Pith Number

pith:CDU5EXKT

pith:2026:CDU5EXKTMXISG6ZBLQGIKAZVCY

not attested not anchored not stored refs pending

BareBones: Benchmarking Zero-Shot Geometric Comprehension in VLMs

Aaditya Baranwal, Abhishek Rajora, Vishal Yadav

Current vision-language models lack genuine geometric comprehension and instead rely on texture and contextual shortcuts.

arxiv:2604.10528 v4 · 2026-04-12 · cs.CV

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\usepackage{pith}
\pithnumber{CDU5EXKTMXISG6ZBLQGIKAZVCY}

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Record completeness

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Our evaluation of 26 state-of-the-art proprietary and open-weight VLMs (eg. GPT-4.1, Gemini, Claude Sonnet 4.5, LLaVA) reveals a consistent, severe performance collapse under RGB deprivation, a phenomenon we term the Texture Bias Cliff.

C2weakest assumption

That the curated pixel-level silhouettes and WTP-Bench taxonomy are truly noise-free and isolate geometric structure without inadvertently leaking semantic, contextual, or annotation cues that models could exploit.

C3one line summary

VLMs exhibit a consistent 'Texture Bias Cliff' and fail to comprehend pure geometric shapes from boundary contours alone in zero-shot settings.

Receipt and verification

First computed	2026-06-02T01:03:46.875372Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

10e9d25d5365d1237b215c0c8503351615a2c2c09fb537882eb2bb0c9bd2c997

Aliases

arxiv: 2604.10528 · arxiv_version: 2604.10528v4 · doi: 10.48550/arxiv.2604.10528 · pith_short_12: CDU5EXKTMXIS · pith_short_16: CDU5EXKTMXISG6ZB · pith_short_8: CDU5EXKT

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/CDU5EXKTMXISG6ZBLQGIKAZVCY \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 10e9d25d5365d1237b215c0c8503351615a2c2c09fb537882eb2bb0c9bd2c997

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "e9dfbca550e96d0b69b7394c76c6a98d6a71239f85b26a8aac0c1d270a84ba48",
    "cross_cats_sorted": [],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CV",
    "submitted_at": "2026-04-12T08:46:27Z",
    "title_canon_sha256": "19abdaacccdd5cef35641ef8f7ad87c370cc685ea3b0b226b35c30a7d439689f"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.10528",
    "kind": "arxiv",
    "version": 4
  }
}