6 citations · 9 across the 9 of their papers we have counts for
9 papers
Rubric-Grounded RL: Structured Judge Rewards for Generalizable Reasoning
Manish Bhattarai, Ismael Boureima, Nishath Rajiv Ranasinghe +2
We argue that decomposing reward into weighted, verifiable criteria and using an LLM judge to score them provides a partial-credit optimization signal: instead of a binary outcome…
Enhancing Cross-Language Code Translation via Task-Specific Embedding Alignment in Retrieval-Augmented Generation
Manish Bhattarai, Minh Vu, Javier E. Santos +2
We introduce a novel method to enhance cross-language code translation from Fortran to C++ by integrating task-specific embedding alignment into a Retrieval-Augmented Generation (R…
HEAL: Hierarchical Embedding Alignment Loss for Improved Retrieval and Representation Learning
Manish Bhattarai, Ryan Barron, Maksim Eren +8
Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by integrating external document retrieval to provide domain-specific or up-to-date knowledge. The effect…
Tensor Train Low-rank Approximation (TT-LoRA): Democratizing AI with Accelerated LLMs
Afia Anjum, Maksim E. Eren, Ismael Boureima +2
In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of natural language processing (NLP) tasks, such as question-answering,…
Binary Bleed: Fast Distributed and Parallel Method for Automatic Model Selection
Ryan Barron, Maksim E. Eren, Manish Bhattarai +3
In several Machine Learning (ML) clustering and dimensionality reduction approaches, such as non-negative matrix factorization (NMF), RESCAL, and K-Means clustering, users must sel…
Tensor-Train WENO Scheme for Compressible Flows
Mustafa Engin Danis, Duc Truong, Ismael Boureima +3
In this study, we introduce a tensor-train (TT) finite difference WENO method for solving compressible Euler equations. In a step-by-step manner, the tensorization of the governing…
Tensor Networks for Solving Realistic Time-independent Boltzmann Neutron Transport Equation
Duc P. Truong, Mario I. Ortega, Ismael Boureima +3
Tensor network techniques, known for their low-rank approximation ability that breaks the curse of dimensionality, are emerging as a foundation of new mathematical methods for ultr…
Distributed Out-of-Memory SVD on CPU/GPU Architectures
Ismael Boureima, Manish Bhattarai, Maksim E. Eren +3
We propose an efficient, distributed, out-of-memory implementation of the truncated singular value decomposition (t-SVD) for heterogeneous (CPU+GPU) high performance computing (HPC…
Distributed Out-of-Memory NMF on CPU/GPU Architectures
Ismael Boureima, Manish Bhattarai, Maksim Eren +4
We propose an efficient distributed out-of-memory implementation of the Non-negative Matrix Factorization (NMF) algorithm for heterogeneous high-performance-computing (HPC) systems…