Search Results for author: Shahin Shayandeh

Found 10 papers, 4 papers with code

AUTODIAL: Efficient Asynchronous Task-Oriented Dialogue Model

no code implementations10 Mar 2023 Prajjwal Bhargava, Pooyan Amini, Shahin Shayandeh, Chinnadhurai Sankar

As large dialogue models become commonplace in practice, the problems surrounding high compute requirements for training, inference and larger memory footprint still persists.

Dialogue State Tracking

Database Search Results Disambiguation for Task-Oriented Dialog Systems

no code implementations NAACL 2022 Kun Qian, Ahmad Beirami, Satwik Kottur, Shahin Shayandeh, Paul Crook, Alborz Geramifard, Zhou Yu, Chinnadhurai Sankar

We find that training on our augmented dialog data improves the model's ability to deal with ambiguous scenarios, without sacrificing performance on unmodified turns.

Multi-Task Learning

Know Thy Strengths: Comprehensive Dialogue State Tracking Diagnostics

2 code implementations15 Dec 2021 Hyundong Cho, Chinnadhurai Sankar, Christopher Lin, Kaushik Ram Sadagopan, Shahin Shayandeh, Asli Celikyilmaz, Jonathan May, Ahmad Beirami

Recent works that revealed the vulnerability of dialogue state tracking (DST) models to distributional shifts have made holistic comparisons on robustness and qualitative analyses increasingly important for understanding their relative performance.

Ranked #4 on Multi-domain Dialogue State Tracking on MULTIWOZ 2.1 (using extra training data)

Dialogue State Tracking Multi-domain Dialogue State Tracking +1

Robust Conversational AI with Grounded Text Generation

no code implementations7 Sep 2020 Jianfeng Gao, Baolin Peng, Chunyuan Li, Jinchao Li, Shahin Shayandeh, Lars Liden, Heung-Yeung Shum

This article provides an overview of this progress and discusses related methods and technologies that can be incorporated for building robust conversational AI systems.

Text Generation World Knowledge

Conversation Learner -- A Machine Teaching Tool for Building Dialog Managers for Task-Oriented Dialog Systems

no code implementations9 Apr 2020 Swadheen Shukla, Lars Liden, Shahin Shayandeh, Eslam Kamal, Jinchao Li, Matt Mazzola, Thomas Park, Baolin Peng, Jianfeng Gao

Traditionally, industry solutions for building a task-oriented dialog system have relied on helping dialog authors define rule-based dialog managers, represented as dialog flows.

Guided Dialog Policy Learning without Adversarial Learning in the Loop

1 code implementation7 Apr 2020 Ziming Li, Sungjin Lee, Baolin Peng, Jinchao Li, Julia Kiseleva, Maarten de Rijke, Shahin Shayandeh, Jianfeng Gao

Reinforcement Learning (RL) methods have emerged as a popular choice for training an efficient and effective dialogue policy.

Reinforcement Learning (RL)

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