Evo-DexBench: Benchmarking Generalization across Related Tasks for Dexterous Manipulation

Bing Cheng; Yiran Mao; Zewei Ye; Yifan Jin; Xinyi Chen; Ruifeng Tu; Shuhuai Wang; Tao Lin

cs.ROOct 15, 2026

Evo-DexBench: Benchmarking Generalization across Related Tasks for Dexterous Manipulation

Authors: Bing Cheng, Yiran Mao, Zewei Ye, Yifan Jin, Xinyi Chen, Ruifeng Tu, Shuhuai Wang, Tao Lin,

Organizations: School of AI, Shanghai Jiao Tong University · Nanjing University · Central South University · Beĳing University of Posts and Telecommunications ·

Abstract

General-purpose dexterous manipulation requires policies to transfer knowledge from related tasks to new tasks with only a few target demonstrations. Existing benchmarks often provide too many target demonstrations. They also leave the differences between source and target tasks uncontrolled. As a result, they cannot clearly distinguish knowledge transfer from task memorization. Our key insight is the Core-Gen principle. Core tasks are related tasks that share a functional interaction and provide source knowledge, while a Gen task is a novel target within the same functional family that has only a few demonstrations. This setup tests whether a policy can reuse functional interaction knowledge. Based on this principle, we propose Evo-DexBench, which controls both source-task relatedness and target-task exposure. It comprises 30 tasks in six functional families and a VR teleoperation pipeline. The resulting dataset covers three everyday scenes per task. It contains 1,248 multimodal demonstrations collected with simulated Shadow Hands equipped with 123 taxels. Experiments show that even the best-performing method achieves an average success rate of only 38.5%, highlighting the challenges existing methods face in transferring functional interaction knowledge. Further analysis shows that, across the two tasks, joint Core+Gen training improves performance by 12% and 38%, respectively, over training on Core followed by fine-tuning on Gen. This indicates that joint training makes better use of Core knowledge and that functionally matched Core data yields greater gains in success rate than mismatched data. We release the Evo-DexBench dataset and benchmark to support the evaluation of dexterous manipulation policies' generalization across related tasks.

Figures & tables

Figure 1: Overview of the Evo-DexBench. The benchmark comprises six functional task categories, each containing four Core tasks and one Gen task. Each task randomly switches among three scenes within its corresponding Kitchen or Studio environment during data collection and evaluation. The bottom-right panel reports the performance of representative models.

Benchmark	Arm–hand	Bimanual	Force	Scenes/task	Core-Gen	Data Collection
LIBERO	✗	✗	✗	1	✗	SpaceMouse teleoperation
RoboTwin 2.0	✗	✓	✗	1	✗	MLLM-based generation
Bi-DexHands	✗	✓	✗	1	ML4	RL policy
DexArt	✓	✗	✗	1	✗	RL policy
DexCraft	✓	✗	✗	1	✗	Keyboard teleoperation
HANDFUL	✓	✗	✗	1	✗	RL policy

Table 1: Comparison of embodied manipulation benchmarks.

Figure 2: Overall framework of the benchmark. The environment covers six task categories, three Kitchen/Studio scenes, 123 hand taxels, and variations in layout, cameras, lighting, and physical properties, while decoupling task logic from scene layout. Policies and keyboard/mouse or Quest 3 teleoperation share a unified interface.

Family	Shared interaction
Button-driven	Displace a localized control to change device state.
Rotational manipulation	Apply directed rotation to a functional component.
Access-and-transfer	Open an access mechanism, transfer an object, and restore its state.
Structured configuration	Construct a spatial arrangement under ordering or stability constraints.
Assembly	Align complementary objects with two hands for insertion or fitting.
Articulated configuration control	Stabilize one part while changing another’s relative configuration.

Table 2: Interaction families and shared functional interaction patterns.

