41 citations · 131 across the 14 of their papers we have counts for
14 papers
FANTAstic SEquences and Where to Find Them: Faithful and Efficient API Call Generation through State-tracked Constrained Decoding and Reranking
Zhuoer Wang, Leonardo F. R. Ribeiro, Alexandros Papangelis +6
API call generation is the cornerstone of large language models' tool-using ability that provides access to the larger world. However, existing supervised and in-context learning a…
Multi-User MultiWOZ: Task-Oriented Dialogues among Multiple Users
Yohan Jo, Xinyan Zhao, Arijit Biswas +5
While most task-oriented dialogues assume conversations between the agent and one user at a time, dialogue systems are increasingly expected to communicate with multiple users simu…
Toward More Accurate and Generalizable Evaluation Metrics for Task-Oriented Dialogs
Abishek Komma, Nagesh Panyam Chandrasekarasastry, Timothy Leffel +4
Measurement of interaction quality is a critical task for the improvement of spoken dialog systems. Existing approaches to dialog quality estimation either focus on evaluating the…
Alexa Conversations: An Extensible Data-driven Approach for Building Task-oriented Dialogue Systems
Anish Acharya, Suranjit Adhikari, Sanchit Agarwal +28
Traditional goal-oriented dialogue systems rely on various components such as natural language understanding, dialogue state tracking, policy learning and response generation. Trai…
Dialog Simulation with Realistic Variations for Training Goal-Oriented Conversational Systems
Chien-Wei Lin, Vincent Auvray, Daniel Elkind +10
Goal-oriented dialog systems enable users to complete specific goals like requesting information about a movie or booking a ticket. Typically the dialog system pipeline contains mu…
MA-DST: Multi-Attention Based Scalable Dialog State Tracking
Adarsh Kumar, Peter Ku, Anuj Kumar Goyal +2
Task oriented dialog agents provide a natural language interface for users to complete their goal. Dialog State Tracking (DST), which is often a core component of these systems, tr…
Controlled Text Generation for Data Augmentation in Intelligent Artificial Agents
Nikolaos Malandrakis, Minmin Shen, Anuj Goyal +3
Data availability is a bottleneck during early stages of development of new capabilities for intelligent artificial agents. We investigate the use of text generation techniques to…
Simple Question Answering with Subgraph Ranking and Joint-Scoring
Wenbo Zhao, Tagyoung Chung, Anuj Goyal +1
Knowledge graph based simple question answering (KBSQA) is a major area of research within question answering. Although only dealing with simple questions, i.e., questions that can…
Unsupervised Transfer Learning for Spoken Language Understanding in Intelligent Agents
Aditya Siddhant, Anuj Goyal, Angeliki Metallinou
User interaction with voice-powered agents generates large amounts of unlabeled utterances. In this paper, we explore techniques to efficiently transfer the knowledge from these un…
Online Embedding Compression for Text Classification using Low Rank Matrix Factorization
Anish Acharya, Rahul Goel, Angeliki Metallinou +1
Deep learning models have become state of the art for natural language processing (NLP) tasks, however deploying these models in production system poses significant memory constrai…
Contextual Language Model Adaptation for Conversational Agents
Anirudh Raju, Behnam Hedayatnia, Linda Liu +5
Statistical language models (LM) play a key role in Automatic Speech Recognition (ASR) systems used by conversational agents. These ASR systems should provide a high accuracy under…
Fast and Scalable Expansion of Natural Language Understanding Functionality for Intelligent Agents
Anuj Goyal, Angeliki Metallinou, Spyros Matsoukas
Fast expansion of natural language functionality of intelligent virtual agents is critical for achieving engaging and informative interactions. However, developing accurate models…
Topic-based Evaluation for Conversational Bots
Fenfei Guo, Angeliki Metallinou, Chandra Khatri +3
Dialog evaluation is a challenging problem, especially for non task-oriented dialogs where conversational success is not well-defined. We propose to evaluate dialog quality using t…
On Evaluating and Comparing Open Domain Dialog Systems
Anu Venkatesh, Chandra Khatri, Ashwin Ram +10
Conversational agents are exploding in popularity. However, much work remains in the area of non goal-oriented conversations, despite significant growth in research interest over r…