Feature Extraction
PEFT
Safetensors
English
lora
multimodal
embedding
retrieval
chain-of-thought
qwen3-vl
Instructions to use zhanglx/TWN-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use zhanglx/TWN-4B with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
metadata
base_model: Qwen/Qwen3-VL-4B-Instruct
library_name: peft
license: apache-2.0
language:
- en
tags:
- lora
- multimodal
- embedding
- retrieval
- chain-of-thought
- qwen3-vl
pipeline_tag: feature-extraction
TWN-4B
The 4B version of Think When Needed (TWN), a framework for adaptive reasoning-driven multimodal embeddings. TWN introduces a dual-LoRA architecture on top of Qwen3-VL-4B-Instruct with a learned routing gate that adaptively activates chain-of-thought reasoning.
Weight Structure
TWN-4B/
reasoning/ # LoRA adapter for CoT generation
adapter_config.json
adapter_model.safetensors
embedding/ # LoRA adapter for embedding extraction
adapter_config.json
adapter_model.safetensors
gate_mlp.pt # Routing gate MLP weights
queries.pt # Learnable query embeddings
Citation
@article{zhang2026thinkneeded,
title={Think When Needed: Adaptive Reasoning-Driven Multimodal Embeddings with a Dual-LoRA Architecture},
author={Longxiang Zhang and Weilong Dai and Guanghao Zhang and Hao Jiang and Pipei Huang},
year={2026},
eprint={2605.14448},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2605.14448},
}