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researcher

Maja Trebacz

4 papers hereh-index 64.4k citations17 works total

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

author position
  • first author1
  • middle author3

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL1
  • cs.LG1
  • q-bio.GN1
  • q-bio.MN1

identity via Semantic Scholar / OpenAlex

activity
20202022
most citedOpen-Ended Learning Leads to Generally Capable Agents

55 citations · 111 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CL2022★ 54 cited

Teaching language models to support answers with verified quotes

Jacob Menick, Maja Trebacz, Vladimir Mikulik +8

Recent large language models often answer factual questions correctly. But users can't trust any given claim a model makes without fact-checking, because language models can halluc…

cs.LG2021★ 55 cited

Open-Ended Learning Leads to Generally Capable Agents

Open Ended Learning Team, Adam Stooke, Anuj Mahajan +15

In this work we create agents that can perform well beyond a single, individual task, that exhibit much wider generalisation of behaviour to a massive, rich space of challenges. We…

q-bio.GN2020★ 2 cited

Using ontology embeddings for structural inductive bias in gene expression data analysis

Maja Trębacz, Zohreh Shams, Mateja Jamnik +4

Stratifying cancer patients based on their gene expression levels allows improving diagnosis, survival analysis and treatment planning. However, such data is extremely highly dimen…

q-bio.MN2020

Incorporating network based protein complex discovery into automated model construction

Paul Scherer, Maja Trȩbacz, Nikola Simidjievski +4

We propose a method for gene expression based analysis of cancer phenotypes incorporating network biology knowledge through unsupervised construction of computational graphs. The s…

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