AgentIR: 1st Workshop on Agent-based Information Retrieval

Introduction

Welcome to AgentIR: 1st Workshop on Agent-based Information Retrieval! Information retrieval (IR) systems have become an essential component in modern society to help users find useful information, which consists of a series of processes including query expansion, item recall, item ranking and re-ranking, etc. Based on the ranked information list, users can provide their feedbacks. Such an interaction process between users and IR systems can be naturally formulated as a decision-making problem, which can be either one-step or sequential. In the last ten years, deep reinforcement learning (DRL) has become a promising direction for decision-making, since DRL utilizes the high model capacity of deep learning for complex decision-making tasks. On the one hand, there have been emerging research works focusing on leveraging DRL for IR tasks. However, the fundamental information theory under DRL settings, the challenge of RL methods for Industrial IR tasks, or the simulations of DRL-based IR systems, has not been deeply investigated. On the other hand, the emerging LLM provides new opportunities for optimizing and simulating IR systems. AgentIR provides a venue for both academia researchers and industry practitioners to present the recent advances of both DRL-based IR systems and LLM-based IR systems from the agent-based IR’s perspective, to foster novel research, interesting findings, and new applications.

Attendance

When: July 18, 2024
Where:
- In-person participation: The workshop will be an in-person event and to be held in room Ohio in the Capital Hilton Hotel, Washington D.C., US.
- Online participation: You can also join the workshop virtually at Zoom.