Figure 3: Core-Gen task examples. The first and second rows show single-arm rotational manipulation and access-and-transfer tasks, respectively, while the third row shows bimanual articulated configuration control tasks. The first four columns show Core tasks, and the last column shows Gen tasks.

Figure 4: Task visualizations. The first column shows short-horizon tasks: pressing a desk lamp button and stapling paper. The second and third columns show long-horizon tasks: opening a cabinet with one hand and placing a tennis ball on the lower shelf, and assembling a sandwich with both hands.

Figure 5: Family-level baseline SR for the evaluated policies, with 95% confidence intervals.

Family	Task	$\pi_{0.5}$	DP-T	DP-C	KineDex	SmolVLA
Button- driven	LampButton	30% / 35.7	15% / 12.6	26% / 28.7	24% / 23.2	41% / 35.2
	WallSwitch	60% / 74.1	35% / 57.8	68% / 79.7	76% / 85.6	66% / 78.0
	PhoneHomeButton	16% / 24.4	1% / 2.2	8% / 13.7	5% / 14.8	8% / 12.8
	ToasterSlider	42% / 75.2	49% / 79.6	64% / 84.0	63% / 84.0	37% / 74.2
	DisplayPowerButton	20% / 39.4	33% / 52.8	9% / 31.5	18% / 40.8	18% / 36.0
Rotational manipulation	FaucetHandle	21% / 29.1	24% / 27.2	19% / 23.0	16% / 22.0	12% / 22.2

Table 3: Standard evaluation on 15 tasks. Each entry is SR (%) / StageScore .

Strategy	DisplayPowerButton	DishwasherKnob
Gen only	15% / 29.7	36% / 55.1
Full Core $\rightarrow$ Gen	8% / 23.6	8% / 29.3
Early Core $\rightarrow$ Gen	9% / 24.6	22% / 41.2
Core + Gen joint	20% / 39.4	46% / 62.5

Table 4: Few-shot adaptation strategies at 50 epochs. Each entry is SR (%) / StageScore .

Panel of Figure 6 — Figure 6: Transfer heatmap and tactile analysis. Left: Change in $\pi_{0.5}$ SR relative to Gen-only training when mixing each Core family with a Gen target. The diagonal contains the functionally matched pairs. Right: Task-wise SR change from adding tactile observations to KineDex.

Method	Gen only	Button-driven	Rotational manip.	Access-and-transfer
$\pi_{0.5}$	36% / 55.1	40% / 61.0	46% / 62.5	32% / 52.4
DP-T	28% / 42.1	27% / 51.0	41% / 56.6	41% / 56.0
KineDex	42% / 57.9	39% / 48.9	55% / 67.9	51% / 63.9

Table 5: Core-source relatedness on DishwasherKnob across three models. Each entry is SR (%) / StageScore ; the functionally matched Rotational source is bold.

Appendix figures & tables13 assets

Supplementary material from the paper’s appendix.

Appendix

Task	Description	Stage success conditions
LampButton	Press the lamp button and keep the lamp on.	30%: index-finger force $\geq$ 0.15 N; 60%: button travel $\geq$ 70%; 100%: lamp remains lit for $\geq$ 1 s after triggering.
WallSwitch	Flip the wall switch on.	30%: hand tip within 0.20 m; 60%: angle $\geq$ 0.061 rad; 100%: switch angle $\geq$ 0.122 rad for 1 s.
PhoneHomeButton	Press and release the phone Home button.	30%: correct contact force $\geq$ 0.12 N; 70%: contact held while travel $\geq$ 70%; 100%: button released, return travel $\leq$ 20%, and phone remains safely on the table.
ToasterSlider	Press the toaster slider.	30%: hand tip within 0.40 m of toaster; 60%: hand tip within 0.35 m of slider point; 100%: toaster slider displacement $\geq$ 0.062 m.
DisplayPowerButton	Press the display power button.	30%: fingertip within 0.05 m; 60%: contact force $\geq$ 0.15 N; 100%: contact followed by travel $\geq$ 70% and lasted for 3 control steps.

