Separating What from When
Fine-Grained Temporal Control for Joint Audio-Video Generation
Yichen Liu1 路 Quanwei Zhang2 路 Haozhe Wang3 路 Donghao Zhou4 路 Xiaojie Li 路 Yang Shi2 路 Jiaming Liu2 路 Ruihua Huang2 路 Yingtian Zou5 路 Daquan Zhou1
1Peking University 路 2Qwen Business Unit of Alibaba 路 3HKUST 路 4CUHK 路 5Shanghai Jiao Tong University
Temporal Context Routing (TCR) adds a timing term to text-attention logits so picture and speech are generated as two streams against one shared clock. This repo hosts the released LoRA (separating-what-from-when.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/SEPARATING-WHAT-FROM-WHEN. Demos: project page.
Files
| File | What it is |
|---|---|
separating-what-from-when.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.
huggingface-cli download starry0929/Separating-What-From-When \
separating-what-from-when.safetensors test_prompts_200.json \
--local-dir ./weights
Then follow the code README:
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/separating-what-from-when.safetensors \
--output outputs/tcr_infer.mp4
Citation
@inproceedings{liu2027separating,
title = {Separating What from When: Fine-Grained Temporal Control
for Joint 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.