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Neural Search Talks [10] — Task-aware Retrieval with Instructions

In this episode of Neural Search Talks, Andrew Yates (Assistant Professor at University of Amsterdam) and Sergi Castella (Analyst at Zeta Alpha) discuss the paper "Task-aware Retrieval with Instructions" by Akari Asai et al. This paper proposes to augment a conglomerate of existing retrieval and NLP datasets with natural language instructions (BERRI, Bank of Explicit RetRieval Instructions) and use it to train TART (Multi-task Instructed Retriever).

📄 Paper:

🍻 BEIR benchmark:

📈 LOTTE (Long-Tail Topic-stratified Evaluation, introduced in ColBERT v2):

🔊 Audio-only podcast:


00:00 Intro: "Task-aware Retrieval with Instructions"

02:20 BERRI, TART, X^2 evaluation

04:00 Background: recent works in domain adaptation

06:50 Instruction Tuning

08:50 Retrieval with descriptions

11:30 Retrieval with instructions

17:28 BERRI, Bank of Explicit RetRieval Instructions

21:48 Repurposing NLP tasks as retrieval tasks

23:53 Negative document selection

27:47 TART, Multi-task Instructed Retriever

31:50 Evaluation: Zero-shot and X^2 evaluation

39:20 Results on Table 3 (BEIR, LOTTE)

50:30 Results on Table 4 (X^2-Retrieval)

55:50 Ablations

57:17 Discussion: user modeling, future work, scale

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