Appendix

Table 6: Task definitions for the Button-driven family.

Task	Description	Stage success conditions
FaucetHandle	Turn the faucet handle open.	30%: handle contact force $\geq$ 0.40 N; 60%: opening travel $\geq$ 50%; 100%: opening travel $\geq$ 80%.
MouseWheel	Hold the mouse and scroll its wheel.	25%: mouse contact force $\geq$ 0.15 N or wheel rotation $>0.03$ rad; 50%: wheel contact force $\geq$ 0.15 N or rotation $>0.03$ rad; 100%: wheel rotation $\geq$ 1.5 rad, mouse linear speed $\leq$ 0.04 m/s, and angular speed $\leq$ 0.60 rad/s.
CoffeeKnob	Turn the coffee-machine knob to its designated target setting.	30%: knob contact force $\geq$ 0.40 N; 50%: turning toward the target at $\geq$ 0.03 rad/s with valid knob contact has been recorded; 75%: angle error $\leq$ 20 ∘ ; 100%: angle error $\leq$ 6 ∘ , knob angular speed $\leq$ 0.20 rad/s.
KettleLidTab	Rotate the kettle-lid tab to the notch.	30%: thumb and index contacts, each $\geq$ 0.35 N; 55%: positive rotation $\geq$ 5 ∘ at $\geq$ 0.03 rad/s; 80%: angle in 60 ∘ –90 ∘ ; 100%: angle error $\leq$ 9 ∘ , tab angular speed $\leq$ 0.50 rad/s, kettle displacement $\leq$ 0.01 m, and tilt $\leq$ 3 ∘ .
DishwasherKnob	Turn the dishwasher knob to its target setting.	30%: knob contact force $\geq$ 0.40 N; 60%: angle error $\leq$ 45 ∘ ; 100%: effective turn recorded, angle error $\leq$ 9 ∘ , and angular speed $\leq$ 1.00 rad/s.

Appendix

Table 7: Task definitions for the Rotational manipulation family.

Task	Description	Stage success conditions
CupFromCabinet	Open the cabinet, remove the cup, and place it upright on the counter.	25%: door angle $>45^{\circ}$ ; 50%: valid cup-body/handle grasp (force $\geq$ 0.40 N); 75%: cup clears the cabinet opening; 100%: cup is on the counter, tilt $\leq$ 15 ∘ , released, with linear speed $\leq$ 0.05 m/s and angular speed $\leq$ 0.60 rad/s for 0.40 s.
MicrowaveBowl	Open the microwave, place the bowl inside, and close the door.	25%: door opening $\geq$ 45%; 50%: two-finger bowl grasp, each force $\geq$ 0.30 N, held 0.12 s; 75%: bowl fully inside, support $\geq$ 0.20 N, tilt $\leq$ 35 ∘ , released, linear speed $\leq$ 0.05 m/s and angular speed $\leq$ 0.60 rad/s for 0.35 s; 100%: placement confirmed and the same bowl conditions hold with the door closed for 0.30 s. Closed condition is at opening $\leq$ 5% and speed $\leq$ 0.08 rad/s, and exits above 8%.
TennisBallTransfer	Move the tennis ball from shelf 1 to shelf 2 and close the cabinet.	20%: door opening $\geq$ 55%; 45%: two-finger grasp with force $\geq$ 0.40 N per finger; 75%: ball in shelf-2 target, supported, released, linear speed $\leq$ 0.03 m/s, angular speed $\leq$ 0.60 rad/s for 5 steps; 100%: target was placed, the door is confirmed closed with speed $\leq$ 0.01 m/s for 5 steps, and the ball satisfies the placement conditions.
BananaFromDrawer	Open the drawer, place the banana on the desk, and close the drawer.	25%: drawer opening $\geq$ 45%; 40%: valid grasp held 0.15 s; 60%: banana fully clears drawer; 85%: desk support $\geq$ 0.20 N, released and still for 0.50 s; 100%: banana remains released and stable on the desk while the drawer is confirmed closed with speed $\leq$ 0.01 m/s for 0.15 s.
CandleToCabinet	Open the upper glass cabinet, place the candle inside, and release it.	25%: an upper door angle $>60^{\circ}$ ; 50%: at least two fingers, each $\geq$ 0.30 N; 75%: candle bounding box inside cabinet; 100%: candle remains inside and upright with base-height error $\leq$ 0.025 m, released, tilt $\leq$ 20 ∘ , linear speed $\leq$ 0.03 m/s, and angular speed $\leq$ 0.50 rad/s for 1 s.

