Shi-Zhe Chen — accepted AI-conference papers

2026

U-MARVEL: Unveiling Key Factors for Universal Multimodal Retrieval via Embedding Learning with MLLMs

Xiaojie Li, Chu Li, Shi-Zhe Chen, Xi Chen

ICLR 2026poster

Universal multimodal retrieval (UMR), which aims to address complex retrieval tasks where both queries and candidates span diverse modalities, has been significantly advanced by the emergence of MLLMs. While state-of-the-art MLLM-based methods in the literature predominantly adopt contrastive learni…

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2025

Conan-Embedding-v2: Training an LLM from Scratch for Text Embeddings

Shiyu Li, Yang Tang, Ruijie Liu, Shi-Zhe Chen, Xi Chen

EMNLP 2025

Large language models (LLMs) have recently demonstrated excellent performance in text embedding tasks. Previous work usually use LoRA to fine-tune existing LLMs, which are limited by the data and training gap between LLMs and embedding models. In this work, we introduce Conan-embedding-v2, a new 1.4

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