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researcher

Martin Gubri

Parameter Lab

15 papers hereh-index 8496 citations20 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author1
  • first author4
  • middle author9
  • last author1

Across the 15 of 15 papers where every author was matched, so the position is known.

fields
  • cs.LG6
  • cs.CL5
  • cs.AI1
  • cs.CR1
  • cs.LO1
  • stat.ML1
affiliations
  • Parameter Lab
Homepage
same name
  • Martin Gubri — 5 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182025
most citedProPILE: Probing Privacy Leakage in Large Language Models

21 citations · 29 across the 15 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.AI2024

Social Science Is Necessary for Operationalizing Socially Responsible Foundation Models

Adam Davies, Elisa Nguyen, Michael Simeone +2

With the rise of foundation models, there is growing concern about their potential social impacts. Social science has a long history of studying the social impacts of transformativ…

cs.CL2024

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

Haritz Puerto, Martin Gubri, Sangdoo Yun +1

Membership inference attacks (MIA) attempt to verify the membership of a given data sample in the training set for a model. MIA has become relevant in recent years, following the r…

cs.CL2024

Calibrating Large Language Models Using Their Generations Only

Dennis Ulmer, Martin Gubri, Hwaran Lee +2

As large language models (LLMs) are increasingly deployed in user-facing applications, building trust and maintaining safety by accurately quantifying a model's confidence in its p…

cs.LG2024

TRAP: Targeted Random Adversarial Prompt Honeypot for Black-Box Identification

Martin Gubri, Dennis Ulmer, Hwaran Lee +2

Large Language Model (LLM) services and models often come with legal rules on who can use them and how they must use them. Assessing the compliance of the released LLMs is crucial,…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.