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Enric Boix-Adserà

19 papers hereh-index 9532 citations20 works total

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

author position
  • sole author2
  • first author6
  • middle author6
  • last author5

Across the 19 of 19 papers where every author was matched, so the position is known.

fields
  • cs.LG12
  • cs.CL4
  • cs.AI1
  • cs.DS1
  • stat.ML1
same name
  • Enric Boix-Adserà — 6 papers, h 4
  • Enric Boix-Adserà — 4 papers, h 5
  • Enric Boix-Adserà — 1 paper

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
20192026
most citedThe merged-staircase property: a necessary and nearly sufficient condition for SGD learning of sparse functions on two-layer neural networks

8 citations · 24 across the 16 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2026

Model Hypnosis: Strong control of AI via additive subliminal effects

Enric Boix-Adsera, Benedict Tessler

We demonstrate that AI models are broadly susceptible to a phenomenon we call model hypnosis, in which individually weak and seemingly irrelevant cues in the prompt can be systemat…

cs.CL2025

Toward universal steering and monitoring of AI models

Daniel Beaglehole, Adityanarayanan Radhakrishnan, Enric Boix-Adserà +1

Modern AI models contain much of human knowledge, yet understanding of their internal representation of this knowledge remains elusive. Characterizing the structure and properties…

cs.CL2023★ 1 cited

Prompts have evil twins

Rimon Melamed, Lucas H. McCabe, Tanay Wakhare +3

We discover that many natural-language prompts can be replaced by corresponding prompts that are unintelligible to humans but that provably elicit similar behavior in language mode…

cs.CL2023★ 2 cited

When can transformers reason with abstract symbols?

Enric Boix-Adsera, Omid Saremi, Emmanuel Abbe +3

We investigate the capabilities of transformer models on relational reasoning tasks. In these tasks, models are trained on a set of strings encoding abstract relations, and are the…

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