2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CL2025
SpecAttn: Speculating Sparse Attention
Harsh Shah
Large Language Models (LLMs) face significant computational bottlenecks during inference due to the quadratic complexity of self-attention mechanisms, particularly as context lengt…
cs.LG2025
Parameters vs FLOPs: Scaling Laws for Optimal Sparsity for Mixture-of-Experts Language Models
Samira Abnar, Harshay Shah, Dan Busbridge +3
Scaling the capacity of language models has consistently proven to be a reliable approach for improving performance and unlocking new capabilities. Capacity can be primarily define…
cs.IR2020★ 2 cited
Detecting Problem Statements in Peer Assessments
Yunkai Xiao, Gabriel Zingle, Qinjin Jia +12
Effective peer assessment requires students to be attentive to the deficiencies in the work they rate. Thus, their reviews should identify problems. But what ways are there to chec…