71 citations · 407 across the 69 of their papers we have counts for
73 papers
One Frozen Simulator Is Not Enough: Simulator Collapse in Multi-Agent RL
Simon Yu, Nicholas Tomlin, Marwa Abdulhai +7
Multi-agent reinforcement learning for human-AI interaction typically relies on a single large language model to simulate user behavior. We show that this approach systematically f…
ProCUA-SFT Technical Report
Jaehun Jung, Ximing Lu, Brandon Cui +11
Training computer-use agents (CUAs) -- models that interact with graphical desktops through screenshots and keyboard/mouse actions -- requires large-scale, diverse trajectory data…
Zone of Proximal Policy Optimization: Teacher in Prompts, Not Gradients
Byung-Kwan Lee, Ximing Lu, Shizhe Diao +8
Knowledge distillation transfers a teacher's competence to a small student but is brittle in the small-student regime: forcing the student to imitate logits from a much larger teac…
Nemotron 3 Nano Omni: Efficient and Open Multimodal Intelligence
NVIDIA, :, Amala Sanjay Deshmukh +204
We introduce Nemotron 3 Nano Omni, the latest model in the Nemotron multimodal series and the first to natively support audio inputs alongside text, images, and video. Nemotron 3 N…
DeltaPrompts: Escaping the Zero-Delta Trap in Multimodal Distillation
Jaehun Jung, Hyunwoo Kim, Brandon Cui +4
Distillation enables compact Vision-Language Models (VLMs) to obtain strong reasoning capabilities, yet the prompts driving this process are typically chosen via simple heuristics…
iGRPO: Self-Feedback-Driven LLM Reasoning
Ali Hatamizadeh, Shrimai Prabhumoye, Igor Gitman +5
Large Language Models (LLMs) have shown promise in solving complex mathematical problems, yet they still fall short of producing accurate and consistent solutions. Reinforcement Le…