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@@ -108,11 +108,8 @@ bash scripts/spatialvla_4b_finetune/finetune_lora.sh
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  ```
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  ## Evaluation
 
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- <details>
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- <summary>
114
- SimplerEnv evaluation on Google Robot tasks.
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- </summary>
116
  <table border="1" class="dataframe">
117
  <thead>
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  <tr style="text-align: center;">
@@ -278,137 +275,131 @@ bash scripts/spatialvla_4b_finetune/finetune_lora.sh
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  </tbody>
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  </table>
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- </details>
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-
283
-
284
- <details>
285
- <summary>
286
- SimplerEnv evaluation on WidowX Robot tasks.
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- </summary>
288
- <table border="1" class="dataframe">
289
- <thead>
290
- <tr style="text-align: center;">
291
- <th rowspan="2">Model</th>
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- <th colspan="2">Put Spoon on Towel</th>
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- <th colspan="2">Put Carrot on Plate</th>
294
- <th colspan="2">Stack Green Block on Yellow Block</th>
295
- <th colspan="2">Put Eggplant in Yellow Basket</th>
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- <th rowspan="2">#Overall Average</th>
297
- </tr>
298
- <tr style="text-align: center;">
299
- <th>Grasp Spoon</th>
300
- <th>Success</th>
301
- <th>Grasp Carrot</th>
302
- <th>Success</th>
303
- <th>Grasp Green Block</th>
304
- <th>Success</th>
305
- <th>Grasp Eggplant</th>
306
- <th>Success</th>
307
- </tr>
308
- </thead>
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- <tbody>
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- <tr>
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- <td>RT-1-X</td>
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- <td>16.7%</td>
313
- <td>0.0%</td>
314
- <td>20.8%</td>
315
- <td>4.2%</td>
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- <td>8.3%</td>
317
- <td>0.0%</td>
318
- <td>0.0%</td>
319
- <td>0.0%</td>
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- <td>1.1%</td>
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- </tr>
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- <tr>
323
- <td>Octo-Base</td>
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- <td>34.7%</td>
325
- <td>12.5%</td>
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- <td>52.8%</td>
327
- <td>8.3%</td>
328
- <td>31.9%</td>
329
- <td>0.0%</td>
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- <td>66.7%</td>
331
- <td>43.1%</td>
332
- <td>16.0%</td>
333
- </tr>
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- <tr>
335
- <td>Octo-Small</td>
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- <td>77.8%</td>
337
- <td>47.2%</td>
338
- <td>27.8%</td>
339
- <td>9.7%</td>
340
- <td>40.3%</td>
341
- <td>4.2%</td>
342
- <td>87.5%</td>
343
- <td>56.9%</td>
344
- <td>30.0%</td>
345
- </tr>
346
- <tr>
347
- <td>OpenVLA</td>
348
- <td>4.1%</td>
349
- <td>0.0%</td>
350
- <td>33.3%</td>
351
- <td>0.0%</td>
352
- <td>12.5%</td>
353
- <td>0.0%</td>
354
- <td>8.3%</td>
355
- <td>4.1%</td>
356
- <td>1.0%</td>
357
- </tr>
358
- <tr>
359
- <td>RoboVLM (zero-shot)</td>
360
- <td>37.5%</td>
361
- <td>20.8%</td>
362
- <td>33.3%</td>
363
- <td>25.0%</td>
364
- <td>8.3%</td>
365
- <td>8.3%</td>
366
- <td>0.0%</td>
367
- <td>0.0%</td>
368
- <td>13.5%</td>
369
- </tr>
370
- <tr>
371
- <td>RoboVLM (fine-tuning)</td>
372
- <td>54.2%</td>
373
- <td>29.2%</td>
374
- <td>25.0%</td>
375
- <td>25.0%</td>
376
- <td>45.8%</td>
377
- <td>12.5%</td>
378
- <td>58.3%</td>
379
- <td>58.3%</td>
380
- <td>31.3%</td>
381
- </tr>
382
- <tr>
383
- <td>SpatialVLA (zero-shot)</td>
384
- <td><b>25.0%</b></td>
385
- <td><b>20.8%</b></td>
386
- <td><b>41.7%</b></td>
387
- <td>20.8%</td>
388
- <td><b>58.3%</b></td>
389
- <td>25.0%</td>
390
- <td><b>79.2%</b></td>
391
- <td>70.8%</td>
392
- <td><b>34.4%</b></td>
393
- </tr>
394
- <tr>
395
- <td>SpatialVLA (fine-tuning)</td>
396
- <td><b>20.8%</b></td>
397
- <td>16.7%</td>
398
- <td>29.2%</td>
399
- <td>25.0%</td>
400
- <td><b>62.5%</b></td>
401
- <td>29.2%</td>
402
- <td><b>100.0%</b></td>
403
- <td><b>100.0%</b></td>
404
- <td><b>42.7%</b></td>
405
- </tr>
406
- </tbody>
407
- </table>
408
- </details>
409
-
410
- <details>
411
- <summary>LIBERO Simulation Benchmark Results.</summary>
412
  <table border="1" class="dataframe">
413
  <thead>
414
  <tr style="text-align: center;">
@@ -501,22 +492,20 @@ bash scripts/spatialvla_4b_finetune/finetune_lora.sh
501
  </tbody>
502
  </table>
503
 
