AVIS is an adaptive policy that jointly scales visual context via key-based token pruning and reasoning via difficulty-predicted self-consistency to improve the accuracy-compute curve on image and video tasks.
When Does RL Help Medical VLMs? Disentangling Vision, SFT, and RL Gains.arXiv preprint arXiv:2603.01301, 2026
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PathoSage is a three-stage framework using Structured Evidence Deliberation and a Beta-Bernoulli experience system to improve patch-level pathology reasoning by mitigating hallucinations and tool conflicts.
citing papers explorer
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AVIS: Adaptive Test-Time Scaling for Vision-Language Models
AVIS is an adaptive policy that jointly scales visual context via key-based token pruning and reasoning via difficulty-predicted self-consistency to improve the accuracy-compute curve on image and video tasks.
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PathoSage: Towards Multi-Source Evidence Adjudication in Pathology via Experience-Aware Agentic Workflow
PathoSage is a three-stage framework using Structured Evidence Deliberation and a Beta-Bernoulli experience system to improve patch-level pathology reasoning by mitigating hallucinations and tool conflicts.