Appendix

Table 8: Task definitions for the Access-and-transfer family.

Task	Description	Stage success conditions
TablewarePlacement	Place the plate in the center, fork left, and knife right.	30%: any one piece correctly placed; 60%: any two pieces correctly placed; 90%: all three correctly placed. Correct placement requires position error $\leq$ 0.12 m, tilt $\leq$ 35 ∘ , utensil yaw error $\leq$ 35 ∘ , release, linear speed $\leq$ 0.04 m/s and angular speed $\leq$ 0.60 rad/s; 100%: all three have valid placements, left/right relations and clearance for 1 s.
HammerBlockAssembly	Arrange three blocks into the reference hammer shape.	25%: one block position/height error $\leq$ 0.015 m, yaw/tilt $\leq$ 8 ∘ , released; 50%: at least two blocks have valid poses and releases, with at least one prescribed adjacency pair (center error $\leq$ 0.020 m, edge angle $\leq$ 12 ∘ ); 75%: all three target poses and releases valid; 100%: all three target poses and prescribed adjacency pairs valid, all blocks released, linear speed $\leq$ 0.03 m/s, and angular speed $\leq$ 0.50 rad/s for 0.50 s.
SandwichAssembly	Place the patty and top bread on the pre-stacked bottom bread and cheese.	40%: either movable ingredient correctly placed; 80%: both movable ingredients correctly placed. Placement requires position error $\leq$ 0.050 m, height error $\leq$ 0.018 m, tilt $\leq$ 25 ∘ , valid support and overlap, release, linear speed $\leq$ 0.08 m/s and angular speed $\leq$ 1.20 rad/s; 100%: all four layers satisfy the ordered support, pose, overlap, release and speed conditions for 0.25 s.
RingTowerAssembly	Stack the red, blue, and yellow rings from largest to smallest.	30%: red ring correctly on bottom; 60%: red and blue rings correctly placed; each ring center within 0.028 m of post axis, height error $\leq$ 0.018 m, tilt $\leq$ 22 ∘ ; 100%: correct three-ring order and poses, with linear speed $\leq$ 0.06 m/s and angular speed $\leq$ 0.80 rad/s for 20 steps.
BoxPacking	Pack three shaped objects into the box and close the lid.	20%: at least one object fully inside; 40%: at least two objects fully inside; 75%: all three objects fully inside; 100%: all three objects fully inside and maximum opening across all lids $\leq$ 4%.

Appendix

Table 9: Task definitions for the Structured configuration family.

