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The official repository for "Bridging the Gap Between Indexing and Retrieval for Differentiable Search Index with Query Generation", Shengyao Zhuang, Houxing Ren, Linjun Shou, Jian Pei, Ming Gong, Gui...

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Hi, Dr. Zhuang. Thanks for your contribution again. I've successfully conducted some experiments on MSMARCO with DSI-QG. To keep going, I plan to conduct the experiments on NQ dataset. The...

Hi, I am a bit confused on how the metric HITS is calculated. According to the article, HITS is defined as "the proportion of the correct docids ranked in the...

Hi,I want to evaluate the DSI performance, use the command , ![image](https://user-images.githubusercontent.com/53204985/233579308-8615d825-5272-46e4-aaea-dda093cb04ed.png) , and train 5000steps ,hits@10 is zero,Could you push the right evaluation result.Thank you !

In the paper, a "cross-encoder ranker" is used to rank the queries. Could you point me to the code of the ranking in this repo? Thanks!

Hi. Note that the demo command will launch the training in 8 GPU. Have you tested running this task on a single GPU, and how long will it take? I...

Hi @ArvinZhuang, Thanks for your great efforts! I was wondering if it is possible to provide the data files for the NQ dataset? Thanks!

Step 1 of readme, description of script saying query generation. But in run.py, "DocTqueryTrainer" use "IndexingTrainDataset" and it make document/query to docid dataset. So, result of training model make just...

It seems that the code will output metrics. I wonder if there is a way to output the actual predictions per query?

Hi, I tried to reproduce the results of your experiments on NQ320k dataset as per the table from your paper ![image](https://github.com/ArvinZhuang/DSI-QG/assets/71232712/15142d38-aaef-483f-8cc4-85b304bc606e) To do this, I referred to [your script](https://github.com/ArvinZhuang/DSI-transformers/blob/main/data/NQ/create_NQ_train_vali.py) from...