22 citations · 44 across the 14 of their papers we have counts for
16 papers
Uncertainty principles as forcing mechanisms
Laurent Massoulié
In this note we first consider the Heisenberg uncertainty principle. We show that it acts as a {\bf forcing mechanism} in the following sense. Real functions that approach its limi…
Nemotron 3 Ultra: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
NVIDIA, :, Aaron Blakeman +572
We introduce Nemotron 3 Ultra, a 550 billion total and 55 billion active parameter Mixture-of-Experts Hybrid Mamba-Attention language model. We pre-trained Nemotron 3 Ultra on 20 t…
Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
NVIDIA, :, Aakshita Chandiramani +544
We describe the pre-training, post-training, and quantization of Nemotron 3 Super, a 120 billion (active 12 billion) parameter hybrid Mamba-Attention Mixture-of-Experts model. Nemo…
Learning Without Critics? Revisiting GRPO in Classical Reinforcement Learning Environments
Bryan L. M. de Oliveira, Felipe V. Frujeri, Marcos P. C. M. Queiroz +3
Group Relative Policy Optimization (GRPO) has emerged as a scalable alternative to Proximal Policy Optimization (PPO) by eliminating the learned critic and instead estimating advan…
HoloAssist: an Egocentric Human Interaction Dataset for Interactive AI Assistants in the Real World
Xin Wang, Taein Kwon, Mahdi Rad +9
Building an interactive AI assistant that can perceive, reason, and collaborate with humans in the real world has been a long-standing pursuit in the AI community. This work is par…
ALLURE: Auditing and Improving LLM-based Evaluation of Text using Iterative In-Context-Learning
Hosein Hasanbeig, Hiteshi Sharma, Leo Betthauser +2
From grading papers to summarizing medical documents, large language models (LLMs) are evermore used for evaluation of text generated by humans and AI alike. However, despite their…
Evaluating Cognitive Maps and Planning in Large Language Models with CogEval
Ida Momennejad, Hosein Hasanbeig, Felipe Vieira +5
Recently an influx of studies claim emergent cognitive abilities in large language models (LLMs). Yet, most rely on anecdotes, overlook contamination of training sets, or lack syst…
Fine-Tuning Language Models with Advantage-Induced Policy Alignment
Banghua Zhu, Hiteshi Sharma, Felipe Vieira Frujeri +4
Reinforcement learning from human feedback (RLHF) has emerged as a reliable approach to aligning large language models (LLMs) to human preferences. Among the plethora of RLHF techn…
A Deep Learning Perspective on Network Routing
Yarin Perry, Felipe Vieira Frujeri, Chaim Hoch +4
Routing is, arguably, the most fundamental task in computer networking, and the most extensively studied one. A key challenge for routing in real-world environments is the need to…
Towards Data-Driven Offline Simulations for Online Reinforcement Learning
Shengpu Tang, Felipe Vieira Frujeri, Dipendra Misra +4
Modern decision-making systems, from robots to web recommendation engines, are expected to adapt: to user preferences, changing circumstances or even new tasks. Yet, it is still un…
PACT: Perception-Action Causal Transformer for Autoregressive Robotics Pre-Training
Rogerio Bonatti, Sai Vemprala, Shuang Ma +3
Robotics has long been a field riddled with complex systems architectures whose modules and connections, whether traditional or learning-based, require significant human expertise…
MoCapAct: A Multi-Task Dataset for Simulated Humanoid Control
Nolan Wagener, Andrey Kolobov, Felipe Vieira Frujeri +3
Simulated humanoids are an appealing research domain due to their physical capabilities. Nonetheless, they are also challenging to control, as a policy must drive an unstable, disc…
Hindsight Learning for MDPs with Exogenous Inputs
Sean R. Sinclair, Felipe Frujeri, Ching-An Cheng +6
Many resource management problems require sequential decision-making under uncertainty, where the only uncertainty affecting the decision outcomes are exogenous variables outside t…
The Sandbox Environment for Generalizable Agent Research (SEGAR)
R Devon Hjelm, Bogdan Mazoure, Florian Golemo +5
A broad challenge of research on generalization for sequential decision-making tasks in interactive environments is designing benchmarks that clearly landmark progress. While there…
Towards a Cost vs. Quality Sweet Spot for Monitoring Networks
Nofel Yaseen, Behnaz Arzani, Krishna Chintalapudi +6
Continuously monitoring a wide variety of performance and fault metrics has become a crucial part of operating large-scale datacenter networks. In this work, we ask whether we can…
Prediction-Based Power Oversubscription in Cloud Platforms
Alok Kumbhare, Reza Azimi, Ioannis Manousakis +8
Datacenter designers rely on conservative estimates of IT equipment power draw to provision resources. This leaves resources underutilized and requires more datacenters to be built…