3 citations · 4 across the 22 of their papers we have counts for
7 papers · 1 filter
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…
Introspective X Training: Feedback Conditioning Improves Scaling Across all LLM Training Stages
Brandon Cui, Ximing Lu, Jaehun Jung +7
We tackle the question of how to scale more efficiently across the many, ever-growing stages of current LLM training pipelines. Our guiding intuition stems from the fact that the d…
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…
Synthetic Mixed Training: Scaling Parametric Knowledge Acquisition Beyond RAG
Seungju Han, Konwoo Kim, Chanwoo Park +5
Synthetic data augmentation helps language models learn new knowledge in data-constrained domains. However, naively scaling existing synthetic data methods by training on more synt…
Prismatic Synthesis: Gradient-based Data Diversification Boosts Generalization in LLM Reasoning
Jaehun Jung, Seungju Han, Ximing Lu +7
Effective generalization in language models depends critically on the diversity of their training data. Yet existing diversity metrics often fall short of this goal, relying on sur…
Trust or Escalate: LLM Judges with Provable Guarantees for Human Agreement
Jaehun Jung, Faeze Brahman, Yejin Choi
We present a principled approach to provide LLM-based evaluation with a rigorous guarantee of human agreement. We first propose that a reliable evaluation method should not uncriti…