Unverified50% confidenceBenchmarkExact time
According to data published by the HexaShell project team, the VLM reached a 78% success rate within three attempts on the RLBench pick-and-place task.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/19/2026
First Seen
Valid until: 1/17/2027
Sources
Related Entities
Related Claims
UnverifiedMATE paired with the Qwen2.5-14B model achieves a task success rate of 81.3%.66% similarUnverifiedIn the HexaShell experiments, the robot failed its first grasp of a cylinder, and the VLM, based on the logs, raised the approach height by 4 cm and succeeded on the second attempt.66% similarUnverified3,189 successful rollouts were collected from Qwen3.8-27B for supervised fine-tuning (imitation learning), and performance stagnated at 47.5%, below the results of two rounds of RL training.63% similarUnverifiedOn the Qwen3-VL-4B model, fine-tuning with procedurally generated data raises its accuracy on SpaceCast-Bench from 34.0% to 65.7%, and achieves a macro-average gain across six out-of-domain benchmarks.60% similarUnverifiedMiniMax-H3 achieved a success rate of 29.90% on WorldGuide-Bench under the condition of receiving a reference action plan.60% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1065622API
curl https://kongchang.com/api/v1/knowledge/claims/1065622MCP
get_claim(id=1065622)