activity
20182021
most citedHigh-Quality Diversification for Task-Oriented Dialogue Systems

1 citations · 1 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CL2021★ 1 cited

High-Quality Diversification for Task-Oriented Dialogue Systems

Zhiwen Tang, Hrishikesh Kulkarni, Grace Hui Yang

Many task-oriented dialogue systems use deep reinforcement learning (DRL) to learn policies that respond to the user appropriately and complete the tasks successfully. Training DRL…

cs.IR2020

Balancing Reinforcement Learning Training Experiences in Interactive Information Retrieval

Limin Chen, Zhiwen Tang, Grace Hui Yang

Interactive Information Retrieval (IIR) and Reinforcement Learning (RL) share many commonalities, including an agent who learns while interacts, a long-term and complex goal, and a…

cs.IR2019

Corpus-Level End-to-End Exploration for Interactive Systems

Zhiwen Tang, Grace Hui Yang

A core interest in building Artificial Intelligence (AI) agents is to let them interact with and assist humans. One example is Dynamic Search (DS), which models the process that a…

cs.AI2019

A Re-classification of Information Seeking Tasks and Their Computational Solutions

Zhiwen Tang, Grace Hui Yang

This article presents a re-classification of information seeking (IS) tasks, concepts, and algorithms. The proposed taxonomy provides new dimensions to look into information seekin…

cs.IR2018

DeepTileBars: Visualizing Term Distribution for Neural Information Retrieval

Zhiwen Tang, Grace Hui Yang

Most neural Information Retrieval (Neu-IR) models derive query-to-document ranking scores based on term-level matching. Inspired by TileBars, a classical term distribution visualiz…