1 citations · 2 across the 13 of their papers we have counts for
14 papers
Lighthouse: On Building a Trustworthy Digital Assistant for Exploring History with Civil Rights Archives
John A. Aydin, Angelica Williams, Steven Dindl +4
Artificial intelligence (AI), as a decision-support aid, provides new tools for studying history effectively using multimodal data, including text, images, and audio. We present, t…
Eliot: Interactively xploring Fast-Changing Scientific terature Trends with nline Daa and Learning
Bernardo A. Denkvitts, Nitin Gupta, Biplav Srivastava
The rapid growth of scientific publishing has made it increasingly difficult to track how fast-moving areas evolve. Search engines and LLM-based assistants retrieve or summarize pa…
On Sample-Efficient Generalized Planning via Learned Transition Models
Nitin Gupta, Vishal Pallagani, John A. Aydin +1
Generalized planning studies the construction of solution strategies that generalize across families of planning problems sharing a common domain model, formally defined by a trans…
On Identifying Why and When Foundation Models Perform Well on Time-Series Forecasting Using Automated Explanations and Rating
Michael Widener, Kausik Lakkaraju, John Aydin +1
Time-series forecasting models (TSFM) have evolved from classical statistical methods to sophisticated foundation models, yet understanding why and when these models succeed or fai…
GAICo: A Deployed and Extensible Framework for Evaluating Diverse and Multimodal Generative AI Outputs
Nitin Gupta, Pallav Koppisetti, Kausik Lakkaraju +1
The rapid proliferation of Generative AI (GenAI) into diverse, high-stakes domains necessitates robust and reproducible evaluation methods. However, practitioners often resort to a…
Holistic Explainable AI (H-XAI): Extending Transparency Beyond Developers in AI-Driven Decision Making
Kausik Lakkaraju, Siva Likitha Valluru, Biplav Srivastava
As AI systems increasingly mediate decisions in domains such as credit scoring and financial forecasting, their lack of transparency and bias raises critical concerns for fairness…
FABLE: A Novel Data-Flow Analysis Benchmark on Procedural Text for Large Language Model Evaluation
Vishal Pallagani, Nitin Gupta, John Aydin +1
Understanding how data moves, transforms, and persists, known as data flow, is fundamental to reasoning in procedural tasks. Despite their fluency in natural and programming langua…
SafeChat: A Framework for Building Trustworthy Collaborative Assistants and a Case Study of its Usefulness
Biplav Srivastava, Kausik Lakkaraju, Nitin Gupta +3
Collaborative assistants, or chatbots, are data-driven decision support systems that enable natural interaction for task completion. While they can meet critical needs in modern so…
Creating a Causally Grounded Rating Method for Assessing the Robustness of AI Models for Time-Series Forecasting
Kausik Lakkaraju, Rachneet Kaur, Parisa Zehtabi +5
AI models, including both time-series-specific and general-purpose Foundation Models (FMs), have demonstrated strong potential in time-series forecasting across sectors like financ…
A Novel Approach to Balance Convenience and Nutrition in Meals With Long-Term Group Recommendations and Reasoning on Multimodal Recipes and its Implementation in BEACON
Vansh Nagpal, Siva Likitha Valluru, Kausik Lakkaraju +4
A common decision made by people, whether healthy or with health conditions, is choosing meals like breakfast, lunch, and dinner, comprising combinations of foods for appetizer, ma…
BEACON: Balancing Convenience and Nutrition in Meals With Long-Term Group Recommendations and Reasoning on Multimodal Recipes
Vansh Nagpal, Siva Likitha Valluru, Kausik Lakkaraju +1
A common, yet regular, decision made by people, whether healthy or with any health condition, is to decide what to have in meals like breakfast, lunch, and dinner, consisting of a…
Rating Multi-Modal Time-Series Forecasting Models (MM-TSFM) for Robustness Through a Causal Lens
Kausik Lakkaraju, Rachneet Kaur, Zhen Zeng +4
AI systems are notorious for their fragility; minor input changes can potentially cause major output swings. When such systems are deployed in critical areas like finance, the cons…
On Learning with LAD
C. A. Jothishwaran, Biplav Srivastava, Jitin Singla +1
The logical analysis of data, LAD, is a technique that yields two-class classifiers based on Boolean functions having disjunctive normal form (DNF) representation. Although LAD alg…
Promoting Research Collaboration with Open Data Driven Team Recommendation in Response to Call for Proposals
Siva Likitha Valluru, Biplav Srivastava, Sai Teja Paladi +2
Building teams and promoting collaboration are two very common business activities. An example of these are seen in the TeamingForFunding problem, where research institutions and r…