activity
20182022
most citedRLIRank: Learning to Rank with Reinforcement Learning for Dynamic Search

18 citations · 78 across the 14 of their papers we have counts for

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8 papers · 1 filter

cs.CL202210 cited

Alexa, Let's Work Together: Introducing the First Alexa Prize TaskBot Challenge on Conversational Task Assistance

Anna Gottardi, Osman Ipek, Giuseppe Castellucci +27

Since its inception in 2016, the Alexa Prize program has enabled hundreds of university students to explore and compete to develop conversational agents through the SocialBot Grand…

cs.CL2021

Identifying Helpful Sentences in Product Reviews

Iftah Gamzu, Hila Gonen, Gilad Kutiel +2

In recent years online shopping has gained momentum and became an important venue for customers wishing to save time and simplify their shopping process. A key advantage of shoppin…

cs.CL2020

Contextual Dialogue Act Classification for Open-Domain Conversational Agents

Ali Ahmadvand, Jason Ingyu Choi, Eugene Agichtein

Classifying the general intent of the user utterance in a conversation, also known as Dialogue Act (DA), e.g., open-ended question, statement of opinion, or request for an opinion,…

cs.CL2020

Would you Like to Talk about Sports Now? Towards Contextual Topic Suggestion for Open-Domain Conversational Agents

Ali Ahmadvand, Harshita Sahijwani, Eugene Agichtein

To hold a true conversation, an intelligent agent should be able to occasionally take initiative and recommend the next natural conversation topic. This is a challenging task. A to…

cs.CL20203 cited

ConCET: Entity-Aware Topic Classification for Open-Domain Conversational Agents

Ali Ahmadvand, Harshita Sahijwani, Jason Ingyu Choi +1

Identifying the topic (domain) of each user's utterance in open-domain conversational systems is a crucial step for all subsequent language understanding and response tasks. In par…

cs.CL2020

Domain-Guided Task Decomposition with Self-Training for Detecting Personal Events in Social Media

Payam Karisani, Joyce C. Ho, Eugene Agichtein

Mining social media content for tasks such as detecting personal experiences or events, suffer from lexical sparsity, insufficient training data, and inventive lexicons. To reduce…