Search Results for author: Dilek Hakkani-Tür

Found 11 papers, 3 papers with code

KILM: Knowledge Injection into Encoder-Decoder Language Models

1 code implementation17 Feb 2023 Yan Xu, Mahdi Namazifar, Devamanyu Hazarika, Aishwarya Padmakumar, Yang Liu, Dilek Hakkani-Tür

Large pre-trained language models (PLMs) have been shown to retain implicit knowledge within their parameters.

Entity Disambiguation

Using In-Context Learning to Improve Dialogue Safety

no code implementations2 Feb 2023 Nicholas Meade, Spandana Gella, Devamanyu Hazarika, Prakhar Gupta, Di Jin, Siva Reddy, Yang Liu, Dilek Hakkani-Tür

For instance, using automatic evaluation, we find our best fine-tuned baseline only generates safe responses to unsafe dialogue contexts from DiaSafety 4. 04% more than our approach.

Re-Ranking Retrieval

Revisiting the Boundary between ASR and NLU in the Age of Conversational Dialog Systems

no code implementations CL (ACL) 2022 Manaal Faruqui, Dilek Hakkani-Tür

As more users across the world are interacting with dialog agents in their daily life, there is a need for better speech understanding that calls for renewed attention to the dynamics between research in automatic speech recognition (ASR) and natural language understanding (NLU).

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Zero-Shot Controlled Generation with Encoder-Decoder Transformers

no code implementations11 Jun 2021 Devamanyu Hazarika, Mahdi Namazifar, Dilek Hakkani-Tür

In this work, we propose novel approaches for controlling encoder-decoder transformer-based NLG models in zero-shot.

Document Summarization Machine Translation +1

VISITRON: Visual Semantics-Aligned Interactively Trained Object-Navigator

1 code implementation Findings (ACL) 2022 Ayush Shrivastava, Karthik Gopalakrishnan, Yang Liu, Robinson Piramuthu, Gokhan Tür, Devi Parikh, Dilek Hakkani-Tür

Interactive robots navigating photo-realistic environments need to be trained to effectively leverage and handle the dynamic nature of dialogue in addition to the challenges underlying vision-and-language navigation (VLN).

Binary Classification Imitation Learning +2

Learning Question-Guided Video Representation for Multi-Turn Video Question Answering

no code implementations WS 2019 Guan-Lin Chao, Abhinav Rastogi, Semih Yavuz, Dilek Hakkani-Tür, Jindong Chen, Ian Lane

Understanding and conversing about dynamic scenes is one of the key capabilities of AI agents that navigate the environment and convey useful information to humans.

Navigate Question Answering +2

Towards Universal Dialogue Act Tagging for Task-Oriented Dialogues

no code implementations5 Jul 2019 Shachi Paul, Rahul Goel, Dilek Hakkani-Tür

In unsupervised learning experiments we achieve an F1 score of 54. 1% on system turns in human-human dialogues.

Task-Oriented Dialogue Systems

HyST: A Hybrid Approach for Flexible and Accurate Dialogue State Tracking

no code implementations1 Jul 2019 Rahul Goel, Shachi Paul, Dilek Hakkani-Tür

In this work, we analyze the performance of these two alternative dialogue state tracking methods, and present a hybrid approach (HyST) which learns the appropriate method for each slot type.

Dialogue State Tracking Multi-domain Dialogue State Tracking

Building a Conversational Agent Overnight with Dialogue Self-Play

3 code implementations15 Jan 2018 Pararth Shah, Dilek Hakkani-Tür, Gokhan Tür, Abhinav Rastogi, Ankur Bapna, Neha Nayak, Larry Heck

We propose Machines Talking To Machines (M2M), a framework combining automation and crowdsourcing to rapidly bootstrap end-to-end dialogue agents for goal-oriented dialogues in arbitrary domains.

Cannot find the paper you are looking for? You can Submit a new open access paper.