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20242026
most citedTrustworthy Agentic AI Requires Deterministic Architectural Boundaries

1 citations · 2 across the 12 of their papers we have counts for

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5 papers · 1 filter

cs.CV2024

Patchfinder: Leveraging Visual Language Models for Accurate Information Retrieval using Model Uncertainty

Roman Colman, Minh Vu, Manish Bhattarai +4

For decades, corporations and governments have relied on scanned documents to record vast amounts of information. However, extracting this information is a slow and tedious process…

cs.AI2024

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…

cs.IR2024★ 1 cited

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…

cs.LG2024

LoRID: Low-Rank Iterative Diffusion for Adversarial Purification

Geigh Zollicoffer, Minh Vu, Ben Nebgen +3

This work presents an information-theoretic examination of diffusion-based purification methods, the state-of-the-art adversarial defenses that utilize diffusion models to remove m…

cs.LG2024

LaFA: Latent Feature Attacks on Non-negative Matrix Factorization

Minh Vu, Ben Nebgen, Erik Skau +5

As Machine Learning (ML) applications rapidly grow, concerns about adversarial attacks compromising their reliability have gained significant attention. One unsupervised ML method…