activity
20192026
most citedDoes CLIP Benefit Visual Question Answering in the Medical Domain as Much as it Does in the General Domain?

41 citations · 46 across the 9 of their papers we have counts for

collaborators

9 papers

cs.IR2026

Q2D-Web: A Large-Scale Benchmark for Retrieval in Agentic RAG Systems

Maximilian Schall, Sedigheh Eslami, Markus Krimmel +4

Evaluating first-stage retrievers in large-scale production RAG requires a benchmark that pairs a large-scale corpus with a large set of agent-reformulated search queries based on…

cs.LG2026

Diffusion-Pretrained Dense and Contextual Embeddings

Sedigheh Eslami, Maksim Gaiduk, Markus Krimmel +3

In this report, we introduce pplx-embed, a family of multilingual embedding models that employ multi-stage contrastive learning on a diffusion-pretrained language model backbone fo…

cs.CL2025

jina-vlm: Small Multilingual Vision Language Model

Andreas Koukounas, Georgios Mastrapas, Florian Hönicke +3

We present jina-vlm, a token-efficient 2.4B parameter vision-language model that achieves state-of-the-art multilingual VQA performance among open 2B-scale VLMs. The model couples…

cs.AI2025★ 1 cited

jina-embeddings-v4: Universal Embeddings for Multimodal Multilingual Retrieval

Michael Günther, Saba Sturua, Mohammad Kalim Akram +8

We introduce jina-embeddings-v4, a 3.8 billion parameter multimodal embedding model that unifies text and image representations through a novel architecture supporting both single-…

cs.CL2024★ 2 cited

jina-clip-v2: Multilingual Multimodal Embeddings for Text and Images

Andreas Koukounas, Georgios Mastrapas, Sedigheh Eslami +7

Contrastive Language-Image Pretraining (CLIP) has been widely used for crossmodal information retrieval and multimodal understanding tasks. However, CLIP models are mainly optimize…

cs.CV2024★ 1 cited

Mitigate the Gap: Investigating Approaches for Improving Cross-Modal Alignment in CLIP

Sedigheh Eslami, Gerard de Melo

Contrastive Language--Image Pre-training (CLIP) has manifested remarkable improvements in zero-shot classification and cross-modal vision-language tasks. Yet, from a geometrical po…

cs.CV2024★ 1 cited

ELSA: Evaluating Localization of Social Activities in Urban Streets using Open-Vocabulary Detection

Maryam Hosseini, Marco Cipriano, Sedigheh Eslami +4

Existing Open Vocabulary Detection (OVD) models exhibit a number of challenges. They often struggle with semantic consistency across diverse inputs, and are often sensitive to slig…

cs.CV2021★ 41 cited

Does CLIP Benefit Visual Question Answering in the Medical Domain as Much as it Does in the General Domain?

Sedigheh Eslami, Gerard de Melo, Christoph Meinel

Contrastive Language--Image Pre-training (CLIP) has shown remarkable success in learning with cross-modal supervision from extensive amounts of image--text pairs collected online.…

cs.HC2019

SignCol: Open-Source Software for Collecting Sign Language Gestures

Mohammad Eslami, Mahdi Karami, Sedigheh Eslami +3

Sign(ed) languages use gestures, such as hand or head movements, for communication. Sign language recognition is an assistive technology for individuals with hearing disability and…