Nils Reimers | DeepAI

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∙ 10/19/2022

Incorporating Relevance Feedback for Information-Seeking Retrieval using Few-Shot Document Re-Ranking

Pairing a lexical retriever with a neural re-ranking model has set state...

0 Tim Baumgartner, et al. ∙

∙ 10/13/2022

MTEB: Massive Text Embedding Benchmark

Text embeddings are commonly evaluated on a small set of datasets from a...

0 Niklas Muennighoff, et al. ∙

∙ 09/22/2022

Efficient Few-Shot Learning Without Prompts

Recent few-shot methods, such as parameter-efficient fine-tuning (PEFT) ...

10 Lewis Tunstall, et al. ∙

∙ 05/23/2022

Domain Adaptation for Memory-Efficient Dense Retrieval

Dense retrievers encode documents into fixed dimensional embeddings. How...

9 Nandan Thakur, et al. ∙

∙ 03/25/2022

UKP-SQUARE: An Online Platform for Question Answering Research

Recent advances in NLP and information retrieval have given rise to a di...

2 Tim Baumgartner, et al. ∙

∙ 12/14/2021

GPL: Generative Pseudo Labeling for Unsupervised Domain Adaptation of Dense Retrieval

Dense retrieval approaches can overcome the lexical gap and lead to sign...

0 Kexin Wang, et al. ∙

∙ 04/17/2021

BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models

Neural IR models have often been studied in homogeneous and narrow setti...

13 Nandan Thakur, et al. ∙

∙ 04/14/2021

TWEAC: Transformer with Extendable QA Agent Classifiers

Question answering systems should help users to access knowledge on a br...

0 Gregor Geigle, et al. ∙

∙ 04/14/2021

TSDAE: Using Transformer-based Sequential Denoising Auto-Encoder for Unsupervised Sentence Embedding Learning

Learning sentence embeddings often requires large amount of labeled data...

0 Kexin Wang, et al. ∙

∙ 03/22/2021

Retrieve Fast, Rerank Smart: Cooperative and Joint Approaches for Improved Cross-Modal Retrieval

Current state-of-the-art approaches to cross-modal retrieval process tex...

8 Gregor Geigle, et al. ∙

∙ 12/28/2020

The Curse of Dense Low-Dimensional Information Retrieval for Large Index Sizes

Information Retrieval using dense low-dimensional representations recent...

0 Nils Reimers, et al. ∙

∙ 11/24/2020

Cross-Document Event Coreference Resolution Beyond Corpus-Tailored Systems

Cross-document event coreference resolution (CDCR) is an NLP task in whi...

0 Michael Bugert, et al. ∙

∙ 10/22/2020

AdapterDrop: On the Efficiency of Adapters in Transformers

Massively pre-trained transformer models are computationally expensive t...

6 Andreas Rücklé, et al. ∙

∙ 10/16/2020

Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks

There are two approaches for pairwise sentence scoring: Cross-encoders, ...

0 Nandan Thakur, et al. ∙

∙ 04/21/2020

Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation

We present an easy and efficient method to extend existing sentence embe...

0 Nils Reimers, et al. ∙

∙ 08/27/2019

Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

BERT (Devlin et al., 2018) and RoBERTa (Liu et al., 2019) has set a new ...

0 Nils Reimers, et al. ∙

∙ 06/24/2019

Classification and Clustering of Arguments with Contextualized Word Embeddings

We experiment with two recent contextualized word embedding methods (ELM...

0 Nils Reimers, et al. ∙

∙ 06/04/2019

Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution

Recognizing coreferring events and entities across multiple texts is cru...

0 Shany Barhom, et al. ∙

∙ 04/05/2019

Alternative Weighting Schemes for ELMo Embeddings

ELMo embeddings (Peters et. al, 2018) had a huge impact on the NLP commu...

0 Nils Reimers, et al. ∙

∙ 03/26/2018

Why Comparing Single Performance Scores Does Not Allow to Draw Conclusions About Machine Learning Approaches

Developing state-of-the-art approaches for specific tasks is a major dri...

0 Nils Reimers, et al. ∙

∙ 07/31/2017

Reporting Score Distributions Makes a Difference: Performance Study of LSTM-networks for Sequence Tagging

In this paper we show that reporting a single performance score is insuf...

0 Nils Reimers, et al. ∙

∙ 07/21/2017

Optimal Hyperparameters for Deep LSTM-Networks for Sequence Labeling Tasks

Selecting optimal parameters for a neural network architecture can often...

0 Nils Reimers, et al. ∙