Astra couples an RL-trained VLM policy with a view-consistent Bagel-based world simulator to enable agentic imagination during spatial reasoning, yielding benchmark gains on MMSI-Bench and MindCube.
g2vlm: Geometry grounded vision language model with unified 3d reconstruction and spatial reasoning.arXiv preprint arXiv:2511.21688
13 Pith papers cite this work. Polarity classification is still indexing.
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GeoThinker enables active, task-conditioned geometry integration in MLLMs via spatial-grounded fusion and importance gating, reaching 72.6 on VSI-Bench.
3D HAMSTER adds depth encoding and reconstruction to VLMs to produce 3D waypoint sequences that feed directly into pointcloud policies, claiming better generalization than 2D baselines under shifts.
MV-Actor proposes a multi-view framework using semantic interaction, semantic-spatial token interaction, and guided depth repair to reach 87.8% success on the PerAct2 bimanual benchmark and outperform RGB/RGB-D baselines in real-world tests.
Stream3D-VLM adds autoregressive streaming control, VSFI geometry integration, GAVC compression, and a 1M-pair benchmark to enable real-time 3D VLM performance that beats prior models on 29 online and offline tasks.
Reasmory turns 3D reconstruction into validated program-executable memory for VLMs, yielding 6-18% gains on spatial reasoning benchmarks over direct baselines.
ProSR adds a Counterfactual Invariance Penalty and a Tail Drift Penalty to shape VLM reasoning trajectories for better visual dependence and stability on spatial tasks.
Adding per-frame camera-pose supervision to a video MLLM improves spatial and general video question answering by 2–6% and yields SOTA streaming pose estimates on ScanNet.
DepthVLM converts a standard VLM into a dense metric depth predictor by attaching a lightweight head and training under unified vision-text supervision, outperforming prior VLMs and some pure vision models on a new indoor-outdoor benchmark.
FGQ applies diagonal Fisher information to guide learnable affine transformations in PTQ for multi-task VGGT, yielding up to 39% relative gains over baselines at 4-bit quantization.
Closed-loop VLM agents with multi-view feedback, object axes overlays, and single-axis rotations predict text-guided goal 6D poses better than prior methods and improve zero-shot robot manipulation.
GeoVR distills camera pose, depth, scale, and multi-scale 3D features from pre-trained models into MLLMs via video supervision to improve spatial reasoning.
OpenVLThinkerV2 applies a new Gaussian GRPO training objective with response and entropy shaping to outperform prior open-source and proprietary models on 18 visual reasoning benchmarks.
citing papers explorer
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Thinking with Imagination: Agentic Visual Spatial Reasoning with World Simulators
Astra couples an RL-trained VLM policy with a view-consistent Bagel-based world simulator to enable agentic imagination during spatial reasoning, yielding benchmark gains on MMSI-Bench and MindCube.
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Thinking with Geometry: Active Geometry Integration for Spatial Reasoning
GeoThinker enables active, task-conditioned geometry integration in MLLMs via spatial-grounded fusion and importance gating, reaching 72.6 on VSI-Bench.
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3D HAMSTER: Bridging Planning and Control in Hierarchical Vision Language Action Models through 3D Trajectory Guidance
3D HAMSTER adds depth encoding and reconstruction to VLMs to produce 3D waypoint sequences that feed directly into pointcloud policies, claiming better generalization than 2D baselines under shifts.
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MV-Actor: Aligning Multi-View Semantics and Spatial Awareness for Bimanual Manipulation
MV-Actor proposes a multi-view framework using semantic interaction, semantic-spatial token interaction, and guided depth repair to reach 87.8% success on the PerAct2 bimanual benchmark and outperform RGB/RGB-D baselines in real-world tests.
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Stream3D-VLM: Online 3D Spatial Understanding with Incremental Geometry Priors
Stream3D-VLM adds autoregressive streaming control, VSFI geometry integration, GAVC compression, and a 1M-pair benchmark to enable real-time 3D VLM performance that beats prior models on 29 online and offline tasks.
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Reasmory: 3D Reconstruction as Explicit Memory for VLMs Spatial Reasoning
Reasmory turns 3D reconstruction into validated program-executable memory for VLMs, yielding 6-18% gains on spatial reasoning benchmarks over direct baselines.
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ProSR: Process-Shaped Spatial Reasoning for Reliable Chain-of-Thought in VLMs
ProSR adds a Counterfactual Invariance Penalty and a Tail Drift Penalty to shape VLM reasoning trajectories for better visual dependence and stability on spatial tasks.
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Cambrian-P: Pose-Grounded Video Understanding
Adding per-frame camera-pose supervision to a video MLLM improves spatial and general video question answering by 2–6% and yields SOTA streaming pose estimates on ScanNet.
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Unlocking Dense Metric Depth Estimation in VLMs
DepthVLM converts a standard VLM into a dense metric depth predictor by attaching a lightweight head and training under unified vision-text supervision, outperforming prior VLMs and some pure vision models on a new indoor-outdoor benchmark.
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Not All Tasks Quantize Equally: Fisher-Guided Quantization for Visual Geometry Transformer
FGQ applies diagonal Fisher information to guide learnable affine transformations in PTQ for multi-task VGGT, yielding up to 39% relative gains over baselines at 4-bit quantization.
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Text-Guided 6D Object Pose Rearrangement via Closed-Loop VLM Agents
Closed-loop VLM agents with multi-view feedback, object axes overlays, and single-axis rotations predict text-guided goal 6D poses better than prior methods and improve zero-shot robot manipulation.
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Learning Geometric Representations from Videos for Spatial Intelligent Multimodal Large Language Models
GeoVR distills camera pose, depth, scale, and multi-scale 3D features from pre-trained models into MLLMs via video supervision to improve spatial reasoning.
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OpenVLThinkerV2: A Generalist Multimodal Reasoning Model for Multi-domain Visual Tasks
OpenVLThinkerV2 applies a new Gaussian GRPO training objective with response and entropy shaping to outperform prior open-source and proprietary models on 18 visual reasoning benchmarks.