activity
20182026
most citedNeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

64 citations · 72 across the 13 of their papers we have counts for

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16 papers · 1 filter

cs.CL2025

Examining the Metrics for Document-Level Claim Extraction in Czech and Slovak

Lucia Makaiova, Martin Fajcik, Antonin Jarolim

Document-level claim extraction remains an open challenge in the field of fact-checking, and subsequently, methods for evaluating extracted claims have received limited attention.…

cs.CL2025

Can LLMs extract human-like fine-grained evidence for evidence-based fact-checking?

Antonín Jarolím, Martin Fajčík, Lucia Makaiová

Misinformation frequently spreads in user comments under online news articles, highlighting the need for effective methods to detect factually incorrect information. To strongly su…

cs.CL2025

On Recipe Memorization and Creativity in Large Language Models: Is Your Model a Creative Cook, a Bad Cook, or Merely a Plagiator?

Jan Kvapil, Martin Fajcik

This work-in-progress investigates the memorization, creativity, and nonsense found in cooking recipes generated from Large Language Models (LLMs). Precisely, we aim (i) to analyze…

cs.CL2024

BenCzechMark : A Czech-centric Multitask and Multimetric Benchmark for Large Language Models with Duel Scoring Mechanism

Martin Fajcik, Martin Docekal, Jan Dolezal +15

We present BenCzechMark (BCM), the first comprehensive Czech language benchmark designed for large language models, offering diverse tasks, multiple task formats, and multiple eval…

cs.CL2024

OARelatedWork: A Large-Scale Dataset of Related Work Sections with Full-texts from Open Access Sources

Martin Docekal, Martin Fajcik, Pavel Smrz

This paper introduces OARelatedWork: a dataset for related work generation from open-access sources. It is the first large-scale multi-document summarization dataset for related wo…

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.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…