3 papers
cs.AI2026
MHA-RAG: Improving Efficiency, Accuracy, and Consistency by Encoding Exemplars as Soft Prompts
Abhinav Jain, Xinyu Yao, Thomas Reps +1
Adapting Foundation Models to new domains with limited training data is challenging and computationally expensive. While prior work has demonstrated the effectiveness of using doma…
cs.LG2026
DOPPLER: Dual-Policy Learning for Device Assignment in Asynchronous Dataflow Graphs
Xinyu Yao, Daniel Bourgeois, Abhinav Jain +5
We study the problem of assigning operations in a dataflow graph to devices to minimize execution time in a work-conserving system, with emphasis on complex machine learning worklo…
cs.MS2026
Automated Tensor-Relational Decomposition for Large-Scale Sparse Tensor Computation
Yuxin Tang, Zhiyuan Xin, Zhimin Ding +4
A \emph{tensor-relational} computation is a relational computation where individual tuples carry vectors, matrices, or higher-dimensional arrays. An advantage of tensor-relational…