TSEmbed: Unlocking Task Scaling in Universal Multimodal Embeddings

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References (52)

[1]
Embed-RL: Reinforcement Learning for Reasoning-Driven Multimodal Embeddings
2026Hao Jiang, Yuji Wang et al.
[2]
Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking
2026Mingxin Li, Yanzhao Zhang et al.
[3]
Bridging the Copyright Gap: Do Large Vision-Language Models Recognize and Respect Copyrighted Content?
2025Naen Xu, Jinghuai Zhang et al.
[4]
Elastic Mixture of Rank-Wise Experts for Knowledge Reuse in Federated Fine-Tuning
2025Yebo Wu, Jingguang Li et al.
[5]
RzenEmbed: Towards Comprehensive Multimodal Retrieval
2025Weijian Jian, Yajun Zhang et al.
[6]
UniME-V2: MLLM-as-a-Judge for Universal Multimodal Embedding Learning
2025Tiancheng Gu, Kaicheng Yang et al.
[7]
Think Then Embed: Generative Context Improves Multimodal Embedding
2025Xuanming Cui, Jianpeng Cheng et al.
[8]
Memory-Efficient Federated Fine-Tuning of Large Language Models via Layer Pruning
2025Yebo Wu, Jingguang Li et al.
[9]
Learning Like Humans: Resource-Efficient Federated Fine-Tuning through Cognitive Developmental Stages
2025Yebo Wu, Jingguang Li et al.
[10]
VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents
2025Rui Meng, Ziyan Jiang et al.
[11]
Bridging Modalities: Improving Universal Multimodal Retrieval by Multimodal Large Language Models
2025Xin Zhang, Yanzhao Zhang et al.
[12]
Improve Multi-Modal Embedding Learning via Explicit Hard Negative Gradient Amplifying
2025Youze Xue, Dian Li et al.
[13]
Modality Curation: Building Universal Embeddings for Advanced Multimodal Information Retrieval
2025Fanheng Kong, Jingyuan Zhang et al.
[14]
Breaking the Batch Barrier (B3) of Contrastive Learning via Smart Batch Mining
2025Raghuveer Thirukovalluru, Rui Meng et al.
[15]
CAFE: Unifying Representation and Generation with Contrastive-Autoregressive Finetuning
2025Hao Yu, Zhuokai Zhao et al.
[16]
LLaVE: Large Language and Vision Embedding Models with Hardness-Weighted Contrastive Learning
2025Zhibin Lan, Liqiang Niu et al.
[17]
SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features
2025Michael Tschannen, Alexey Gritsenko et al.
[18]
A Comprehensive Survey on Composed Image Retrieval
2025Xuemeng Song, Haoqiang Lin et al.
[19]
LamRA: Large Multimodal Model as Your Advanced Retrieval Assistant
2024Yikun Liu, Pingan Chen et al.
[20]
CopyrightMeter: Revisiting Copyright Protection in Text-to-image Models
2024Naen Xu, Changjiang Li et al.

Showing 20 of 52 references

Founder's Pitch

"TSEmbed enhances universal multimodal embeddings using MoE and LoRA to overcome task conflict, achieving state-of-the-art performance."

Multimodal ModelsScore: 5View PDF ↗

Commercial Viability Breakdown

0-10 scale

High Potential

2/4 signals

5

Quick Build

2/4 signals

5

Series A Potential

2/4 signals

5

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