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Youssef Mohamed

7 accepted papers

2026

The Cylindrical Representation Hypothesis for Language Model Steering

ICML 2026poster

Steering is a widely used technique for controlling large language models, yet its effects are often unstable and hard to predict. Existing theoretical accounts are largely based on the Linear Representation Hypothesis (LRH). While LRH assumes that concepts can be orthogonalized for lossless control…

Cited by 0SourceScholar
2025

Towards AI-Assisted Psychotherapy: Emotion-Guided Generative Interventions

EMNLP 2025

Large language models (LLMs) hold promise for therapeutic interventions, yet most existing datasets rely solely on text, overlooking non-verbal emotional cues essential to real-world therapy. To address this, we introduce a multimodal dataset of 1,441 publicly sourced therapy session videos containi

Cited by 0SourcePDFScholar
2024

Continual Learning on a Diet: Learning from Sparsely Labeled Streams Under Constrained Computation

ICLR 2024poster

We propose and study a realistic Continual Learning (CL) setting where learning algorithms are granted a restricted computational budget per time step while training. We apply this setting to large-scale semi-supervised Continual Learning scenarios with sparse label rate. Previous proficient CL met…

2024

No Culture Left Behind: ArtELingo-28, a Benchmark of WikiArt with Captions in 28 Languages

EMNLP 2024main

Research in vision and language has made considerable progress thanks to benchmarks such as COCO. COCO captions focused on unambiguous facts in English; ArtEmis introduced subjective emotions and ArtELingo introduced some multilinguality (Chinese and Arabic). However we believe there should be more…

2022

ArtELingo: A Million Emotion Annotations of WikiArt with Emphasis on Diversity over Language and Culture

EMNLP 2022main

This paper introduces ArtELingo, a new benchmark and dataset, designed to encourage work on diversity across languages and cultures. Following ArtEmis, a collection of 80k artworks from WikiArt with 0.45M emotion labels and English-only captions, ArtELingo adds another 0.79M annotations in Arabic an…

2022

It Is Okay To Not Be Okay: Overcoming Emotional Bias in Affective Image Captioning by Contrastive Data Collection

CVPR 2022poster

Datasets that capture the connection between vision, language, and affection are limited, causing a lack of understanding of the emotional aspect of human intelligence. As a step in this direction, the ArtEmis dataset was recently introduced as a large-scale dataset of emotional reactions to images…

Cited by 44PDFScholar