7 papers
Multimodal Diffusion to Mutually Enhance Polarized Light and Low Resolution EBSD Data
Harry Dong, Timofey Efimov, Megna Shah +4
In spite of the utility of 3-D electron back-scattered diffraction (EBSD) microscopy, the data collection process can be time-consuming with serial-sectioning. Hence, it is natural…
STEM: Scaling Transformers with Embedding Modules
Ranajoy Sadhukhan, Sheng Cao, Harry Dong +5
Fine-grained sparsity promises higher parametric capacity without proportional per-token compute, but often suffers from training instability, load balancing, and communication ove…
Generalized Parallel Scaling with Interdependent Generations
Harry Dong, David Brandfonbrener, Eryk Helenowski +5
Parallel LLM inference scaling involves sampling a set of responses for a single input prompt. However, these parallel responses tend to be generated independently from e…
Scalable LLM Reasoning Acceleration with Low-rank Distillation
Harry Dong, Bilge Acun, Beidi Chen +1
Due to long generations, large language model (LLM) math reasoning demands significant computational resources and time. While many existing efficient inference methods have been d…
Towards Low-bit Communication for Tensor Parallel LLM Inference
Harry Dong, Tyler Johnson, Minsik Cho +1
Tensor parallelism provides an effective way to increase server large language model (LLM) inference efficiency despite adding an additional communication cost. However, as server…
Leveraging Multimodal Diffusion Models to Accelerate Imaging with Side Information
Timofey Efimov, Harry Dong, Megna Shah +3
Diffusion models have found phenomenal success as expressive priors for solving inverse problems, but their extension beyond natural images to more structured scientific domains re…