--- license: other license_name: ltx-2-community tags: - video-generation - audio - lora - temporal-control - text-to-video ---

The Missing Temporal Link: Temporal Context Routing
for Script-Driven Audio-Video Generation

Yichen Liu1, Quanwei Zhang2, Haozhe Wang3, Donghao Zhou4, Xiaojie Li
Yang Shi2, Jiaming Liu2, Ruihua Huang2, Yingtian Zou5, Daquan Zhou1

1 Peking University  ·  2 Qwen Applications
3 HKUST  ·  4 CUHK  ·  5 Shanghai Jiao Tong University

[![Project Page](https://img.shields.io/badge/Project-Page-4d86c4)](https://dagroup-pku.github.io/Temporal-Context-Routing.github.io/) [![GitHub](https://img.shields.io/badge/Code-GitHub-24292f?logo=github)](https://github.com/DAGroup-PKU/Temporal-Context-Routing) [![LoRA Weights](https://img.shields.io/badge/LoRA-Weights-ffbd2e?logo=huggingface)](https://huggingface.co/starry0929/Temporal-Context-Routing/blob/main/temporal-context-routing.safetensors) [![Test Prompts](https://img.shields.io/badge/Test-Prompts-2da44e)](https://huggingface.co/starry0929/Temporal-Context-Routing/blob/main/test_prompts_200.json)
**Temporal Context Routing (TCR)** aligns script-specified shot and dialogue timing with the shared video-audio timeline. Timing bypasses the text encoder and enters cross-attention logits as a routing score, separating *what* to generate from *when* it should appear. Built on LTX-2.3 22B, TCR reduces shot-boundary error from **1.11 s to 0.042 s**—about one frame at 24 fps—and raises dialogue timing accuracy from **28.3% to 84.1%**. This repository hosts the released **LoRA** (`temporal-context-routing.safetensors`, ~2.3 GB) and the **200 held-out test prompts** (`test_prompts_200.json`) used in the paper. Training and inference code is at [DAGroup-PKU/Temporal-Context-Routing](https://github.com/DAGroup-PKU/Temporal-Context-Routing). Demos are available on the [project page](https://dagroup-pku.github.io/Temporal-Context-Routing.github.io/). ## Files | File | What it is | | --- | --- | | `temporal-context-routing.safetensors` | TCR LoRA, rank 128, trained on LTX-2.3 22B (paper 7k-step recipe) | | `test_prompts_200.json` | 200 held-out script JSON files with per-shot / per-line `time_range` | You still need the **LTX-2.3 22B** checkpoint and the **Gemma 3 12B** text encoder locally. One 80 GB GPU is the working setup. ```bash huggingface-cli download starry0929/Temporal-Context-Routing \ temporal-context-routing.safetensors test_prompts_200.json \ --local-dir ./weights ``` Then follow the [code README](https://github.com/DAGroup-PKU/Temporal-Context-Routing#inference): ```bash bash scripts/infer.sh \ --checkpoint /path/to/ltx-2.3-22b-dev.safetensors \ --text-encoder-path /path/to/gemma-3-12b-it \ --lora-path ./weights/temporal-context-routing.safetensors \ --output outputs/tcr_infer.mp4 ``` ## Citation ```bibtex @inproceedings{liu2027missingtemporallink, title = {The Missing Temporal Link: Temporal Context Routing for Script-Driven Audio-Video Generation}, author = {Liu, Yichen and Zhang, Quanwei and Wang, Haozhe and Zhou, Donghao and Li, Xiaojie and Shi, Yang and Liu, Jiaming and Huang, Ruihua and Zou, Yingtian and Zhou, Daquan}, booktitle = {Under review}, year = {2027} } ``` ## License The LoRA is trained on LTX-2.3 and is intended to be used with that backbone under the [LTX-2 Community License](https://github.com/DAGroup-PKU/Temporal-Context-Routing/blob/main/LICENSE).