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pith:2NJ4TGRP

pith:2026:2NJ4TGRPZFGF56BVIPUHRD5APF
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VLRS-Bench: A Vision-Language Reasoning Benchmark for Remote Sensing

Bo Du, Di Wang, Haonan Guo, Jing Zhang, Zhiming Luo

VLRS-Bench is the first benchmark built exclusively for complex vision-language reasoning in remote sensing.

arxiv:2602.07045 v2 · 2026-02-04 · cs.CV · cs.AI

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\usepackage{pith}
\pithnumber{2NJ4TGRPZFGF56BVIPUHRD5APF}

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3 Author claim open · sign in to claim
4 Citations open
5 Replications open
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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

VLRS-Bench is the first benchmark exclusively dedicated to complex RS reasoning.

C2weakest assumption

The specialized pipeline that integrates RS-specific priors and expert knowledge produces questions with genuine geospatial realism and reasoning complexity.

C3one line summary

VLRS-Bench is the first benchmark dedicated to complex vision-language reasoning in remote sensing, with 2000 QA pairs across 14 tasks in cognition, decision, and prediction dimensions.

References

66 extracted · 66 resolved · 9 Pith anchors

[1] Choice: Benchmarking the remote sensing capabilities of large vision-language models 2025
[2] Qwen2.5-VL Technical Report 2025 · arXiv:2502.13923
[3] Dota 2 with Large Scale Deep Reinforcement Learning 1912 · arXiv:1912.06680
[4] Towards injecting medical vi- sual knowledge into multimodal llms at scale 2024
[5] Are We on the Right Way for Evaluating Large Vision-Language Models? · arXiv:2403.20330
Receipt and verification
First computed 2026-05-17T23:39:16.275681Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

d353c99a2fc94c5ef83543e8788fa07954fab7d6bd20d4b69f26e2ed32a542a4

Aliases

arxiv: 2602.07045 · arxiv_version: 2602.07045v2 · doi: 10.48550/arxiv.2602.07045 · pith_short_12: 2NJ4TGRPZFGF · pith_short_16: 2NJ4TGRPZFGF56BV · pith_short_8: 2NJ4TGRP
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/2NJ4TGRPZFGF56BVIPUHRD5APF \
  | 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: d353c99a2fc94c5ef83543e8788fa07954fab7d6bd20d4b69f26e2ed32a542a4
Canonical record JSON
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    "submitted_at": "2026-02-04T08:21:33Z",
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