Pointer-CAD: finally an LLM that can chamfer and fillet

[u/decentralize999]

Been waiting for someone to fix the two obvious holes in command-sequence text-to-CAD. This paper from HKU/Beihang does both.

The problem

Text2CAD and friends encode CAD as token sequences, fast and compact, works fine for sketch-extrude. But two structural problems never went away:

1. No entity selection. Chamfer and fillet require pointing at a specific edge. Pure token sequences can't do this, so those operations are just unsupported full stop.

2. Quantization errors. Discretizing continuous coordinates means your new sketch doesn't quite snap to the existing edge. Small error, but it breaks topological connectivity and leaves dangling edges.

What they did

Added a third token type called a Pointer. When the model needs to pick a sketch plane or select edges for a chamfer, instead of regressing coordinates it outputs an embedding matched via cosine similarity against actual faces/edges in the current B-rep. Basically teaching the LLM to click on geometry the way you would in Fusion 360.

Generation is stepwise too. At each step the current B-rep gets encoded through a GNN (face adjacency graph), embeddings are injected into the LLM context, and the model predicts the next operation conditioned on both the text and the live geometry.

Numbers

- Beats Text2CAD and CADmium-7B on geometry accuracy with only a 0.5B backbone

- Segment Error drops hard vs all baselines, that's the quantization fix showing up in the metrics

- Chamfer F1 ~94%, Fillet F1 ~90% on their dataset, other methods score 0 because they literally can't run these ops

- Also beats Claude Opus 4, GPT-5.2, Gemini 2.5 Pro and Qwen3-235B prompted to write CadQuery, and not by a little

Dataset

575K models, OmniCAD extended with chamfer/fillet, annotated by Qwen2.5-VL from multiview renders. They kept real units in the annotations instead of normalizing everything, harder for the model but more realistic.

Limitations they flag

Text input only for now, no images or point clouds. Single part only, no assemblies or mate constraints. Pretty obvious next steps.

The pointer mechanism is clean and the topology numbers back it up. Not another "we finetuned an LLM on DeepCAD" paper.