Zobrazeno 1 - 10
of 190
pro vyhledávání: '"Docekal, P"'
Autor:
Fajcik, Martin, Docekal, Martin, Dolezal, Jan, Ondrej, Karel, Beneš, Karel, Kapsa, Jan, Smrz, Pavel, Polok, Alexander, Hradis, Michal, Neverilova, Zuzana, Horak, Ales, Sabol, Radoslav, Stefanik, Michal, Jirkovsky, Adam, Adamczyk, David, Hyner, Petr, Hula, Jan, Kydlicek, Hynek
We present BenCzechMark (BCM), the first comprehensive Czech language benchmark designed for large language models, offering diverse tasks, multiple task formats, and multiple evaluation metrics. Its scoring system is grounded in statistical signific
Externí odkaz:
http://arxiv.org/abs/2412.17933
This paper introduces OARelatedWork, the first large-scale multi-document summarization dataset for related work generation containing whole related work sections and full-texts of cited papers. The dataset includes 94 450 papers and 5 824 689 unique
Externí odkaz:
http://arxiv.org/abs/2405.01930
Publikováno v:
IEEE-RAS International Conference on Humanoid Robots (Humanoids 2022)
We study the performance of state-of-the-art human keypoint detectors in the context of close proximity human-robot interaction. The detection in this scenario is specific in that only a subset of body parts such as hands and torso are in the field o
Externí odkaz:
http://arxiv.org/abs/2207.07742
Autor:
Docekal, Martin, Smrz, Pavel
Publikováno v:
The International FLAIRS Conference Proceedings. 35, (May 2022)
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 issue for keyphrase extraction by chunking the long documents while kee
Externí odkaz:
http://arxiv.org/abs/2205.05391
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, generative reader and a mechanism that aggregates the final prediction from al
Externí odkaz:
http://arxiv.org/abs/2109.03502
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 twice, reaD twice) pipeline composed of retriever, passage reranker, extra
Externí odkaz:
http://arxiv.org/abs/2102.10697
Autor:
Min, Sewon, Boyd-Graber, Jordan, Alberti, Chris, Chen, Danqi, Choi, Eunsol, Collins, Michael, Guu, Kelvin, Hajishirzi, Hannaneh, Lee, Kenton, Palomaki, Jennimaria, Raffel, Colin, Roberts, Adam, Kwiatkowski, Tom, Lewis, Patrick, Wu, Yuxiang, Küttler, Heinrich, Liu, Linqing, Minervini, Pasquale, Stenetorp, Pontus, Riedel, Sebastian, Yang, Sohee, Seo, Minjoon, Izacard, Gautier, Petroni, Fabio, Hosseini, Lucas, De Cao, Nicola, Grave, Edouard, Yamada, Ikuya, Shimaoka, Sonse, Suzuki, Masatoshi, Miyawaki, Shumpei, Sato, Shun, Takahashi, Ryo, Suzuki, Jun, Fajcik, Martin, Docekal, Martin, Ondrej, Karel, Smrz, Pavel, Cheng, Hao, Shen, Yelong, Liu, Xiaodong, He, Pengcheng, Chen, Weizhu, Gao, Jianfeng, Oguz, Barlas, Chen, Xilun, Karpukhin, Vladimir, Peshterliev, Stan, Okhonko, Dmytro, Schlichtkrull, Michael, Gupta, Sonal, Mehdad, Yashar, Yih, Wen-tau
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 return natural language answers. The aim of the competition was to bui
Externí odkaz:
http://arxiv.org/abs/2101.00133
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 investigate the system on the official dataset, and we provide more insight to
Externí odkaz:
http://arxiv.org/abs/2008.11053
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 submissions are based on pretrained language representation models (namel
Externí odkaz:
http://arxiv.org/abs/2008.07259
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 given statement contains a counterfactual (Subtask 1) and extracting bot
Externí odkaz:
http://arxiv.org/abs/2007.14128