28 citations · 86 across the 24 of their papers we have counts for
27 papers
Thoughts without Thinking: Reconsidering the Explanatory Value of Chain-of-Thought Reasoning in LLMs through Agentic Pipelines
Ramesh Manuvinakurike, Emanuel Moss, Elizabeth Anne Watkins +3
Agentic pipelines present novel challenges and opportunities for human-centered explainability. The HCXAI community is still grappling with how best to make the inner workings of L…
What's So Human about Human-AI Collaboration, Anyway? Generative AI and Human-Computer Interaction
Elizabeth Anne Watkins, Emanuel Moss, Giuseppe Raffa +1
While human-AI collaboration has been a longstanding goal and topic of study for computational research, the emergence of increasingly naturalistic generative AI language models ha…
QA-TOOLBOX: Conversational Question-Answering for process task guidance in manufacturing
Ramesh Manuvinakurike, Elizabeth Watkins, Celal Savur +7
In this work we explore utilizing LLMs for data augmentation for manufacturing task guidance system. The dataset consists of representative samples of interactions with technicians…
Decoding Biases: Automated Methods and LLM Judges for Gender Bias Detection in Language Models
Shachi H Kumar, Saurav Sahay, Sahisnu Mazumder +6
Large Language Models (LLMs) have excelled at language understanding and generating human-level text. However, even with supervised training and human alignment, these LLMs are sus…
Introducing v0.5 of the AI Safety Benchmark from MLCommons
Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed +97
This paper introduces v0.5 of the AI Safety Benchmark, which has been created by the MLCommons AI Safety Working Group. The AI Safety Benchmark has been designed to assess the safe…
Zero-shot Conversational Summarization Evaluations with small Large Language Models
Ramesh Manuvinakurike, Saurav Sahay, Sangeeta Manepalli +1
Large Language Models (LLMs) exhibit powerful summarization abilities. However, their capabilities on conversational summarization remains under explored. In this work we evaluate…
Inspecting Spoken Language Understanding from Kids for Basic Math Learning at Home
Eda Okur, Roddy Fuentes Alba, Saurav Sahay +1
Enriching the quality of early childhood education with interactive math learning at home systems, empowered by recent advances in conversational AI technologies, is slowly becomin…
Position Matters! Empirical Study of Order Effect in Knowledge-grounded Dialogue
Hsuan Su, Shachi H Kumar, Sahisnu Mazumder +7
With the power of large pretrained language models, various research works have integrated knowledge into dialogue systems. The traditional techniques treat knowledge as part of th…
End-to-End Evaluation of a Spoken Dialogue System for Learning Basic Mathematics
Eda Okur, Saurav Sahay, Roddy Fuentes Alba +1
The advances in language-based Artificial Intelligence (AI) technologies applied to build educational applications can present AI for social-good opportunities with a broader posit…
Human in the loop approaches in multi-modal conversational task guidance system development
Ramesh Manuvinakurike, Sovan Biswas, Giuseppe Raffa +6
Development of task guidance systems for aiding humans in a situated task remains a challenging problem. The role of search (information retrieval) and conversational systems for t…
NLU for Game-based Learning in Real: Initial Evaluations
Eda Okur, Saurav Sahay, Lama Nachman
Intelligent systems designed for play-based interactions should be contextually aware of the users and their surroundings. Spoken Dialogue Systems (SDS) are critical for these inte…
Intuitive and Efficient Human-robot Collaboration via Real-time Approximate Bayesian Inference
Javier Felip Leon, David Gonzalez-Aguirre, Lama Nachman
The combination of collaborative robots and end-to-end AI, promises flexible automation of human tasks in factories and warehouses. However, such promise seems a few breakthroughs…
Data Augmentation with Paraphrase Generation and Entity Extraction for Multimodal Dialogue System
Eda Okur, Saurav Sahay, Lama Nachman
Contextually aware intelligent agents are often required to understand the users and their surroundings in real-time. Our goal is to build Artificial Intelligence (AI) systems that…
Controllable Response Generation for Assistive Use-cases
Shachi H Kumar, Hsuan Su, Ramesh Manuvinakurike +2
Conversational agents have become an integral part of the general population for simple task enabling situations. However, these systems are yet to have any social impact on the di…
Semi-supervised Interactive Intent Labeling
Saurav Sahay, Eda Okur, Nagib Hakim +1
Building the Natural Language Understanding (NLU) modules of task-oriented Spoken Dialogue Systems (SDS) involves a definition of intents and entities, collection of task-relevant…
Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty
Umang Bhatt, Javier Antorán, Yunfeng Zhang +12
Algorithmic transparency entails exposing system properties to various stakeholders for purposes that include understanding, improving, and contesting predictions. Until now, most…
Audio-Visual Understanding of Passenger Intents for In-Cabin Conversational Agents
Eda Okur, Shachi H Kumar, Saurav Sahay +1
Building multimodal dialogue understanding capabilities situated in the in-cabin context is crucial to enhance passenger comfort in autonomous vehicle (AV) interaction systems. To…
Low Rank Fusion based Transformers for Multimodal Sequences
Saurav Sahay, Eda Okur, Shachi H Kumar +1
Our senses individually work in a coordinated fashion to express our emotional intentions. In this work, we experiment with modeling modality-specific sensory signals to attend to…
Optimizing User Interface Layouts via Gradient Descent
Peitong Duan, Casimir Wierzynski, Lama Nachman
Automating parts of the user interface (UI) design process has been a longstanding challenge. We present an automated technique for optimizing the layouts of mobile UIs. Our method…
Exploring Context, Attention and Audio Features for Audio Visual Scene-Aware Dialog
Shachi H Kumar, Eda Okur, Saurav Sahay +2
We are witnessing a confluence of vision, speech and dialog system technologies that are enabling the IVAs to learn audio-visual groundings of utterances and have conversations wit…
Leveraging Topics and Audio Features with Multimodal Attention for Audio Visual Scene-Aware Dialog
Shachi H Kumar, Eda Okur, Saurav Sahay +2
With the recent advancements in Artificial Intelligence (AI), Intelligent Virtual Assistants (IVA) such as Alexa, Google Home, etc., have become a ubiquitous part of many homes. Cu…
Modeling Intent, Dialog Policies and Response Adaptation for Goal-Oriented Interactions
Saurav Sahay, Shachi H Kumar, Eda Okur +2
Building a machine learning driven spoken dialog system for goal-oriented interactions involves careful design of intents and data collection along with development of intent recog…
Towards Multimodal Understanding of Passenger-Vehicle Interactions in Autonomous Vehicles: Intent/Slot Recognition Utilizing Audio-Visual Data
Eda Okur, Shachi H Kumar, Saurav Sahay +1
Understanding passenger intents from spoken interactions and car's vision (both inside and outside the vehicle) are important building blocks towards developing contextual dialog s…
Natural Language Interactions in Autonomous Vehicles: Intent Detection and Slot Filling from Passenger Utterances
Eda Okur, Shachi H Kumar, Saurav Sahay +2
Understanding passenger intents and extracting relevant slots are important building blocks towards developing contextual dialogue systems for natural interactions in autonomous ve…