1 citations · 1 across the 4 of their papers we have counts for
5 papers
Dion3: Full-Stack Orthogonal Updates
Noah Amsel, Jack Zhang, Kwangjun Ahn +5
The Muon optimizer incurs a significant overhead cost due to its cubic-time Newton-Schulz orthogonalization step. When weights are sharded, communication overhead compounds this co…
Mamba-3: Improved Sequence Modeling using State Space Principles
Aakash Lahoti, Kevin Y. Li, Berlin Chen +5
Scaling inference-time compute has emerged as an important driver of LLM performance, making inference efficiency a central focus of model design alongside model quality. While the…
Enhancing Speech Emotion Recognition Leveraging Aligning Timestamps of ASR Transcripts and Speaker Diarization
Hsuan-Yu Wang, Pei-Ying Lee, Berlin Chen
In this paper, we investigate the impact of incorporating timestamp-based alignment between Automatic Speech Recognition (ASR) transcripts and Speaker Diarization (SD) outputs on S…
Long-Context State-Space Video World Models
Ryan Po, Yotam Nitzan, Richard Zhang +5
Video diffusion models have recently shown promise for world modeling through autoregressive frame prediction conditioned on actions. However, they struggle to maintain long-term m…
Speech-Aware Neural Diarization with Encoder-Decoder Attractor Guided by Attention Constraints
PeiYing Lee, HauYun Guo, Berlin Chen
End-to-End Neural Diarization with Encoder-Decoder based Attractor (EEND-EDA) is an end-to-end neural model for automatic speaker segmentation and labeling. It achieves the capabil…