2 citations · 3 across the 4 of their papers we have counts for
6 papers
Multi-Task Learning by using Contextualized Word Representations for Syntactic Parsing of a Morphologically Rich Language
Toqeer Ehsan, Miriam Butt, Sarmad Hussain +2
We address the challenge of syntactic parsing for Urdu, a morphologically rich language, and present state-of-the-art results for both constituency and dependency parsing. This pap…
From Policy Documents to Structured Survey Responses: Evaluating Large Language Models for Policy Monitoring
Carolyn Cole, Matthias Deschryvere, Toqeer Ehsan +1
Science, technology, and innovation policies are crucial for competitiveness, yet their diversity and scale make them difficult to map and monitor consistently. Existing approaches…
Vroom-Vroom at SHROOM-Visions: A Multi-Judge Committee for Detecting Hallucinated Spans in Vision-Language Outputs
Toqeer Ehsan, Nico Penttilä, Richard Schmidt +2
This paper describes our submission to the SHROOM-Visions shared task on detecting and classifying hallucinated character spans in vision-language model outputs across four languag…
CaMMT: Benchmarking Culturally Aware Multimodal Machine Translation
Emilio Villa-Cueva, Sholpan Bolatzhanova, Diana Turmakhan +32
Translating cultural content poses challenges for machine translation systems due to the differences in conceptualizations between cultures, where language alone may fail to convey…
Enhancing NER Performance in Low-Resource Pakistani Languages using Cross-Lingual Data Augmentation
Toqeer Ehsan, Thamar Solorio
Named Entity Recognition (NER), a fundamental task in Natural Language Processing (NLP), has shown significant advancements for high-resource languages. However, due to a lack of a…
CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark
David Romero, Chenyang Lyu, Haryo Akbarianto Wibowo +73
Visual Question Answering (VQA) is an important task in multimodal AI, and it is often used to test the ability of vision-language models to understand and reason on knowledge pres…