Task-aware Retrieval with Instructions

We study the problem of retrieval with instructions, where users of a retrieval system explicitly describe their intent along with their queries, making the system task-aware. We aim to develop a general-purpose task-aware retrieval systems using multi-task instruction tuning that can follow human-written instructions to find the best documents for a given query. To this end, we introduce the first large-scale collection of approximately 40 retrieval datasets with instructions, and present TART, a multi-task retrieval system trained on the diverse retrieval tasks with instructions. TART shows strong capabilities to adapt to a new task via instructions and advances the state of the art on two zero-shot retrieval benchmarks, BEIR and LOTTE, outperforming models up to three times larger. We further introduce a new evaluation setup to better reflect real-world scenarios, pooling diverse documents and tasks. In this setup, TART significantly outperforms competitive baselines, further demonstrating the effectiveness of guiding retrieval with instructions.

Home - Victor Zhong

Research Excellence Scholarship

UCL’s Research Excellence Scholarship (UCL-RES) is our new prestigious scholarship which aims to attract outstanding scholars to undertake doctoral research at UCL.

PhD positions in Robotics and AI at University College London (September 2023 intake) | Thomas George Thuruthel

There are some PhD positions available in the new research centre in Autonomous Robotics in the Department of Computer Science at University College London. The research topics are broadly in the field of soft robotics, learning-based control, soft sensing technologies, and applied machine learning, starting in September 2023.