Colbertv2: Effective and efficient retrieval via lightweight late interaction
Neural information retrieval (IR) has greatly advanced search and other knowledge-
intensive language tasks. While many neural IR methods encode queries and documents …
intensive language tasks. While many neural IR methods encode queries and documents …
Beir: A heterogenous benchmark for zero-shot evaluation of information retrieval models
Existing neural information retrieval (IR) models have often been studied in homogeneous
and narrow settings, which has considerably limited insights into their out-of-distribution …
and narrow settings, which has considerably limited insights into their out-of-distribution …
Dense text retrieval based on pretrained language models: A survey
Text retrieval is a long-standing research topic on information seeking, where a system is
required to return relevant information resources to user's queries in natural language. From …
required to return relevant information resources to user's queries in natural language. From …
Simplified data wrangling with ir_datasets
Managing the data for Information Retrieval (IR) experiments can be challenging. Dataset
documentation is scattered across the Internet and once one obtains a copy of the data …
documentation is scattered across the Internet and once one obtains a copy of the data …
Coco-dr: Combating distribution shifts in zero-shot dense retrieval with contrastive and distributionally robust learning
We present a new zero-shot dense retrieval (ZeroDR) method, COCO-DR, to improve the
generalization ability of dense retrieval by combating the distribution shifts between source …
generalization ability of dense retrieval by combating the distribution shifts between source …
The information retrieval experiment platform
We integrate irdatasets, ir_measures, and PyTerrier with TIRA in the Information Retrieval
Experiment Platform (TIREx) to promote more standardized, reproducible, scalable, and …
Experiment Platform (TIREx) to promote more standardized, reproducible, scalable, and …
Overview of Touché 2021: argument retrieval
This paper is a condensed report on the second year of the Touché shared task on
argument retrieval held at CLEF 2021. With the goal to provide a collaborative platform for …
argument retrieval held at CLEF 2021. With the goal to provide a collaborative platform for …
Laprador: Unsupervised pretrained dense retriever for zero-shot text retrieval
In this paper, we propose LaPraDoR, a pretrained dual-tower dense retriever that does not
require any supervised data for training. Specifically, we first present Iterative Contrastive …
require any supervised data for training. Specifically, we first present Iterative Contrastive …
Zero-shot dense retrieval with momentum adversarial domain invariant representations
Dense retrieval (DR) methods conduct text retrieval by first encoding texts in the embedding
space and then matching them by nearest neighbor search. This requires strong locality …
space and then matching them by nearest neighbor search. This requires strong locality …
Overview of touché 2022: argument retrieval
This paper is a condensed report on the third year of the Touché lab on argument retrieval
held at CLEF 2022. With the goal to foster and support the development of technologies for …
held at CLEF 2022. With the goal to foster and support the development of technologies for …