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AI Agent Papers·2026
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AI4AI at Test-Time: Strong-to-Weak Capability Transfer via Harnesses

Cheng Qian, Wenting Zhao +7·Salesforce AI Research, University of Illinois Urbana-Champaign

Uses a stronger 'builder' model at inference time to construct executable harnesses that boost weaker target models without parameter updates, mainly by turning unstable reasoning into deterministic code, routing, and strict answer-format enforcement.

#distillation#reasoning#LLM#benchmark#evaluation+4
AI Video Papers·2026
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DreamX-Phi 1.0: Action-Conditioned Video World Model for Robotic Manipulation

DreamX Team, Rui Chen +8

Predicts future video frames conditioned on an observed frame, a language instruction, and a sequence of end-effector poses and gripper states for robot manipulation. Uses per-arm SE(3) geometric encoding (PRoPE-style), a lightweight depth branch, SAM3 masks with a frozen V-JEPA teacher, and distribution-matching distillation for efficient, consistent action-conditioned rollouts.

#robotics#video#depth#distillation#vision+6
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