266 citations · 739 across the 24 of their papers we have counts for
5 papers · 1 filter
GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval
Kexin Wang, Nandan Thakur, Nils Reimers +1
Dense retrieval approaches can overcome the lexical gap and lead to significantly improved search results. However, they require large amounts of training data which is not availab…
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models
Nandan Thakur, Nils Reimers, Andreas Rücklé +2
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…
TWEAC: Transformer with Extendable QA Agent Classifiers
Gregor Geigle, Nils Reimers, Andreas Rücklé +1
Question answering systems should help users to access knowledge on a broad range of topics and to answer a wide array of different questions. Most systems fall short of this expec…
TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learning
Kexin Wang, Nils Reimers, Iryna Gurevych
Learning sentence embeddings often requires a large amount of labeled data. However, for most tasks and domains, labeled data is seldom available and creating it is expensive. In t…
Retrieve Fast, Rerank Smart: Cooperative and Joint Approaches for Improved Cross-Modal Retrieval
Gregor Geigle, Jonas Pfeiffer, Nils Reimers +2
Current state-of-the-art approaches to cross-modal retrieval process text and visual input jointly, relying on Transformer-based architectures with cross-attention mechanisms that…