25 citations · 36 across the 13 of their papers we have counts for
14 papers
Mitigating Task-Order Sensitivity and Forgetting via Hierarchical Second-Order Consolidation
Protik Nag, Krishnan Raghavan, Vignesh Narayanan
We introduce , a framework that couples fast local adaptation with conservative, second-order global consolidat…
Multi-Objective Multi-Fidelity Bayesian Optimization with Causal Priors
Md Abir Hossen, Mohammad Ali Javidian, Vignesh Narayanan +2
Multi-fidelity Bayesian optimization (MFBO) accelerates the search for the global optimum of black-box functions by integrating inexpensive, low-fidelity approximations. The centra…
Towards Information-Optimized Multi-Agent Path Finding: A Hybrid Framework with Reduced Inter-Agent Information Sharing
Bharath Muppasani, Ritirupa Dey, Biplav Srivastava +1
Multi-agent pathfinding (MAPF) remains a critical problem in robotics and autonomous systems, where agents must navigate shared spaces efficiently while avoiding conflicts. Traditi…
Towards Effective Planning Strategies for Dynamic Opinion Networks
Bharath Muppasani, Protik Nag, Vignesh Narayanan +2
In this study, we investigate the under-explored intervention planning aimed at disseminating accurate information within dynamic opinion networks by leveraging learning strategies…
Evaluating Chatbots to Promote Users' Trust -- Practices and Open Problems
Biplav Srivastava, Kausik Lakkaraju, Tarmo Koppel +3
Chatbots, the common moniker for collaborative assistants, are Artificial Intelligence (AI) software that enables people to naturally interact with them to get tasks done. Although…
A Planning Ontology to Represent and Exploit Planning Knowledge for Performance Efficiency
Bharath Muppasani, Vishal Pallagani, Biplav Srivastava +3
Ontologies are known for their ability to organize rich metadata, support the identification of novel insights via semantic queries, and promote reuse. In this paper, we consider t…
IERL: Interpretable Ensemble Representation Learning -- Combining CrowdSourced Knowledge and Distributed Semantic Representations
Yuxin Zi, Kaushik Roy, Vignesh Narayanan +2
Large Language Models (LLMs) encode meanings of words in the form of distributed semantics. Distributed semantics capture common statistical patterns among language tokens (words,…
Knowledge-Infused Self Attention Transformers
Kaushik Roy, Yuxin Zi, Vignesh Narayanan +2
Transformer-based language models have achieved impressive success in various natural language processing tasks due to their ability to capture complex dependencies and contextual…
Process Knowledge-infused Learning for Clinician-friendly Explanations
Kaushik Roy, Yuxin Zi, Manas Gaur +4
Language models have the potential to assess mental health using social media data. By analyzing online posts and conversations, these models can detect patterns indicating mental…
Cook-Gen: Robust Generative Modeling of Cooking Actions from Recipes
Revathy Venkataramanan, Kaushik Roy, Kanak Raj +4
As people become more aware of their food choices, food computation models have become increasingly popular in assisting people in maintaining healthy eating habits. For example, f…
Knowledge Graph Guided Semantic Evaluation of Language Models For User Trust
Kaushik Roy, Tarun Garg, Vedant Palit +3
A fundamental question in natural language processing is - what kind of language structure and semantics is the language model capturing? Graph formats such as knowledge graphs are…
On Safe and Usable Chatbots for Promoting Voter Participation
Bharath Muppasani, Vishal Pallagani, Kausik Lakkaraju +5
Chatbots, or bots for short, are multi-modal collaborative assistants that can help people complete useful tasks. Usually, when chatbots are referenced in connection with elections…
KSAT: Knowledge-infused Self Attention Transformer -- Integrating Multiple Domain-Specific Contexts
Kaushik Roy, Yuxin Zi, Vignesh Narayanan +2
Domain-specific language understanding requires integrating multiple pieces of relevant contextual information. For example, we see both suicide and depression-related behavior (mu…
Learning to Automate Follow-up Question Generation using Process Knowledge for Depression Triage on Reddit Posts
Shrey Gupta, Anmol Agarwal, Manas Gaur +4
Conversational Agents (CAs) powered with deep language models (DLMs) have shown tremendous promise in the domain of mental health. Prominently, the CAs have been used to provide in…