504
- </details>
 
 
 
 
 
 
 
 
505
 
506
- <details>
507
- <summary>Zero-shot Robot Control Evaluation on WidowX Robot.</summary>
508
- <img src="https://cdn-uploads.huggingface.co/production/uploads/6535045a910b844786a6642f/SUPyXwcdfnWranO04tulL.png" alt="perform">
509
- </details>
510
 
511
- <details>
512
- <summary>Spatial Understanding Capability Evaluation..</summary>
513
- <img src="https://cdn-uploads.huggingface.co/production/uploads/6535045a910b844786a6642f/g-EfM-6M7iM9IYryUTwLA.png" alt="perform">
514
- </details>
515
 
516
- <details>
517
- <summary>Adapting to New Robot Setups on Franka Robot.</summary>
518
- <img src="https://cdn-uploads.huggingface.co/production/uploads/6535045a910b844786a6642f/4Z_vjQvsDGUcHCwmBCtRa.png" alt="perform">
519
- </details>
520
 
521
 
522
  ## Citation
 
108
  ```
109
 
110
  ## Evaluation
111
+ - SimplerEnv evaluation on Google Robot tasks.
112
 
 
 
 
 
113
  <table border="1" class="dataframe">
114
  <thead>
115
  <tr style="text-align: center;">
 
275
  </tbody>
276
  </table>
277
 
278
+ - SimplerEnv evaluation on WidowX Robot tasks.
279
+
280
+ <table border="1" class="dataframe">
281
+ <thead>
282
+ <tr style="text-align: center;">
283
+ <th rowspan="2">Model</th>
284
+ <th colspan="2">Put Spoon on Towel</th>
285
+ <th colspan="2">Put Carrot on Plate</th>
286
+ <th colspan="2">Stack Green Block on Yellow Block</th>
287
+ <th colspan="2">Put Eggplant in Yellow Basket</th>
288
+ <th rowspan="2">#Overall Average</th>
289
+ </tr>
290
+ <tr style="text-align: center;">
291
+ <th>Grasp Spoon</th>
292
+ <th>Success</th>
293
+ <th>Grasp Carrot</th>
294
+ <th>Success</th>
295
+ <th>Grasp Green Block</th>
296
+ <th>Success</th>
297
+ <th>Grasp Eggplant</th>
298
+ <th>Success</th>
299
+ </tr>
300
+ </thead>
301
+ <tbody>
302
+ <tr>
303
+ <td>RT-1-X</td>
304
+ <td>16.7%</td>
305
+ <td>0.0%</td>
306
+ <td>20.8%</td>
307
+ <td>4.2%</td>
308
+ <td>8.3%</td>
309
+ <td>0.0%</td>
310
+ <td>0.0%</td>
311
+ <td>0.0%</td>
312
+ <td>1.1%</td>
313
+ </tr>
314
+ <tr>
315
+ <td>Octo-Base</td>
316
+ <td>34.7%</td>
317
+ <td>12.5%</td>
318
+ <td>52.8%</td>
319
+ <td>8.3%</td>
320
+ <td>31.9%</td>
321
+ <td>0.0%</td>
322
+ <td>66.7%</td>
323
+ <td>43.1%</td>
324
+ <td>16.0%</td>
325
+ </tr>
326
+ <tr>
327
+ <td>Octo-Small</td>
328
+ <td>77.8%</td>
329
+ <td>47.2%</td>
330
+ <td>27.8%</td>
