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COMPANY · ENTITY #6721

Qwen3-VL-8B

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2

COMPANIES · 1 SOURCE · AWS Machine Learning

Run SkyRL GRPO post-training of Qwen3‑VL‑8B on Amazon SageMaker HyperPod

Amazon demonstrates running the open-source SkyRL framework on SageMaker HyperPod (EKS) to post-train a Qwen3‑VL‑8B vision‑language model with Group Relative Policy Optimization (GRPO). Using a HyperPod Ray cluster with shared FSx storage, the workflow improved maze solve rate from 43.75% to over 95% on a fixed 64‑maze evaluation set and uses colocated vLLM inference and FSDP-sharded policy training with LoRA adapters.

6.0

RESEARCH · 1 SOURCE · arXiv cs.AI

CounterCredit verifies visual calls to reduce spurious lookups and boost VLM performance

arXiv:2609.22910v1 introduces CounterCredit, a method that tests whether each image-returning call was both needed and actually used by computing a decision value (compare answering immediately vs. using the visual branch) and an evidence value (compare returned crop vs. random same-size patches). From the same cold start, prompt pool, and budget, CounterCredit outperforms an outcome-only GRPO baseline—reaching 89.5% on V*, 80.2% on HR-Bench-4K, and 76.4% on HR-Bench-8K while cutting spurious-call rates to ~31–36% and raising Qwen3-VL-8B from 75.4 to 80.8 on average.

7.0