DB-Nav/SER-Nav improves zero-shot object navigation by reranking frontier goals using activation from object co-occurrence and inhibition from similar distractors and failed visits.
ApexNav: An adaptive exploration strategy for zero-shot object navigation with target- centric semantic fusion
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EvoMemNav builds a Visual-Semantic Memory Graph keeping raw views, applies a budgeted coarse-to-fine policy, and uses reflection-driven updates to improve zero-shot navigation on GOAT-Bench and HM3D.
A zero-shot unified agent for VLN-CE, ObjectNav, EQA and Aerial-VLN on wheeled, quadruped, humanoid and UAV platforms that translates language and vision inputs into actions via MLLMs plus TDM and SCB mechanisms, matching trained foundation models on multiple benchmarks.
HiRO-Nav adaptively triggers reasoning only on high-entropy actions via a hybrid training pipeline and shows better success-token trade-offs than always-reason or never-reason baselines on the CHORES-S benchmark.
TravExplorer couples zero-shot semantic guidance with traversability-aware 3-D planning to enable cross-floor object navigation in unseen indoor environments.
MORN augments frozen VLM-based object navigation agents with a System 2 meta-controller using Potentiality Index, Persistence Gating, and Evidence Accumulation to improve goal completion rate from 0.23 to 0.30 and reduce wasted steps on the HM3D dataset.
citing papers explorer
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Semantic Evidence Regulation via Relational Bias for Zero-Shot Object Navigation
DB-Nav/SER-Nav improves zero-shot object navigation by reranking frontier goals using activation from object co-occurrence and inhibition from similar distractors and failed visits.
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EvoMemNav: Efficient Self-Evolving Fine-Grained Memory for Zero-Shot Embodied Navigation
EvoMemNav builds a Visual-Semantic Memory Graph keeping raw views, applies a budgeted coarse-to-fine policy, and uses reflection-driven updates to improve zero-shot navigation on GOAT-Bench and HM3D.
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Uni-LaViRA: Language-Vision-Robot Actions Translation for Unified Embodied Navigation
A zero-shot unified agent for VLN-CE, ObjectNav, EQA and Aerial-VLN on wheeled, quadruped, humanoid and UAV platforms that translates language and vision inputs into actions via MLLMs plus TDM and SCB mechanisms, matching trained foundation models on multiple benchmarks.
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HiRO-Nav: Hybrid ReasOning Enables Efficient Embodied Navigation
HiRO-Nav adaptively triggers reasoning only on high-entropy actions via a hybrid training pipeline and shows better success-token trade-offs than always-reason or never-reason baselines on the CHORES-S benchmark.
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TravExplorer: Cross-Floor Embodied Exploration via Traversability-Aware 3-D Planning
TravExplorer couples zero-shot semantic guidance with traversability-aware 3-D planning to enable cross-floor object navigation in unseen indoor environments.
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MORN: Metacognitive Object-Goal Regulation for Resource-Rational Long-Horizon Navigation
MORN augments frozen VLM-based object navigation agents with a System 2 meta-controller using Potentiality Index, Persistence Gating, and Evidence Accumulation to improve goal completion rate from 0.23 to 0.30 and reduce wasted steps on the HM3D dataset.