4 citations · 4 across the 10 of their papers we have counts for
10 papers
Metag: A dataset to build agentic meta-reviewing capabilities
Anirudh Sundar, Min Chen, Divya Tadimeti +11
AI tools increasingly support tasks across the scientific research cycle, from experiment design and manuscript preparation to peer review. At the same time, the continuing growth…
FLEx: Language Modeling with Few-shot Language Explanations
Adar Avsian, Christopher Richardson, Anirudh Sundar +1
Language models have become effective at a wide range of tasks, from math problem solving to open-domain question answering. However, they still make mistakes, and these mistakes a…
Schema Augmentation for Zero-Shot Domain Adaptation in Dialogue State Tracking
Christopher Richardson, Roshan Sharma, Neeraj Gaur +3
Zero-shot domain adaptation for dialogue state tracking (DST) remains a challenging problem in task-oriented dialogue (TOD) systems, where models must generalize to target domains…
cPAPERS: A Dataset of Situated and Multimodal Interactive Conversations in Scientific Papers
Anirudh Sundar, Jin Xu, William Gay +2
An emerging area of research in situated and multimodal interactive conversations (SIMMC) includes interactions in scientific papers. Since scientific papers are primarily composed…
iTBLS: A Dataset of Interactive Conversations Over Tabular Information
Anirudh Sundar, Christopher Richardson, Adar Avsian +1
This paper introduces Interactive Tables (iTBLS), a dataset of interactive conversations that focuses on natural-language manipulation of tabular information sourced from academic…
gTBLS: Generating Tables from Text by Conditional Question Answering
Anirudh Sundar, Christopher Richardson, Larry Heck
Distilling large, unstructured text into a structured, condensed form such as tables is an open research problem. One of the primary challenges in automatically generating tables i…
Multimodal Attention Merging for Improved Speech Recognition and Audio Event Classification
Anirudh S. Sundar, Chao-Han Huck Yang, David M. Chan +3
Training large foundation models using self-supervised objectives on unlabeled data, followed by fine-tuning on downstream tasks, has emerged as a standard procedure. Unfortunately…
SYNDICOM: Improving Conversational Commonsense with Error-Injection and Natural Language Feedback
Christopher Richardson, Anirudh Sundar, Larry Heck
Commonsense reasoning is a critical aspect of human communication. Despite recent advances in conversational AI driven by large language models, commonsense reasoning remains a cha…
cTBLS: Augmenting Large Language Models with Conversational Tables
Anirudh S Sundar, Larry Heck
Optimizing accuracy and performance while eliminating hallucinations of open-domain conversational large language models (LLMs) is an open research challenge. A particularly promis…
Multimodal Conversational AI: A Survey of Datasets and Approaches
Anirudh Sundar, Larry Heck
As humans, we experience the world with all our senses or modalities (sound, sight, touch, smell, and taste). We use these modalities, particularly sight and touch, to convey and i…