Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:56:34.381892Z
Paper Citation Record · LEDGER
As of 23 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 9 inbound Pith citation observations for arXiv:2506.01031.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T11:56:34.381892Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-14T04:34:35.166153Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T02:16:27.244688Z
65 of 65 outbound references displayed
External citation measurements
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Observation 21215b46-a989-48d6-a31a-5c189b1c4039 · outbound
NavBench: Probing Multimodal Large Language Models for Embodied Navigation Visual instruction tuning
Reference 1
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
Reference 2
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Reference 3
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Making the v in vqa matter: Elevating the role of image understanding in visual question answering
Reference 4
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis
Reference 5
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts
Reference 6
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Spatialbot: Precise spatial understanding with vision language models
Reference 7
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Thinking in Space: How Multimodal Large Language Models See, Remember and Recall Spaces
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Reid, Stephen Gould, and Anton van den Hengel
Reference 9
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Object goal navigation using goal-oriented semantic exploration
Reference 10
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation The spatial semantic hierarchy
Reference 11
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Intern vl: Scaling up vision foundation models and aligning for generic visual-linguistic tasks
Reference 12
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Flamingo: a Visual Language Model for Few-Shot Learning
Reference 13
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond
Reference 14
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Improved baselines with visual instruction tuning
Reference 15
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Gqa: A new dataset for real-world visual reasoning and compositional question answering
Reference 16
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Ok-vqa: A visual question answering benchmark requiring external knowledge
Reference 17
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Observation 0e8687be-74f3-4bb6-970e-1e0b67838695 · outbound
NavBench: Probing Multimodal Large Language Models for Embodied Navigation Towards vqa models that can read
Reference 18
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Observation 7a65ad5c-e12b-4aa9-9f5e-735fd19daff0 · outbound
NavBench: Probing Multimodal Large Language Models for Embodied Navigation A Survey on Multimodal Large Language Models
Reference 19
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Mmbench: Is your multi-modal model an all-around player? In European Conference on Computer Vision, pages 216–233
Reference 20
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities
Reference 21
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Scanreason: Empowering 3d visual grounding with reasoning capabilities
Reference 22
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation REVERIE: remote embodied visual referring expression in real indoor environments
Reference 23
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Navigating the Nuances: A Fine-grained Evaluation of Vision-Language Navigation
Reference 24
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Target-driven visual navigation in indoor scenes using deep reinforcement learning
Reference 25
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Instance-Specific Image Goal Navigation: Training Embodied Agents to Find Object Instances
Reference 26
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Observation d0a96ec0-53bb-487f-8be0-5d67cb8cc933 · outbound
NavBench: Probing Multimodal Large Language Models for Embodied Navigation Habitat: A platform for embodied ai research
Reference 27
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation History aware multimodal transformer for vision-and-language navigation
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Vision-and-language navigation today and tomorrow: A survey in the era of foundation models
Reference 29
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Room-across-room: Mul- tilingual vision-and-language navigation with dense spatiotemporal grounding
Reference 30
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Vision-and-dialog navigation
Reference 31
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Find what you want: Learning demand-conditioned object attribute space for demand-driven navigation
Reference 32
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Object-and-action aware model for visual language navigation
Reference 33
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Language and visual entity relationship graph for agent navigation
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Neighbor-view enhanced model for vision and language navigation
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Towards learning a generic agent for vision-and-language navigation via pre-training
Reference 36
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Airbert: In- domain pretraining for vision-and-language navigation
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Improving vision-and-language navigation with image-text pairs from the web
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation History aware multimodal transformer for vision-and-language navigation
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Hop: History-and-order aware pre-training for vision-and-language navigation
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Hop+: History-enhanced and order-aware pre-training for vision-and-language navigation
Reference 41
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Bevbert: Mul- timodal map pre-training for language-guided navigation
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Bird’s-eye-view scene graph for vision-language navigation
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Gridmm: Grid memory map for vision-and-language navigation
Reference 44
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Scaling data generation in vision-and-language navigation
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation A new path: Scaling vision-and-language navigation with synthetic instructions and imitation learning
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Reference 47
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Esc: Exploration with soft commonsense constraints for zero-shot object navigation
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Cows on pasture: Baselines and benchmarks for language-driven zero-shot object navigation
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation InstructNav: Zero-shot System for Generic Instruction Navigation in Unexplored Environment
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Open-Nav: Exploring Zero-Shot Vision-and-Language Navigation in Continuous Environment with Open-Source LLMs
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Mapgpt: Map- guided prompting with adaptive path planning for vision-and-language navigation
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Reference 55
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Reference 60
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation LLaVA-OneVision: Easy Visual Task Transfer
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NavBench: Probing Multimodal Large Language Models for Embodied Navigation Gonzalez, Hao Zhang, and Ion Stoica
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MirrorBench: Evaluating Self-centric Intelligence in MLLMs by Introducing a Mirror NavBench: Probing Multimodal Large Language Models for Embodied Navigation
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