activity
20242026
collaborators

8 papers

cs.CL2026

Rate-Utility Frontiers for Language Encodings: Comparing Tokens, Bytes, and Pixels Under Controlled Linguistic Content

Ingo Ziegler, Martin Krebs, Desmond Elliott

Language models encode text as subword tokens, raw bytes, or rendered pixels, but these encodings are usually compared under modeling constraints that expose different amounts of l…

cs.CL2026

Token Distillation: Attention-aware Input Embeddings For New Tokens

Konstantin Dobler, Desmond Elliott, Gerard de Melo

Current language models rely on static vocabularies determined at pretraining time, which can lead to decreased performance and increased computational cost for domains underrepres…

cs.CL2026

Beyond Binary Classification: Detecting Fine-Grained Sexism in Social Media Videos

Laura De Grazia, Danae Sánchez Villegas, Desmond Elliott +2

Online sexism appears in various forms, which makes its detection challenging. Although automated tools can enhance the identification of sexist content, they are often restricted…

cs.CL2025

MuSeD: A Multimodal Spanish Dataset for Sexism Detection in Social Media Videos

Laura De Grazia, Pol Pastells, Mauro Vázquez Chas +4

Sexism is generally defined as prejudice and discrimination based on sex or gender, affecting every sector of society, from social institutions to relationships and individual beha…

cs.CL2025

CRAFT Your Dataset: Task-Specific Synthetic Dataset Generation Through Corpus Retrieval and Augmentation

Ingo Ziegler, Abdullatif Köksal, Desmond Elliott +1

Building high-quality datasets for specialized tasks is a time-consuming and resource-intensive process that often requires specialized domain knowledge. We propose Corpus Retrieva…

cs.CV2025

ImageChain: Advancing Sequential Image-to-Text Reasoning in Multimodal Large Language Models

Danae Sánchez Villegas, Ingo Ziegler, Desmond Elliott

Reasoning over sequences of images remains a challenge for multimodal large language models (MLLMs). While recent models incorporate multi-image data during pre-training, they stil…