Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-21T12:58:30.777235Z
Paper Citation Record · LEDGER
VLANeXt: Recipes for Building Strong VLA Models
As of 3 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 6 inbound Pith citation observations for arXiv:2602.18532.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-03T06:30:56.289259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-28T22:39:15.211339Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-04T14:09:53.718432Z
Reference resolution
41 of 41 outbound references displayed
- verified exact34
- verified fuzzy1
- unresolved0
- parse uncertain0
- malformed identifier1
- metadata mismatch5
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation b2529d4c-c5b3-4386-af60-45f20360ac71 · outbound
This paper cites Qwen3-VL Technical Report.
VLANeXt: Recipes for Building Strong VLA Models Qwen3-VL Technical Report
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.843841Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 7a76bb13-8fbc-4c1f-a856-83b19701ba6b · outbound
This paper cites 3d cavla: Leveraging depth and 3d context to generalize vision language action models for unseen tasks.
VLANeXt: Recipes for Building Strong VLA Models 3d cavla: Leveraging depth and 3d context to generalize vision language action models for unseen tasks
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T13:00:09.938258Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation ea65ca17-e5fe-4943-9cd2-aad2b1be43dc · outbound
This paper cites Motus: A Unified Latent Action World Model.
VLANeXt: Recipes for Building Strong VLA Models Motus: A Unified Latent Action World Model
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.853621Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 91a89579-96fe-4a66-bd99-578a2e942d9b · outbound
This paper cites GR00T N1: An Open Foundation Model for Generalist Humanoid Robots.
VLANeXt: Recipes for Building Strong VLA Models GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
Reference 4
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.829471Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 6a830836-c062-455f-9806-e218bc442433 · outbound
This paper cites $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control.
VLANeXt: Recipes for Building Strong VLA Models $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
Reference 5
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.800641Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 3403115c-1040-4070-a9d6-984910f7010d · outbound
This paper cites RynnVLA-002: A Unified Vision-Language-Action and World Model.
VLANeXt: Recipes for Building Strong VLA Models RynnVLA-002: A Unified Vision-Language-Action and World Model
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-06-02T02:03:36.254972Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 07a9d8cc-c5b5-4d83-a626-80ea2d0ad0fa · outbound
This paper cites Combatvla: An efficient vision-language-action model for combat tasks in 3d action role-playing games.arXiv preprint arXiv:2503.09527, 2025a.
VLANeXt: Recipes for Building Strong VLA Models Combatvla: An efficient vision-language-action model for combat tasks in 3d action role-playing games.arXiv preprint arXiv:2503.09527, 2025a
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T13:00:09.917410Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 3a721f1f-b528-43cd-9b49-b910113cc8c1 · outbound
This paper cites Emu3.5: Native Multimodal Models are World Learners.
VLANeXt: Recipes for Building Strong VLA Models Emu3.5: Native Multimodal Models are World Learners
Reference 8
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.819893Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 2843b0aa-9727-4034-a106-5d3bff1f88ab · outbound
This paper cites Humanoid-VLA: Towards Universal Humanoid Control with Visual Integration.
VLANeXt: Recipes for Building Strong VLA Models Humanoid-VLA: Towards Universal Humanoid Control with Visual Integration
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T13:00:09.825098Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 8b3cf350-377f-4801-b242-20b4adf402eb · outbound
This paper cites Srpo: Self-referential policy optimization for vision-language-action models.
VLANeXt: Recipes for Building Strong VLA Models Srpo: Self-referential policy optimization for vision-language-action models
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T13:00:09.943727Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation f82c2aad-f36e-4573-be43-5453fa722962 · outbound
This paper cites Vla-0: Building state-of-the-art vlas with zero modification.
VLANeXt: Recipes for Building Strong VLA Models Vla-0: Building state-of-the-art vlas with zero modification
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T13:00:09.948808Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation b207c2ce-82e7-45ea-878d-caf95d688861 · outbound
This paper cites The Llama 3 Herd of Models.
VLANeXt: Recipes for Building Strong VLA Models The Llama 3 Herd of Models
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.877521Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation eaa56b9f-aad6-4800-98a0-4a53e04b47e6 · outbound
This paper cites Vla-reasoner: Empowering vision-language-action models with reasoning via online monte carlo tree search.
