# VA-Bench：通过视觉演示、主动感知与度量控制评测具身空间智能

- 来源：HuggingFace Daily Papers（社区热门论文）
- 发布时间：2026-09-17 08:00
- AIHOT 分数：43
- AIHOT 链接：https://aihot.news/items/cmu6ds2t20kqfrofjv2mtgdu8
- 原文链接：https://arxiv.org/abs/2609.19554

## AI 摘要

VA-Bench 发布，用于评测 MLLM 的完整“观察-推理-行动-修正”闭环，模型仅凭 RGB 演示学习流程并主动选择相机视角、发出笛卡尔度量指令。基准含 14 个基础任务族、7 个留出几何/布局变体和五物体长程组合赛道，最佳模型三次运行宏平均任务成功率仅 53.93±3.17%。

## 正文

Spatial intelligence requires more than describing object locations. Under incomplete observation, models must identify and acquire missing evidence, interpret it in a common spatial frame, and act on it. We introduce VA-Bench to evaluate the complete observe-reason-act-revise loop. General-purpose MLLMs learn procedural context from RGB-only demonstrations, actively select camera viewpoints, issue metric Cartesian commands, and revise them from execution feedback. Models receive no privileged object poses, oracle trajectories, or learned action heads.

A fixed model-agnostic controller executes only model-specified targets. VA-Bench contains 14 base task families (11 single-arm and three dual-arm), seven held-out geometry/layout variants, and a long-horizon five-object composition track. We evaluate 12 primary model conditions in three independent runs over the same 20 physically verified seeds per base task, reporting terminal success, nine trajectory-level behavioral diagnostics, and subtask progress. First, the best-performing model scores 100.0% on target localization and 78.9% on spatial relations in the annotated run.

Its three-run macro-average task success is only 53.93+/-3.17%. Second, active camera control significantly improves task success over passive multi-view observation. In one matched comparison, success rises from 27.86% to 57.50%. Third, held-out geometric transfer can reduce task success by over 30 percentage points. No model completes a strict long-horizon episode, despite substantial partial progress. VA-Bench thus tests whether general-purpose MLLMs can turn visual demonstrations and actively acquired evidence into successful embodied action.