no code implementations • NAACL 2022 • Raghav Gupta, Harrison Lee, Jeffrey Zhao, Yuan Cao, Abhinav Rastogi, Yonghui Wu
Building universal dialogue systems that operate across multiple domains/APIs and generalize to new ones with minimal overhead is a critical challenge.
no code implementations • 13 Apr 2024 • Ayush Thakur, Raghav Gupta
The relentless pursuit of enhancing Large Language Models (LLMs) has led to the advent of Super Retrieval-Augmented Generation (Super RAGs), a novel approach designed to elevate the performance of LLMs by integrating external knowledge sources with minimal structural modifications.
no code implementations • 23 May 2023 • Raghav Gupta, Renat Aksitov, Samrat Phatale, Simral Chaudhary, Harrison Lee, Abhinav Rastogi
Conversational recommendation systems (CRS) aim to recommend suitable items to users through natural language conversation.
no code implementations • 20 Dec 2022 • Jeffrey Zhao, Yuan Cao, Raghav Gupta, Harrison Lee, Abhinav Rastogi, Mingqiu Wang, Hagen Soltau, Izhak Shafran, Yonghui Wu
We propose AnyTOD, an end-to-end, zero-shot task-oriented dialog (TOD) system capable of handling unseen tasks without task-specific training.
no code implementations • 8 Apr 2022 • Raghav Gupta, Harrison Lee, Jeffrey Zhao, Abhinav Rastogi, Yuan Cao, Yonghui Wu
Building universal dialogue systems that operate across multiple domains/APIs and generalize to new ones with minimal overhead is a critical challenge.
1 code implementation • 21 Jan 2022 • Jeffrey Zhao, Raghav Gupta, Yuan Cao, Dian Yu, Mingqiu Wang, Harrison Lee, Abhinav Rastogi, Izhak Shafran, Yonghui Wu
Task-oriented dialogue (TOD) systems are required to identify key information from conversations for the completion of given tasks.
1 code implementation • 13 Oct 2021 • Harrison Lee, Raghav Gupta, Abhinav Rastogi, Yuan Cao, Bin Zhang, Yonghui Wu
Zero/few-shot transfer to unseen services is a critical challenge in task-oriented dialogue research.
1 code implementation • 14 Dec 2020 • Raghav Gupta, P. K. Srijith, Shantanu Desai
We introduce a continuous depth version of the Residual Network (ResNet) called Neural ordinary differential equations (NODE) for the purpose of galaxy morphology classification.
Instrumentation and Methods for Astrophysics Astrophysics of Galaxies
1 code implementation • WS 2020 • Xiaoxue Zang, Abhinav Rastogi, Srinivas Sunkara, Raghav Gupta, Jian-Guo Zhang, Jindong Chen
We also benchmark a few state of the art dialogue state tracking models on the corrected dataset to facilitate comparison for future work.
no code implementations • 21 May 2020 • Manoj Kumar Kanakasabapathy, Prudhvi Thirumalaraju, Charles L Bormann, Raghav Gupta, Rohan Pooniwala, Hemanth Kandula, Irene Souter, Irene Dimitriadis, Hadi Shafiee
In conventional clinical in-vitro fertilization practices embryos are transferred either at the cleavage or blastocyst stages of development.
no code implementations • 21 May 2020 • Prudhvi Thirumalaraju, Manoj Kumar Kanakasabapathy, Charles L Bormann, Raghav Gupta, Rohan Pooniwala, Hemanth Kandula, Irene Souter, Irene Dimitriadis, Hadi Shafiee
A critical factor that influences the success of an in-vitro fertilization (IVF) procedure is the quality of the transferred embryo.
2 code implementations • 2 Feb 2020 • Abhinav Rastogi, Xiaoxue Zang, Srinivas Sunkara, Raghav Gupta, Pranav Khaitan
The goal of this task is to develop dialogue state tracking models suitable for large-scale virtual assistants, with a focus on data-efficient joint modeling across domains and zero-shot generalization to new APIs.
no code implementations • 14 Nov 2019 • Seokhwan Kim, Michel Galley, Chulaka Gunasekara, Sungjin Lee, Adam Atkinson, Baolin Peng, Hannes Schulz, Jianfeng Gao, Jinchao Li, Mahmoud Adada, Minlie Huang, Luis Lastras, Jonathan K. Kummerfeld, Walter S. Lasecki, Chiori Hori, Anoop Cherian, Tim K. Marks, Abhinav Rastogi, Xiaoxue Zang, Srinivas Sunkara, Raghav Gupta
This paper introduces the Eighth Dialog System Technology Challenge.
no code implementations • EACL 2021 • Sanqiang Zhao, Raghav Gupta, Yang song, Denny Zhou
Pretrained language models like BERT have achieved good results on NLP tasks, but are impractical on resource-limited devices due to memory footprint.
4 code implementations • 12 Sep 2019 • Abhinav Rastogi, Xiaoxue Zang, Srinivas Sunkara, Raghav Gupta, Pranav Khaitan
In this work, we introduce the the Schema-Guided Dialogue (SGD) dataset, containing over 16k multi-domain conversations spanning 16 domains.
1 code implementation • ACL 2019 • Darsh J Shah, Raghav Gupta, Amir A Fayazi, Dilek Hakkani-Tur
Task-oriented dialog systems increasingly rely on deep learning-based slot filling models, usually needing extensive labeled training data for target domains.
no code implementations • WS 2018 • Abhinav Rastogi, Raghav Gupta, Dilek Hakkani-Tur
This paper presents a novel approach for multi-task learning of language understanding (LU) and dialogue state tracking (DST) in task-oriented dialogue systems.
no code implementations • 1 Jul 2018 • Raghav Gupta, Abhinav Rastogi, Dilek Hakkani-Tur
In task-oriented dialogue systems, spoken language understanding, or SLU, refers to the task of parsing natural language user utterances into semantic frames.
3 code implementations • ACL 2016 • Samuel R. Bowman, Jon Gauthier, Abhinav Rastogi, Raghav Gupta, Christopher D. Manning, Christopher Potts
Tree-structured neural networks exploit valuable syntactic parse information as they interpret the meanings of sentences.
Ranked #86 on Natural Language Inference on SNLI
no code implementations • 14 Nov 2014 • Krishnendu Chatterjee, Martin Chmelík, Raghav Gupta, Ayush Kanodia
We consider partially observable Markov decision processes (POMDPs) with a set of target states and every transition is associated with an integer cost.