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    <item>
      <title><![CDATA[CHOREO Composes 2,950 Humanoid Skills at 95.4% Success]]></title>
      <link>https://humanoidintel.ai/news/choreo-humanoid-skill-composition-framework-2026</link>
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      <pubDate>Tue, 22 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[CHOREO unifies 2,950 humanoid skills as trajectories, hitting 95.4% success on 130 multi-action tasks — no retraining required.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[Layered E-Skin Hits R² 0.944 for Shear Sensing]]></title>
      <link>https://humanoidintel.ai/news/layered-eskin-shear-sensing-fsr-array-robotic-fingertips</link>
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      <pubDate>Tue, 22 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[A two-layer FSR array achieves R²=0.944 shear-force estimation and slip detection from robotic fingertips.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[VLPSA Lifts VLA Collision Avoidance from 23% to 91%]]></title>
      <link>https://humanoidintel.ai/news/vlpsa-vla-collision-avoidance-safety-filter-2026</link>
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      <pubDate>Tue, 22 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[VLPSA safety filter raises π0.5 collision avoidance from 23.1% to 91.2% on SafeLIBERO without retraining.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[VT-Bridge Lifts VLA Contact Success Rate from 11.7% to 62.9%]]></title>
      <link>https://humanoidintel.ai/news/vt-bridge-vtla-residual-adaptation-contact-rich-manipulation</link>
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      <pubDate>Tue, 22 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[VT-Bridge adapts pretrained VLAs to tactile-aware VTLAs with just 50 demos and a 0.98M-parameter adapter.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[ForeTac-VLA Hits 95% on Contact-Rich Tasks]]></title>
      <link>https://humanoidintel.ai/news/foretac-vla-tactile-forecasting-contact-rich-manipulation</link>
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      <pubDate>Mon, 21 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[ForeTac-VLA achieves 95% avg success on 4 contact-rich tasks, beating standard VLA fine-tuning by 36.25 pp.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[VLA-Feedback Lifts Dynamic Task Success 27.5% to 85%]]></title>
      <link>https://humanoidintel.ai/news/vla-feedback-real-time-denoising-responsive-vlas</link>
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      <pubDate>Mon, 21 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[VLA-Feedback's two-timescale architecture closes the open-loop gap in diffusion VLAs, hitting 85% on dynamic tasks vs. 27.5% baseline.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[AthenaZero Throws at 30 m/s with Human-Level Arm Inertia]]></title>
      <link>https://humanoidintel.ai/news/athenazero-low-inertia-bimanual-robot-dynamic-manipulation</link>
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      <pubDate>Fri, 18 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[AthenaZero hits 30 m/s throws and 14 m/s catches using quasi-direct drive arms with human-comparable endpoint inertia.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[DITTO's 7-DOF Hand Solves Force Feedback Tradeoff]]></title>
      <link>https://humanoidintel.ai/news/ditto-dexterous-interface-transparent-teleoperation-7dof</link>
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      <pubDate>Fri, 18 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[Columbia researchers co-designed a 7-DOF hand and kinematically equivalent exoskeleton to unify handheld data collection and bilateral teleoperation.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[Adaptive-MHE Closes Sim-to-Real Gap in Loco-Manipulation]]></title>
      <link>https://humanoidintel.ai/news/adaptive-mhe-sampling-mpc-loco-manipulation-mhe</link>
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      <pubDate>Thu, 17 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[Adaptive-MHE couples online parameter estimation with sampling-based MPC to match ground-truth controller performance in legged loco-manipulation.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[Multi-Humanoid Cooperative Transport via Decentralized Control]]></title>
      <link>https://humanoidintel.ai/news/multi-humanoid-cooperative-transport-decentralized-object-centric-control</link>
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      <pubDate>Thu, 17 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[Oregon State researchers demonstrate decentralized object-centric control enabling humanoid teams to cooperatively pick up and transport objects.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[RL Lifts VLA Accuracy from 42% to 97% in 10 Minutes]]></title>
      <link>https://humanoidintel.ai/news/real-time-expo-ft-rl-vla-fine-tuning</link>
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      <pubDate>Thu, 17 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[Stanford researchers cut VLA latency-induced failure with RL, lifting task success from 42% to 97% in under 10 minutes of robot data.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[WholeBodyWAM Trains on 4K Hours of Human Motion]]></title>
      <link>https://humanoidintel.ai/news/wholebody-wam-world-action-model-motion-priors-2026</link>
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      <pubDate>Thu, 17 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[WholeBodyWAM uses 4K+ hours of heterogeneous human and humanoid motion to bootstrap whole-body manipulation without robot-specific labels.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[AdaDE Cuts VLA Parameters 40% With 95% Task Retention]]></title>
      <link>https://humanoidintel.ai/news/adade-dense-moe-vla-compression-2026</link>
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      <pubDate>Wed, 16 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[AdaDE converts VLA feed-forward blocks to MoE layers, deactivating 40% of LLM params while retaining 95.1% LIBERO success rate.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[RECAL Adds Collision Awareness to Blind WBCs on Digit V3]]></title>
      <link>https://humanoidintel.ai/news/recal-collision-aware-whole-body-control-digit-v3</link>
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      <pubDate>Wed, 16 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[RECAL wraps any blind WBC with a cross-attention layer that trades target tracking for collision safety on Digit V3.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[XRoboToolKit-T Adds Tactile Sensing to Teleoperation]]></title>
      <link>https://humanoidintel.ai/news/xrobotoolkit-t-tactile-teleoperation-contact-rich-manipulation</link>
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      <pubDate>Wed, 16 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[XRoboToolKit-T combines tactile force control and a VLA model to improve data collection for contact-rich manipulation tasks.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[GROOVE Cuts VLA Jerk 43% Without Retraining]]></title>
      <link>https://humanoidintel.ai/news/groove-geometry-guided-vla-jerk-reduction</link>
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      <pubDate>Tue, 15 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[GROOVE reduces rotational EEF jerk 43.42% on LIBERO with no retraining, boosting task success from 93.75% to 95.75%.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[REAL-I Challenge at ICRA 2026: VLA Training Lessons]]></title>
      <link>https://humanoidintel.ai/news/real-i-challenge-icra-2026-vla-training-lessons</link>
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      <pubDate>Tue, 15 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[ICRA 2026's REAL-I Challenge stress-tests VLA training on a shared dual-arm humanoid, exposing key limits of offline metrics.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[ShieldVLA Cuts Safety Violations 57% in VLA Models]]></title>
      <link>https://humanoidintel.ai/news/shieldvla-feasibility-aware-safety-alignment-vla-models</link>
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      <pubDate>Tue, 15 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[ShieldVLA uses HJ reachability to cut VLA safety violations 57% and boost task success +0.13 over SafeVLA.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[DATAFARM Closes the VLA Fine-Tuning Gap with TAMP]]></title>
      <link>https://humanoidintel.ai/news/datafarm-tamp-vla-fine-tuning-distribution-alignment</link>
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      <pubDate>Mon, 14 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[DATAFARM aligns TAMP trajectories with VLA pretraining distributions, hitting 56.7% vs 8.3% for raw TAMP.]]></description>
      <category>research</category>
    </item>
    <item>
      <title><![CDATA[DWMP Uses Dual World Models for Humanoid Navigation]]></title>
      <link>https://humanoidintel.ai/news/dwmp-dual-world-models-humanoid-obstacle-traversal</link>
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      <pubDate>Mon, 14 Sep 2026 04:00:00 GMT</pubDate>
      <description><![CDATA[DWMP splits proprioceptive and visual processing into separate world models, improving obstacle traversal on the Unitree G1.]]></description>
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