331
+ <td>9.7%</td>
332
+ <td>40.3%</td>
333
+ <td>4.2%</td>
334
+ <td>87.5%</td>
335
+ <td>56.9%</td>
336
+ <td>30.0%</td>
337
+ </tr>
338
+ <tr>
339
+ <td>OpenVLA</td>
340
+ <td>4.1%</td>
341
+ <td>0.0%</td>
342
+ <td>33.3%</td>
343
+ <td>0.0%</td>
344
+ <td>12.5%</td>
345
+ <td>0.0%</td>
346
+ <td>8.3%</td>
347
+ <td>4.1%</td>
348
+ <td>1.0%</td>
349
+ </tr>
350
+ <tr>
351
+ <td>RoboVLM (zero-shot)</td>
352
+ <td>37.5%</td>
353
+ <td>20.8%</td>
354
+ <td>33.3%</td>
355
+ <td>25.0%</td>
356
+ <td>8.3%</td>
357
+ <td>8.3%</td>
358
+ <td>0.0%</td>
359
+ <td>0.0%</td>
360
+ <td>13.5%</td>
361
+ </tr>
362
+ <tr>
363
+ <td>RoboVLM (fine-tuning)</td>
364
+ <td>54.2%</td>
365
+ <td>29.2%</td>
366
+ <td>25.0%</td>
367
+ <td>25.0%</td>
368
+ <td>45.8%</td>
369
+ <td>12.5%</td>
370
+ <td>58.3%</td>
371
+ <td>58.3%</td>
372
+ <td>31.3%</td>
373
+ </tr>
374
+ <tr>
375
+ <td>SpatialVLA (zero-shot)</td>
376
+ <td><b>25.0%</b></td>
377
+ <td><b>20.8%</b></td>
378
+ <td><b>41.7%</b></td>
379
+ <td>20.8%</td>
380
+ <td><b>58.3%</b></td>
381
+ <td>25.0%</td>
382
+ <td><b>79.2%</b></td>
383
+ <td>70.8%</td>
384
+ <td><b>34.4%</b></td>
385
+ </tr>
386
+ <tr>
387
+ <td>SpatialVLA (fine-tuning)</td>
388
+ <td><b>20.8%</b></td>
389
+ <td>16.7%</td>
390
+ <td>29.2%</td>
391
+ <td>25.0%</td>
392
+ <td><b>62.5%</b></td>
393
+ <td>29.2%</td>
394
+ <td><b>100.0%</b></td>
395
+ <td><b>100.0%</b></td>
396
+ <td><b>42.7%</b></td>
397
+ </tr>
398
+ </tbody>
399
+ </table>
400
+
401
+ - LIBERO Simulation Benchmark Results.
402
+
 
 
 
 
 
 
403
  <table border="1" class="dataframe">
404
  <thead>
405
  <tr style="text-align: center;">
 
492
  </tbody>
493
  </table>
494
 
495
+ - Zero-shot Robot Control Evaluation on WidowX Robot.
496
+
497
+ <img src="https://cdn-uploads.huggingface.co/production/uploads/6535045a910b844786a6642f/SUPyXwcdfnWranO04tulL.png" alt="perform">
498
+
499
+
500
+ - Spatial Understanding Capability Evaluation.
501
+
502
+ <img src="https://cdn-uploads.huggingface.co/production/uploads/6535045a910b844786a6642f/g-EfM-6M7iM9IYryUTwLA.png" alt="perform">
503
+
504
 
505
+ - Adapting to New Robot Setups on Franka Robot.
 
 
 
506
 
507
+ <img src="https://cdn-uploads.huggingface.co/production/uploads/6535045a910b844786a6642f/4Z_vjQvsDGUcHCwmBCtRa.png" alt="perform">
 
 
 
508
 
 
 
 
 
509
 
510
 
511
  ## Citation