We introduce ReRef-3D, a benchmark for language-guided single-object placement in controlled 3D tabletop scenes. It contains 33,826 instructions across 998 CLEVR-derived scenes, spanning 16 placement types and direct, one-hop, and two-hop references. Given that an instruction defines a region of acceptable placements rather than one coordinate, predictions are evaluated by relation satisfaction and physical validity. Each instruction also includes a verified natural rephrasing. We evaluate LLaVA-3D, 3D-LLM, 3D-LLaVA, LL3DA, and PlaceIt3D, with PlaceIt3D evaluated under both point-based and region-based supervision. Region-supervised PlaceIt3D achieves the highest placement accuracy at about 80% and LLaVA-3D reaches about 70%. Performance varies by relation type, but nearest and aligned remain the most difficult. Rephrasing has little effect on performance overall.

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