Robotics
Transformers
File size: 7,907 Bytes
6ace148
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
19e05fc
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
d39ca20
 
 
19e05fc
d39ca20
 
 
 
 
 
 
 
 
 
19e05fc
 
 
 
 
d39ca20
 
 
 
 
 
 
 
 
 
 
 
 
 
19e05fc
 
 
 
 
 
 
 
d39ca20
 
 
 
 
 
 
 
 
 
 
 
 
 
19e05fc
 
 
 
 
d39ca20
 
 
 
 
 
 
 
 
 
 
 
 
 
19e05fc
 
 
 
 
d39ca20
 
 
 
 
 
 
 
 
 
 
 
 
 
19e05fc
 
 
 
 
d39ca20
 
 
 
 
 
 
 
 
 
 
 
 
 
19e05fc
 
 
 
 
d39ca20
 
 
 
 
 
 
 
 
 
 
 
 
 
19e05fc
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
---
license: mit
pipeline_tag: robotics
library_name: transformers
---

# VLN-PE Benchmark Models

This repository hosts models and results for the [Rethinking the Embodied Gap in Vision-and-Language Navigation: A Holistic Study of Physical and Visual Disparities](https://huggingface.co/papers/2507.13019) benchmark.

VLN-PE is a physically realistic Vision-and-Language Navigation (VLN) platform supporting humanoid, quadruped, and wheeled robots. It aims to bridge the gap between idealized assumptions and physical deployment challenges in VLN, systematically evaluating ego-centric VLN methods across different technical pipelines.

*   **Project Page**: https://crystalsixone.github.io/vln_pe.github.io/
*   **Code Repository**: https://github.com/InternRobotics/InternNav

## Benchmark Results

The following table presents the benchmark results for various models evaluated on the VLN-PE platform:

