activity
20182023
most citedQuery-Based Keyphrase Extraction from Long Documents

5 citations · 6 across the 4 of their papers we have counts for

collaborators

11 papers

cs.RO20231 cited

ARCOR2: Framework for Collaborative End-User Management of Industrial Robotic Workplaces using Augmented Reality

Michal Kapinus, Zdeněk Materna, Daniel Bambušek +2

This paper presents a novel framework enabling end-users to perform the management of complex robotic workplaces using a tablet and augmented reality. The framework allows users to…

cs.CL2022

IDIAPers @ Causal News Corpus 2022: Extracting Cause-Effect-Signal Triplets via Pre-trained Autoregressive Language Model

Martin Fajcik, Muskaan Singh, Juan Zuluaga-Gomez +4

In this paper, we describe our shared task submissions for Subtask 2 in CASE-2022, Event Causality Identification with Casual News Corpus. The challenge focused on the automatic de…

cs.CL20225 cited

Query-Based Keyphrase Extraction from Long Documents

Martin Docekal, Pavel Smrz

Transformer-based architectures in natural language processing force input size limits that can be problematic when long documents need to be processed. This paper overcomes this i…

cs.CL2021

R2-D2: A Modular Baseline for Open-Domain Question Answering

Martin Fajcik, Martin Docekal, Karel Ondrej +1

This work presents a novel four-stage open-domain QA pipeline R2-D2 (Rank twice, reaD twice). The pipeline is composed of a retriever, passage reranker, extractive reader, generati…

cs.CL2021

Pruning the Index Contents for Memory Efficient Open-Domain QA

Martin Fajcik, Martin Docekal, Karel Ondrej +1

This work presents a novel pipeline that demonstrates what is achievable with a combined effort of state-of-the-art approaches. Specifically, it proposes the novel R2-D2 (Rank twic…

cs.CL2021

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

Sewon Min, Jordan Boyd-Graber, Chris Alberti +50

We review the EfficientQA competition from NeurIPS 2020. The competition focused on open-domain question answering (QA), where systems take natural language questions as input and…