---
library_name: transformers
pipeline_tag: image-text-to-text
base_model: Qwen/Qwen3.5-4B
tags:
- gui-agent
- computer-use
- trajectory-memory
- rag
---
# memrag-mem — Trajectory-Memory RAG (GUI agent)

Cold-start SFT from **Qwen3.5-4B** for GUI next-action prediction. This checkpoint = the **retrieved trajectory memory (main result)** arm of a 3-arm A/B.

**Action accuracy (n=498 test, AgentNetBench score_pair):** `0.556` — **+19.0pp** vs basecur, **+8.6pp** vs basefull; usage-gap **+11.4pp** (memory is genuinely used)

| arm | action acc (n=498) |
|---|---|
| basecur (current only) | 0.366 |
| basefull (full history) | 0.470 |
| **mem (retrieved memory)** | **0.556** |

**Status: v1, single-seed** (positive; 3-seed confirmation pending). See the collection for the other arms.

## Load
```python
from transformers import AutoProcessor
from qwen_cua.modeling_qwen35_vl_latent import Qwen35VLLatentForConditionalGeneration as M
proc  = AutoProcessor.from_pretrained("hyunseoki/memrag-mem", max_pixels=1_000_000)
model = M.from_pretrained("hyunseoki/memrag-mem", torch_dtype="bfloat16", attn_implementation="flash_attention_2")
```
Plain Qwen3.5-VL arch (`wm.enabled=false`) — also loadable with the standard class.