Task	Description	Stage success conditions
PenCapping	Remove the pen, grasp its cap, and cap the pen.	20%: either object previously grasped ( $\geq$ 0.15 N per parent link); 40%: both objects previously grasped; 70%: axis error $\leq$ 18 ∘ , lateral error $\leq$ 0.015 m, tip inside cap range; 100%: axis error $\leq$ 18 ∘ , lateral error $\leq$ 0.010 m, and insertion depth $\geq$ 0.015 m.
CupSleeveFit	Slide a sleeve from the cup bottom to its middle.	20%: either object previously grasped ( $\geq$ 0.18 N per parent link); 40%: both objects previously grasped; 70%: axis error $\leq$ 15 ∘ , lateral error $\leq$ 0.018 $\times$ scale, center height in [ $-0.055$ , $0.040$ ] $\times$ scale; 100%: center height in [ $0.062$ , $0.100$ ] $\times$ scale, lateral error $\leq$ 0.010 $\times$ scale, axis error $\leq$ 15 ∘ . Here scale $=0.72$ .
BottleFunnelInsertion	Align a funnel with a bottle and insert it.	20%: either object previously grasped ( $\geq$ 0.18 N per parent link); 40%: both objects previously grasped; 70%: axis error $\leq$ 15 ∘ , lateral error $\leq$ 0.018 m, tip near mouth; 100%: axis error $\leq$ 15 ∘ , insertion depth $\geq$ 0.010 m, tip height in [0.1031, 0.1660] m in the bottle frame, lateral error $\leq$ 0.010 m, linear speed relative to bottle $\leq$ 0.06 m/s, and relative angular speed $\leq$ 1.00 rad/s for 3 steps.
PlugInsertion	Hold a plug and socket and fully insert the plug.	25%: opposite hands hold both objects, at least two parent contacts per object at $\geq$ 0.20 N; 50%: both actual pins align with the socket channels, direction error $\leq$ 12 ∘ , tips near the openings; 75%: both aligned pins enter their channels; 100%: both pins remain aligned with depth $\geq$ 0.01575 m each, linear speed relative to socket $\leq$ 0.15 m/s, and relative angular speed $\leq$ 1.00 rad/s.
ScissorsSheathing	Insert the tips of closed scissors into the sheath.	20%: scissors previously grasped with at least two parent contacts, each $\geq$ 0.20 N, for 0.10 s; 60%: both real blade tips align with the channel cross-section, axis error $\leq$ 12 ∘ , axial distance from entrance $\leq$ 0.025 m; 100%: both blade tips inside the sheath with 0.002 m geometric tolerance, axis error $\leq$ 12 ∘ , maximum tip speed relative to sheath $\leq$ 0.08 m/s, and relative angular speed $\leq$ 1.00 rad/s for 0.10 s.

Appendix

Table 10: Task definitions for the Assembly family. For PenCapping, CupSleeveFit and BottleFunnelInsertion, a grasp requires the same hand to contact an object through at least two distinct tactile parent links, each at or above the listed force threshold, continuously for 0.10 s.

Task	Description	Stage success conditions
LaptopClosing	Stabilize the laptop base and close the screen to about 25 ∘ .	30%: opposite hands contact base/screen at $\geq$ 0.40 N, base displacement $\leq$ 0.040 m and tilt $\leq$ 5 ∘ ; 60%: screen reaches 60 ∘ $\pm$ 8 ∘ ; 100%: screen reaches 25 ∘ $\pm$ 5 ∘ , base remains stable, and absolute screen angular speed $\leq$ 1.00 rad/s for 0.25 s.
StaplerPaperMark	Insert paper, press the stapler, then move it away.	20%: paper force $\geq$ 0.50 N or displacement $\geq$ 0.03 m; 50%: paper enters staple area with tilt $\leq$ 35 ∘ ; 70%: paper remains in area, stapler press-arm qpos $\leq$ 0.10 rad, mark created; 100%: after a mark is created, the current stapling point and the paper mark remain $\geq$ 0.06 m apart for 5 steps.
ScissorsOpening	Stabilize scissors and open the moving handle.	40%: support-handle contact $\geq$ 0.15 N or base linear speed $<0.30$ m/s has been recorded, and current base linear/angular speeds are $\leq$ 0.30 m/s and $\leq$ 6.00 rad/s; 70%: moving-handle contact $\geq$ 0.15 N or proximity to target has been recorded, and current angle error $\leq$ 0.50 rad; 100%: opening angle 1.263 $\pm$ 0.20 rad, scissors-base linear speed $\leq$ 0.30 m/s, and angular speed $\leq$ 6.00 rad/s for 10 steps.
BoxLidOpening	Stabilize a box and open its hinged lid.	30%: task contact $\geq$ 0.40 N with box displacement $\leq$ 0.10 m, tilt $\leq$ 7 ∘ , linear speed $\leq$ 0.05 m/s and angular speed $\leq$ 0.50 rad/s has been recorded; 60%: opening past $\geq$ 10 ∘ with a stable box, lid contact $\geq$ 0.40 N and positive opening velocity $\geq$ 0.02 rad/s has been recorded; 100%: lid angle 90 ∘ –105 ∘ , box stable, and lid angular speed $\leq$ 0.25 rad/s for 1 s.
GlassesFolding	Fold both eyeglass temples into the storage position.	40%: left temple angle $\geq$ 0.55 rad has been recorded; 80%: right temple angle $\geq$ 0.45928 rad has been recorded; 100%: right/left angles satisfy either ( $\geq$ 0.91, $\geq$ 0.55) rad or ( $\geq$ 0.45928, $\geq$ 1.08975) rad.

