公开(公告)号：US20240062079A1

公开(公告)日：2024-02-22

申请号：US18448369

申请日：2023-08-11

Applicant: UNIVERSITY OF SOUTH CAROLINA

Inventor： BIPLAV SRIVASTAVA ,  KAUSIK LAKKARAJU ,  MARCO VALTORTA

IPC: G06N5/022

CPC classification number: G06N5/022

Abstract: A method and system relates to assigning ratings (i.e., labels) to convey the trustability of AI systems grounded in its cause-and-effect behavior of significant inputs and outputs of the AI. Sentiment Analysis Systems (SASs) are data-driven Artificial Intelligence (AI) systems that, given a piece of text, assign a score conveying the sentiment and emotion intensity. The present disclosure uses the approach that protected attributes like gender and race influence the output (sentiment) given by SASs or if the sentiment is based on other components of the textual input, e.g., chosen emotion words. The presently disclosed rating methodology assigns ratings at fine-grained and overall levels, to rate SASs grounded in a causal setup, and provides an open-source implementation of both SASs—two deep-learning based, one lexicon-based, and two custom-built models—for this rating implementation. This allows users to understand the behavior of SAS in real-world applications.

公开(公告)号：US20240086394A1

公开(公告)日：2024-03-14

申请号：US18455730

申请日：2023-08-25

Applicant: UNIVERSITY OF SOUTH CAROLINA

Inventor： BIPLAV SRIVASTAVA ,  VISHAL PALLAGANI ,  REVATHY CHANDRASEKARAN VENKA ,  VEDANT KHANDELWAL ,  KAUSIK LAKKARAJU

IPC: G06F16/23 ,  G06F16/2453 ,  G06F16/2457

CPC classification number: G06F16/2365 ,  G06F16/2453 ,  G06F16/2457

Abstract: The disclosure deals with a system and method for improved representation and retrieval of recipes or workflows. Recipes or workflows such as for preparing food or assembling furniture or performing other complex activities exist as textual or image documents, which makes it difficult for machines to read, reason, and handle ambiguity. The present disclosure provides a Rich Recipe Representation (“R3”), which is enhanced with additional knowledge such as outcomes like allergen information, possible failures, and solutions for each atomic step (such as a cooking step). The disclosed R3 is used in a web-based decision support system that helps users perform constrained queries using multiple modalities while also monitoring execution of an agent cooking or otherwise acting based on it.

公开(公告)号：US20220358922A1

公开(公告)日：2022-11-10

申请号：US17714508

申请日：2022-04-06

Applicant: UNIVERSITY OF SOUTH CAROLINA

Inventor： BIPLAV SRIVASTAVA ,  KAUSIK LAKKARAJU ,  REVATHY VENKATARAMANAN ,  VISHAL PALLAGANI ,  VEDANT KHANDELWAL ,  HONG YUNG YIP

IPC: G10L15/22 ,  G06F3/16 ,  G06F9/38

Abstract: The disclosure deals with a system and method for improved general task-oriented virtual assistants (VAs). The presently disclosed framework incorporates discovery of knowledge from online sources to accomplish tasks (open world), user-specific knowledge for personalization, and domain-specific knowledge for context adaptation to recommend and assist the users over procedural tasks such as cooking and Do-it-Yourself (DIY) tasks. The approach also focuses on content curation for fault-tolerant execution to ensure the end goal is reached despite common failures.