**VLN-PE Benchmark**
<style type="text/css">
.tg  {border-collapse:collapse;border-spacing:0;}
.tg td{border-color:black;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;
  overflow:hidden;padding:10px 5px;word-break:normal;}
.tg th{border-color:black;border-style:solid;border-width:1px;font-family:Arial, sans-serif;font-size:14px;
  font-weight:normal;overflow:hidden;padding:10px 5px;word-break:normal;}
.tg .tg-c3ow{border-color:inherit;text-align:center;vertical-align:top}
.tg .tg-0pky{border-color:inherit;text-align:left;vertical-align:top}
.tg .tg-fymr{border-color:inherit;font-weight:bold;text-align:left;vertical-align:top}
</style>
<table class="tg"><thead>
  <tr>
    <th class="tg-c3ow" rowspan="2"><span style="font-weight:bold">Model</span></th>
    <th class="tg-0pky" rowspan="2"><span style="font-weight:bold">Dataset/Benchmark</span></th>
    <th class="tg-c3ow" colspan="7"><span style="font-weight:bold">Val Seen</span></th>
    <th class="tg-c3ow" colspan="7"><span style="font-weight:bold">Val Unseen</span></th>
    <th class="tg-fymr" rowspan="2">Download</th>
  </tr>
  <tr>
    <th class="tg-fymr">TL</th>
    <th class="tg-fymr">NE</th>
    <th class="tg-fymr">FR</th>
    <th class="tg-fymr">StR</th>
    <th class="tg-fymr">OS</th>
    <th class="tg-fymr">SR</th>
    <th class="tg-fymr">SPL</th>
    <th class="tg-fymr">TL</th>
    <th class="tg-fymr">NE</th>
    <th class="tg-fymr">FR</th>
    <th class="tg-fymr">StR</th>
    <th class="tg-fymr">OS</th>
    <th class="tg-fymr">SR</th>
    <th class="tg-fymr">SPL</th>
  </tr></thead>
<tbody>
  <tr>
    <td class="tg-c3ow" colspan="17">Zero-shot transfer evaluation from VLN-CE</td>
  </tr>
  <tr>
    <td class="tg-0pky">Seq2Seq-Full</td>
    <td class="tg-0pky">R2R VLN-PE</td>
    <td class="tg-0pky">7.80</td>
    <td class="tg-0pky">7.62</td>
    <td class="tg-0pky">20.21</td>
    <td class="tg-0pky">3.04</td>
    <td class="tg-0pky">19.3</td>
    <td class="tg-0pky">15.2</td>
    <td class="tg-0pky">12.79</td>
    <td class="tg-0pky">7.73</td>
    <td class="tg-0pky">7.18</td>
    <td class="tg-0pky">18.04</td>
    <td class="tg-0pky">3.04</td>
    <td class="tg-0pky">22.42</td>
    <td class="tg-0pky">16.48</td>
    <td class="tg-0pky">14.11</td>
    <td class="tg-0pky"><a href="https://huggingface.co/InternRobotics/VLN-PE/tree/main/r2r/zero_shot/seq2seq" target="_blank" rel="noopener noreferrer">model</a></td>
  </tr>
  <tr>
    <td class="tg-0pky">CMA-Full</td>
    <td class="tg-0pky">R2R VLN-PE</td>
    <td class="tg-0pky">6.62</td>
    <td class="tg-0pky">7.37</td>
    <td class="tg-0pky">20.06</td>
    <td class="tg-0pky">3.95</td>
    <td class="tg-0pky">18.54</td>
    <td class="tg-0pky">16.11</td>
    <td class="tg-0pky">14.61</td>
    <td class="tg-0pky">6.58</td>
    <td class="tg-0pky">7.09</td>
    <td class="tg-0pky">17.07</td>
    <td class="tg-0pky">3.79</td>
    <td class="tg-0pky">20.86</td>
    <td class="tg-0pky">16.93</td>
    <td class="tg-0pky">15.24</td>
    <td class="tg-0pky"><a href="https://huggingface.co/InternRobotics/VLN-PE/tree/main/r2r/zero_shot/cma" target="_blank" rel="noopener noreferrer">model</a></td>
  </tr>
  <tr>
    <td class="tg-c3ow" colspan="17">Train on VLN-PE</td>
  </tr>
  <tr>
    <td class="tg-0pky">Seq2Seq</td>
    <td class="tg-0pky">R2R VLN-PE</td>
    <td class="tg-0pky">10.61</td>
    <td class="tg-0pky">7.53</td>
    <td class="tg-0pky">27.36</td>
    <td class="tg-0pky">4.26</td>
    <td class="tg-0pky">32.67</td>
    <td class="tg-0pky">19.75</td>
    <td class="tg-0pky">14.68</td>
    <td class="tg-0pky">10.85</td>
    <td class="tg-0pky">7.88</td>
    <td class="tg-0pky">26.8</td>
    <td class="tg-0pky">5.57</td>
    <td class="tg-0pky">28.13</td>
    <td class="tg-0pky">15.14</td>
    <td class="tg-0pky">10.77</td>
    <td class="tg-0pky"><a href="https://huggingface.co/InternRobotics/VLN-PE/tree/main/r2r/fine_tuned/seq2seq" target="_blank" rel="noopener noreferrer">model</a></td>
  </tr>
  <tr>
    <td class="tg-0pky">CMA</td>
    <td class="tg-0pky">R2R VLN-PE</td>
    <td class="tg-0pky">11.13</td>
    <td class="tg-0pky">7.59</td>
    <td class="tg-0pky">23.71</td>
    <td class="tg-0pky">3.19</td>
    <td class="tg-0pky">34.94</td>
    <td class="tg-0pky">21.58</td>
    <td class="tg-0pky">16.1</td>
    <td class="tg-0pky">11.16</td>
    <td class="tg-0pky">7.98</td>
    <td class="tg-0pky">22.64</td>
    <td class="tg-0pky">3.27</td>
    <td class="tg-0pky">33.11</td>
    <td class="tg-0pky">19.15</td>
    <td class="tg-0pky">14.05</td>
    <td class="tg-0pky"><a href="https://huggingface.co/InternRobotics/VLN-PE/tree/main/r2r/fine_tuned/cma" target="_blank" rel="noopener noreferrer">model</a></td>
  </tr>
  <tr>
    <td class="tg-0pky">RDP</td>
    <td class="tg-0pky">R2R VLN-PE</td>
    <td class="tg-0pky">13.26</td>
    <td class="tg-0pky">6.76</td>
    <td class="tg-0pky">27.51</td>
    <td class="tg-0pky">1.82</td>
    <td class="tg-0pky">38.6</td>
    <td class="tg-0pky">25.08</td>
    <td class="tg-0pky">17.07</td>
    <td class="tg-0pky">12.7</td>
    <td class="tg-0pky">6.72</td>
    <td class="tg-0pky">24.57</td>
    <td class="tg-0pky">3.11</td>
    <td class="tg-0pky">36.9</td>
    <td class="tg-0pky">25.24</td>
    <td class="tg-0pky">17.73</td>
    <td class="tg-0pky"><a href="https://huggingface.co/InternRobotics/VLN-PE/tree/main/r2r/fine_tuned/rdp" target="_blank" rel="noopener noreferrer">model</a></td>
  </tr>
  <tr>
    <td class="tg-0pky">Seq2Seq+</td>
    <td class="tg-0pky">R2R VLN-PE</td>
    <td class="tg-0pky">10.22</td>
    <td class="tg-0pky">7.75</td>
    <td class="tg-0pky">33.43</td>
    <td class="tg-0pky">3.19</td>
    <td class="tg-0pky">30.09</td>
    <td class="tg-0pky">16.86</td>
    <td class="tg-0pky">12.54</td>
    <td class="tg-0pky">9.88</td>
    <td class="tg-0pky">7.85</td>
    <td class="tg-0pky">26.27</td>
    <td class="tg-0pky">6.52</td>
    <td class="tg-0pky">28.79</td>
    <td class="tg-0pky">16.56</td>
    <td class="tg-0pky">12.7</td>
    <td class="tg-0pky"><a href="https://huggingface.co/InternRobotics/VLN-PE/tree/main/r2r/fine_tuned/seq2seq_plus" target="_blank" rel="noopener noreferrer">model</a></td>
  </tr>
  <tr>
    <td class="tg-0pky">CMA+</td>
    <td class="tg-0pky">R2R VLN-PE</td>
    <td class="tg-0pky">8.86</td>
    <td class="tg-0pky">7.14</td>
    <td class="tg-0pky">23.56</td>
    <td class="tg-0pky">3.5</td>
    <td class="tg-0pky">36.17</td>
    <td class="tg-0pky">25.84</td>
    <td class="tg-0pky">21.75</td>
    <td class="tg-0pky">8.79</td>
    <td class="tg-0pky">7.26</td>
    <td class="tg-0pky">21.75</td>
    <td class="tg-0pky">3.27</td>
    <td class="tg-0pky">31.4</td>
    <td class="tg-0pky">22.12</td>
    <td class="tg-0pky">18.65</td>
    <td class="tg-0pky"><a href="https://huggingface.co/InternRobotics/VLN-PE/tree/main/r2r/fine_tuned/cma_plus" target="_blank" rel="noopener noreferrer">model</a></td>
  </tr>
</tbody></table>