VLANeXt: Recipes for Building Strong VLA Models Vla-reasoner: Empowering vision-language-action models with reasoning via online monte carlo tree search
Reference 13
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T13:00:09.902948Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation f0cc7abe-4ecd-4a84-8899-020d74d74d93 · outbound
This paper cites Training Large Language Models to Reason in a Continuous Latent Space.
VLANeXt: Recipes for Building Strong VLA Models Training Large Language Models to Reason in a Continuous Latent Space
Reference 14
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.872549Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 14e156da-bc7c-4d62-92c7-27c5c93c74ea · outbound
This paper cites ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent Planning.
VLANeXt: Recipes for Building Strong VLA Models ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent Planning
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.922795Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 562aa024-58df-464a-823f-066859c496f7 · outbound
This paper cites NORA: A Small Open-Sourced Generalist Vision Language Action Model for Embodied Tasks.
VLANeXt: Recipes for Building Strong VLA Models NORA: A Small Open-Sourced Generalist Vision Language Action Model for Embodied Tasks
Reference 16
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-21T13:00:09.958097Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation fb9fa478-13d0-4ec9-b9ca-ca2f7c7e2e85 · outbound
This paper cites $\pi^{*}_{0.6}$: a VLA That Learns From Experience.
VLANeXt: Recipes for Building Strong VLA Models $\pi^{*}_{0.6}$: a VLA That Learns From Experience
Reference 17
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.863649Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 7feaa7fa-d48d-45e3-9943-bdf0ef59ee9e · outbound
This paper cites Emergence of human to robot transfer in vision-language-action models.arXiv preprint arXiv:2512.22414.
VLANeXt: Recipes for Building Strong VLA Models Emergence of human to robot transfer in vision-language-action models.arXiv preprint arXiv:2512.22414
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T13:00:09.953953Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation a2995e19-b286-431b-8389-ed660c291555 · outbound
This paper cites Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success.
VLANeXt: Recipes for Building Strong VLA Models Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
Reference 19
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-21T13:00:09.983615Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 553266e8-9b48-40fd-9460-5071d629a452 · outbound
This paper cites Adapt Your Body: Mitigating Proprioception Shifts in Imitation Learning.
VLANeXt: Recipes for Building Strong VLA Models Adapt Your Body: Mitigating Proprioception Shifts in Imitation Learning
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T13:00:09.927300Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 8624a883-38a4-4a8c-a3dc-56efec558575 · outbound
This paper cites MolmoAct: Action Reasoning Models that can Reason in Space.
VLANeXt: Recipes for Building Strong VLA Models MolmoAct: Action Reasoning Models that can Reason in Space
Reference 21
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.933214Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 340d6e3b-10d0-4dff-936f-89ffa78a0dec · outbound
This paper cites CronusVLA: Towards Efficient and Robust Manipulation via Multi-Frame Vision-Language-Action Modeling, October 2025.
VLANeXt: Recipes for Building Strong VLA Models CronusVLA: Towards Efficient and Robust Manipulation via Multi-Frame Vision-Language-Action Modeling, October 2025
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T13:00:09.788929Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation a004a340-b210-4fa3-a532-5fd319d6f2b5 · outbound
This paper cites Mm-act: Learn from multimodal parallel generation to act.arXiv preprint arXiv:2512.00975.
VLANeXt: Recipes for Building Strong VLA Models Mm-act: Learn from multimodal parallel generation to act.arXiv preprint arXiv:2512.00975
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T13:00:09.897990Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation bb374873-0a04-4ebc-b858-0cd97984f424 · outbound
This paper cites VLA-RL: Towards Masterful and General Robotic Manipulation with Scalable Reinforcement Learning.
VLANeXt: Recipes for Building Strong VLA Models VLA-RL: Towards Masterful and General Robotic Manipulation with Scalable Reinforcement Learning
Reference 24
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.810733Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 10ea45f0-60d8-4f14-b5c3-0a5129e41dd5 · outbound
This paper cites F1: A Vision-Language-Action Model Bridging Understanding and Generation to Actions.
