activity
20182023
most citedNeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

64 citations · 78 across the 8 of their papers we have counts for

collaborators

14 papers

cs.RO2023★ 1 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.CL2022★ 5 cited

IDIAPers @ Causal News Corpus 2022: Efficient Causal Relation Identification Through a Prompt-based Few-shot Approach

Sergio Burdisso, Juan Zuluaga-Gomez, Esau Villatoro-Tello +4

In this paper, we describe our participation in the subtask 1 of CASE-2022, Event Causality Identification with Casual News Corpus. We address the Causal Relation Identification (C…

cs.CL2022★ 3 cited

Claim-Dissector: An Interpretable Fact-Checking System with Joint Re-ranking and Veracity Prediction

Martin Fajcik, Petr Motlicek, Pavel Smrz

We present Claim-Dissector: a novel latent variable model for fact-checking and analysis, which given a claim and a set of retrieved evidences jointly learns to identify: (i) the r…

cs.CL2022★ 5 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★ 64 cited

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…

cs.CL2020

JokeMeter at SemEval-2020 Task 7: Convolutional humor

Martin Docekal, Martin Fajcik, Josef Jon +1

This paper describes our system that was designed for Humor evaluation within the SemEval-2020 Task 7. The system is based on convolutional neural network architecture. We investig…

cs.CL2020

BUT-FIT at SemEval-2020 Task 4: Multilingual commonsense

Josef Jon, Martin Fajčík, Martin Dočekal +1

This paper describes work of the BUT-FIT's team at SemEval 2020 Task 4 - Commonsense Validation and Explanation. We participated in all three subtasks. In subtasks A and B, our sub…

cs.CL2020

Rethinking the Objectives of Extractive Question Answering

Martin Fajcik, Josef Jon, Pavel Smrz

This work demonstrates that using the objective with independence assumption for modelling the span probability of span starting at position and e…

cs.CL2020

BUT-FIT at SemEval-2020 Task 5: Automatic detection of counterfactual statements with deep pre-trained language representation models

Martin Fajcik, Josef Jon, Martin Docekal +1

This paper describes BUT-FIT's submission at SemEval-2020 Task 5: Modelling Causal Reasoning in Language: Detecting Counterfactuals. The challenge focused on detecting whether a gi…

cs.CL2019

BUT-FIT at SemEval-2019 Task 7: Determining the Rumour Stance with Pre-Trained Deep Bidirectional Transformers

Martin Fajcik, Lukáš Burget, Pavel Smrz

This paper describes our system submitted to SemEval 2019 Task 7: RumourEval 2019: Determining Rumour Veracity and Support for Rumours, Subtask A (Gorrell et al., 2019). The challe…

cs.OH2018

Automation of Processor Verification Using Recurrent Neural Networks

Martin Fajcik, Marcela Zachariasova, Pavel Smrz

When considering simulation-based verification of processors, the current trend is to generate stimuli using pseudorandom generators (PRGs), apply them to the processor inputs and…