Search Results for author: Haritz Puerto

Found 9 papers, 8 papers with code

Scaling Up Membership Inference: When and How Attacks Succeed on Large Language Models

1 code implementation31 Oct 2024 Haritz Puerto, Martin Gubri, Sangdoo Yun, Seong Joon Oh

Membership inference attacks (MIA) attempt to verify the membership of a given data sample in the training set for a model.

Surveying (Dis)Parities and Concerns of Compute Hungry NLP Research

no code implementations29 Jun 2023 Ji-Ung Lee, Haritz Puerto, Betty van Aken, Yuki Arase, Jessica Zosa Forde, Leon Derczynski, Andreas Rücklé, Iryna Gurevych, Roy Schwartz, Emma Strubell, Jesse Dodge

Many recent improvements in NLP stem from the development and use of large pre-trained language models (PLMs) with billions of parameters.

UKP-SQuARE: An Interactive Tool for Teaching Question Answering

1 code implementation31 May 2023 Haishuo Fang, Haritz Puerto, Iryna Gurevych

To evaluate the effectiveness of UKP-SQuARE in teaching scenarios, we adopted it in a postgraduate NLP course and surveyed the students after the course.

Information Retrieval Question Answering +1

UKP-SQuARE v3: A Platform for Multi-Agent QA Research

1 code implementation31 Mar 2023 Haritz Puerto, Tim Baumgärtner, Rachneet Sachdeva, Haishuo Fang, Hao Zhang, Sewin Tariverdian, Kexin Wang, Iryna Gurevych

To ease research in multi-agent models, we extend UKP-SQuARE, an online platform for QA research, to support three families of multi-agent systems: i) agent selection, ii) early-fusion of agents, and iii) late-fusion of agents.

Question Answering

UKP-SQuARE v2: Explainability and Adversarial Attacks for Trustworthy QA

1 code implementation19 Aug 2022 Rachneet Sachdeva, Haritz Puerto, Tim Baumgärtner, Sewin Tariverdian, Hao Zhang, Kexin Wang, Hossain Shaikh Saadi, Leonardo F. R. Ribeiro, Iryna Gurevych

In this paper, we introduce SQuARE v2, the new version of SQuARE, to provide an explainability infrastructure for comparing models based on methods such as saliency maps and graph-based explanations.

Adversarial Attack Explainable Models +2

UKP-SQUARE: An Online Platform for Question Answering Research

1 code implementation ACL 2022 Tim Baumgärtner, Kexin Wang, Rachneet Sachdeva, Max Eichler, Gregor Geigle, Clifton Poth, Hannah Sterz, Haritz Puerto, Leonardo F. R. Ribeiro, Jonas Pfeiffer, Nils Reimers, Gözde Gül Şahin, Iryna Gurevych

Recent advances in NLP and information retrieval have given rise to a diverse set of question answering tasks that are of different formats (e. g., extractive, abstractive), require different model architectures (e. g., generative, discriminative), and setups (e. g., with or without retrieval).

Explainable Models Information Retrieval +2

MetaQA: Combining Expert Agents for Multi-Skill Question Answering

1 code implementation3 Dec 2021 Haritz Puerto, Gözde Gül Şahin, Iryna Gurevych

The recent explosion of question answering (QA) datasets and models has increased the interest in the generalization of models across multiple domains and formats by either training on multiple datasets or by combining multiple models.

Question Answering

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