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README.md

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----
-license: cc-by-4.0
----
+---
+license: cc-by-4.0
+task_categories:
+  - image-to-text
+  - visual-question-answering
+tags:
+  - Multimodal benchmark
+  - Vision-Language Models
+  - Compositionality
+  - Localism-aware compositionality
+  - Multimodal knowledge editing
+---
+
+# LACE-Bench: Localism-Aware Compositionality Evaluation Benchmark for Vision-Language Models
+
+> **LACE-Bench** is a benchmark for evaluating *localism-aware compositionality* in vision-language models (VLMs) — the ability to selectively integrate local region-level semantics with global scene-level understanding. It comprises two complementary tasks: **LoGoCap** and **MMComE**.
+
+## Dataset Card
+
+| Field | Info |
+|---|---|
+| **Tasks** | LoGoCap (Local & Global Compositional Captioning), MMComE (Multimodal Compositional Knowledge Editing) |
+| **Modality** | Vision-Language |
+| **Split** | Train (9,874 images) / Test (2,183 images) |
+| **Total** | 12,057 images |
+| **Image Source** | [Visual Genome](https://homes.cs.washington.edu/~ranjay/visualgenome/api.html) |
+| **License** | CC BY 4.0 |
+
+<!-- 
+## Tasks
+
+### 1. LoGoCap — Multi-grained Local and Global Compositional Captioning
+
+LoGoCap evaluates a model's *static selectivity*: can it simultaneously understand the global scene while identifying and grounding constituent local objects?
+
+- **Local captioning**: given an atomic region (a single object marked with a colored bounding box), generate a region-specific caption.
+- **Global captioning**: given a compound region (a group of atomic regions), generate a single coherent caption that integrates all constituent local parts while introducing holistic scene-level context (moods, relations, atmosphere) not present in any individual local caption.
+
+Evaluation uses standard captioning metrics (BLEU, ROUGE-1, METEOR) against human-annotated reference captions.
+
+### 2. MMComE — Multimodal Compositional Knowledge Editing
+
+MMComE evaluates a model's *dynamic robustness*: can it apply a localized counterfactual edit (e.g., replacing *referee* with *spectator*) consistently across region-marked images, while preserving all unrelated global semantics?
+
+A multimodal edit request is defined as a tuple `(I, r, ph → ph*)`, where:
+- `I` is the image, `r` is the target region
+- `ph` is the original phrase to be replaced, `ph*` is the counterfactual substitute
+
+The model is evaluated on whether it correctly reflects `ph*` in both in-scope regions (edited) and correctly retains all out-of-scope regions (unedited).
+
+
+## Intended Use
+
+LACE-Bench is designed for:
+
+- Evaluating **localism-aware compositionality** — whether VLMs can selectively deploy local and global compositional operations as the task demands
+- Measuring **global binding stability**: how consistently local semantic units of atomic regions bind into global captions
+- Quantifying **cross-scale interference**: the degree to which local counterfactual edits propagate into unintended global semantic regions
+- Benchmarking **fine-tuning strategies** (e.g., LoRA, blur+bbox visual grounding) for compositional captioning -->
+
+
+## Data Fields
+
+Each record corresponds to one image and contains the following fields:
+
+| Field | Type | Description |
+|---|---|---|
+| `image_id` | string | Visual Genome image identifier |
+| `regions` | list[object] | Annotated bounding box regions (atomic) |
+| `narratives` | string | Description of the full image |
+| `keywords` | list[object] | Key noun concepts grounded in WordNet |
+| `relation_centric_regions` | list[object] | Groups of region IDs with a human-written relational annotation |
+
+### `regions`
+
+Each atomic region corresponds to a single object marked with a distinct colored bounding box.
+
+| Key | Type | Description |
+|---|---|---|
+| `id` | string | Region identifier (`{image_id}_{region_index}`) |
+| `color` | string | Bounding box color used for visual grounding (aqua / yellow / lime / red / blue / orange / magenta) |
+| `x`, `y` | float | Top-left corner coordinates of the bounding box |
+| `width`, `height` | float | Width and height of the bounding box |
+| `captions` | list[object] | Human-annotated region-level captions (see below) |
+| `object_ids` | list[int] | Linked object IDs from Visual Genome |
+| `relationships` | list[object] | Scene graph relationships associated with this region (see below) |
+
+**`regions[].captions`**
+
+| Key | Type | Description |
+|---|---|---|
+| `caption` | string | Original human-written caption for the region (e.g. `"the tall clock on the street"`) |
+| `counterfactual_caption` | string | Minimally edited caption where one noun is replaced with a plausible but incorrect alternative (e.g. `"the tall dart board on the street"`) |
+
+**`regions[].relationships`**
+
+| Key | Type | Description |
+|---|---|---|
+| `relationship_id` | int | Visual Genome relationship identifier |
+| `predicate` | string | Relation predicate between subject and object (e.g. `"on"`) |
+| `synsets` | list[string] | WordNet synsets for the predicate (e.g. `["along.r.01"]`) |
+| `subject_id` | int | Visual Genome object ID of the subject |
+| `object_id` | int | Visual Genome object ID of the object |
+
+---
+
+### `keywords`
+
+Each entry represents a key noun concept extracted from region captions and grounded in WordNet.
+
+| Key | Type | Description |
+|---|---|---|
+| `synset_id` | string | WordNet synset identifier (e.g. `clock.n.01`) |
+| `synonyms` | list[string] | Lemma names belonging to this synset (e.g. `["clock"]`) |
+| `nearest_ancestor` | string | Closest hypernym synset in the WordNet hierarchy (e.g. `timepiece.n.01`) |
+| `supersense` | string | Broad semantic category from WordNet lexicographer files (e.g. `noun.artifact`, `noun.person`) |
+| `counterfactual` | list[object] | Human-annotated counterfactual substitutions for this concept (see below) |
+
+**`keywords[].counterfactual`**
+
+| Key | Type | Description |
+|---|---|---|
+| `human_annotation` | string | Plausible but incorrect substitute chosen by a human annotator (e.g. `"dart board"`) |
+| `candidate` | list[string] | Candidate substitutions presented to the annotator for selection |
+
+> `counterfactual` is empty (`[]`) for concepts where no counterfactual annotation was collected.
+
+---
+
+### `relation_centric_regions`
+
+Each entry groups multiple atomic regions and provides a human-written description of the relational context among them.
+
+| Key | Type | Description |
+|---|---|---|
+| `human_annotation` | string | Free-form description of the spatial or semantic relationship among the grouped regions (e.g. `"The central clock tower... stands as a focal point against the backdrop of the building's pillars."`) |
+| `region_ids` | list[string] | IDs of the atomic regions involved in this relational group (e.g. `["2358647_0", "2358647_1"]`) |
+
+
+## Citation
+
+```bibtex
+@dataset{anonymous2026lacebench,
+  title  = {LACE-Bench: Localism-Aware Compositionality Evaluation Benchmark for Vision-Language Models},
+  author = {Anonymous},
+  year   = {2026},
+}
+```

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