Appendix

Table 11: Task definitions for the Articulated configuration control family.

Grouping	Thumb	Index	Middle	Ring	Little	Palm	Total
By finger/area	29	21	18	18	14	23	123
Region	Distal	Middle	Proximal	Palm	Sub-palm		Total
By anatomy	62	24	14	21	2		123

Appendix

Table 12: Distribution of the 123 taxels on one Shadow Hand.

Policy	Native model	Policy interface	Model-specific adaptation
$\pi_{0.5}$	OpenPI JAX; pretrained flow-matching VLA	Three RGB views, language, 31-D/62-D state; 50-step chunks	Pad state/action interfaces to 32-D/64-D and discard padded action dimensions
SmolVLA	LeRobot 0.4.0; SmolVLM2-500M with flow-matching expert	Three/four RGB views, language, 31-D/62-D state; 50-step chunks	Pad to 32-D/64-D and expand four projection tensors for bimanual control
DP-C	Convolutional Diffusion Policy with temporal U-Net	Two observation steps; 30-step external action horizon	Use a 32-step internal target for U-Net divisibility and discard the final two steps
DP-T	Transformer Diffusion Policy	Two observation steps; 30-step action horizon	Map benchmark compact state and action channels to the released workspace
KineDex	Multi-view ResNet-18, per-finger tactile CNN, conditional U-Net	Two observation steps; 16-step horizon; motion plus five force targets per hand	Map 123 taxels to 100 finger taxels, expand the action head, and add bounded force feedback
KineDex No-Touch	Backbone-matched KineDex variant	Visual/proprioceptive input; 30 motion values per hand	Feed zero tactile input and remove force supervision and force feedback

Appendix

Table 13: Policy implementations and Evo-DexBench compatibility adaptations.

Policy	Epochs	Peak LR	Minimum LR	Batchsize
$\pi_{0.5}$	25 †	$5\!\times\!10^{-6}$	$5\!\times\!10^{-7}$	32
SmolVLA	25 ‡	$1\!\times\!10^{-4}$	$2.5\!\times\!10^{-6}$	32
DP-T	600	$1\!\times\!10^{-4}$	$1\!\times\!10^{-6}$	32
DP-C	600	$1\!\times\!10^{-4}$	$1\!\times\!10^{-6}$	32
KineDex	600	$1\!\times\!10^{-4}$	$1\!\times\!10^{-5}$	32
KineDex No-Touch	600	$1\!\times\!10^{-4}$	$1\!\times\!10^{-5}$	32

Appendix

Table 14: Training hyperparameters. KineDex No-Touch uses the same settings as Full KineDex.

