Sequence Generation
Alexandre Piché, Ehsan Kamalloo, Rafael Pardinas +2
Reinforcement Learning (RL) is increasingly utilized to enhance the reasoning capabilities of Large Language Models (LLMs). However, effectively scaling these RL methods presents s…
TapeAgents: a Holistic Framework for Agent Development and Optimization
Dzmitry Bahdanau, Nicolas Gontier, Gabriel Huang +10
We present TapeAgents, an agent framework built around a granular, structured log tape of the agent session that also plays the role of the session's resumable state. In TapeAgents…
Implicit Offline Reinforcement Learning via Supervised Learning
Alexandre Piche, Rafael Pardinas, David Vazquez +2
Offline Reinforcement Learning (RL) via Supervised Learning is a simple and effective way to learn robotic skills from a dataset collected by policies of different expertise levels…