Policy	Task	Overall	Nom.	Cam.	Light.	Phys.	Spat.
$\pi_{0.5}$	LampButton	30% / 35.7	40	15	35	40	20
	WallSwitch	60% / 74.1	60	50	75	55	60
	PhoneHomeButton	16% / 24.4	30	25	10	0	15
	ToasterSlider	42% / 75.2	40	55	50	20	45
	DisplayPowerButton	20% / 39.4	25	15	15	20	25
	FaucetHandle	21% / 29.1	15	15	5	40	30

Appendix

Table 15: Complete baseline results. Overall is SR (%) / StageScore; Nom., Cam., Light., Phys., and Spat. are condition-specific SR (%).

Gen target	Epochs	Training data	SR / StageScore
DisplayPowerButton	50	Gen only	15% / 29.7
	50	Button-driven Core + Gen	20% / 39.4
	50	Rotational manip. Core + Gen	17% / 34.7
	50	Access-and-transfer Core + Gen	12% / 33.0
DishwasherKnob	50	Gen only	36% / 55.1
	50	Button-driven Core + Gen	40% / 61.0

Appendix

Table 16: Complete

\pi_{0.5}

Core-source relatedness results. Entries are SR (%) / StageScore; bold marks the strongest retained result for each target.

Gen target	Training data	SR / StageScore
DisplayPowerButton	Gen only	15% / 29.7
	LampButton + ToasterSlider + Gen	17% / 32.9
	WallSwitch + PhoneHomeButton + Gen	20% / 39.3
	Four matched Core + Gen	20% / 39.4
DishwasherKnob	Gen only	36% / 55.1
	MouseWheel + CoffeeKnob + Gen	35% / 53.6

Appendix

Table 17: Core-set breadth/composition ablation for

\pi_{0.5}

. Entries are SR (%) / StageScore; bold marks the best result for each target.

Task	No-Touch	Full
FaucetHandle	15% / 16.3	16% / 22.0
MouseWheel	46% / 67.0	53% / 72.5
CoffeeKnob	25% / 63.9	33% / 68.9
KettleLidTab	54% / 70.7	62% / 75.3
DishwasherKnob	60% / 73.5	55% / 67.9
LaptopClosing	72% / 77.7	69% / 75.9

Appendix

Table 18: Task-wise KineDex tactile ablation. Entries are SR (%) / StageScore.

Dexterous Manipulation

Dexterous manipulation studies how robots use multi-fingered hands to grasp, reorient, and interact with objects through contact.

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DexVerse: A Modular Benchmark for Multi-Task, Multi-Embodiment Dexterous Manipulation

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Dexterous Manipulation Long-Horizon Robotic Manipulation Bimanual Robotic Manipulation Generalization in Robotic Manipulation Cross-Embodiment Robot Learning Multi-Task Robotic Manipulation+1

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Building general-purpose dexterous manipulation policies requires benchmarks that go beyond isolated tasks to systematically evaluate policies across diverse interaction modes, sensory conditions, and robot embodiments. However, existing benchmarks remain limited in task and data diversity, embodiment coverage, or controllable visual variation, hindering studies of cross-task and cross-embodiment generalization. We present DexVerse, a large-scale and modular benchmark for dexterous manipulation. DexVerse includes 100 tasks spanning a broad range of manipulation skills, including object grasping and relocation, articulated-object interaction, functional tool use, bimanual coordination, non-prehensile control, contact-rich behaviors, multi-goal execution, and long-horizon multi-stage task completion. It supports 3 robot arms and 6 dexterous hands, and is extensible to new tasks, assets, and embodiments. To evaluate visuomotor generalization, DexVerse provides configurable visual variations in textures, background, lighting, and camera viewpoints. We further provide a VR-based teleoperation interface and 3,180 demonstrations with synchronized proprioceptive, RGB, depth, point-cloud, and state observations. We benchmark representative methods, including Diffusion Policy, DP3, OpenVLA, and

π_{0.5}

, across 19 tasks. Results reveal substantial challenges in task generalization and visuomotor robustness, establishing DexVerse as a promising testbed for general-purpose dexterous manipulation. Project page: https://ycyao216.github.io/DexVerse.site

Abstract

Dexterous Manipulation

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