VLANeXt: Recipes for Building Strong VLA Models F1: A Vision-Language-Action Model Bridging Understanding and Generation to Actions
Reference 25
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.839448Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 81c2b160-50b1-46f6-adb6-5307249002d5 · outbound
This paper cites A Survey on Vision-Language-Action Models for Embodied AI.
VLANeXt: Recipes for Building Strong VLA Models A Survey on Vision-Language-Action Models for Embodied AI
Reference 26
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.966662Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 7f42c612-968c-4900-abd2-b075f39f4f38 · outbound
This paper cites Transfer between Modalities with MetaQueries.
VLANeXt: Recipes for Building Strong VLA Models Transfer between Modalities with MetaQueries
Reference 27
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-21T13:00:09.815233Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation c2198c2b-e888-4d1f-b497-b45c68da367f · outbound
This paper cites FAST: Efficient Action Tokenization for Vision-Language-Action Models.
VLANeXt: Recipes for Building Strong VLA Models FAST: Efficient Action Tokenization for Vision-Language-Action Models
Reference 28
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.805192Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 5e275428-fc9b-4194-94da-00872201c09d · outbound
This paper cites SpatialVLA: Exploring Spatial Representations for Visual-Language-Action Model.
VLANeXt: Recipes for Building Strong VLA Models SpatialVLA: Exploring Spatial Representations for Visual-Language-Action Model
Reference 29
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.974891Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 3e623b8b-dfec-4782-bb0b-0e1bece95321 · outbound
This paper cites FLOWER: Democratizing Generalist Robot Policies with Efficient Vision-Language-Action Flow Policies.
VLANeXt: Recipes for Building Strong VLA Models FLOWER: Democratizing Generalist Robot Policies with Efficient Vision-Language-Action Flow Policies
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T13:00:09.834452Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation e4622c13-61b2-431f-a2fb-aa6d7df9ab69 · outbound
This paper cites MemoryVLA: Perceptual-Cognitive Memory in Vision-Language-Action Models for Robotic Manipulation.
VLANeXt: Recipes for Building Strong VLA Models MemoryVLA: Perceptual-Cognitive Memory in Vision-Language-Action Models for Robotic Manipulation
Reference 31
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.882340Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation f83a9739-9b9f-4adf-ae36-042adf8aab82 · outbound
This paper cites SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics.
VLANeXt: Recipes for Building Strong VLA Models SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
Reference 32
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.892667Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation fee226ad-4cf7-4ec4-8e05-8746dc4aae4d · outbound
This paper cites Gemini Robotics: Bringing AI into the Physical World.
VLANeXt: Recipes for Building Strong VLA Models Gemini Robotics: Bringing AI into the Physical World
Reference 33
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-21T13:00:09.848903Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation bb42da93-9506-4e30-bc3c-1fa1ea1ba714 · outbound
This paper cites SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features.
VLANeXt: Recipes for Building Strong VLA Models SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features
Reference 34
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-21T13:00:09.970523Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 2d520977-76dd-4e28-b380-d883e3d437b3 · outbound
This paper cites End-to-end Listen, Look, Speak and Act.
VLANeXt: Recipes for Building Strong VLA Models End-to-end Listen, Look, Speak and Act
Reference 35
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.979464Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 71c88fad-a9b5-4a7f-b2be-7ada6c9808c1 · outbound
This paper cites World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training.
VLANeXt: Recipes for Building Strong VLA Models World-Env: Leveraging World Model as a Virtual Environment for VLA Post-Training
Reference 36
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T13:00:09.868211Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation b231477a-b9f9-488e-a402-c4690cd96367 · outbound
This paper cites 4d-vla: Spatiotemporal vision-language-action pretraining with cross-scene calibration.arXiv preprint arXiv:2506.22242, 2025a.
VLANeXt: Recipes for Building Strong VLA Models 4d-vla: Spatiotemporal vision-language-action pretraining with cross-scene calibration.arXiv preprint arXiv:2506.22242, 2025a
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T13:00:09.795112Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation bf431467-507b-4f2d-8d10-0212c85a8db3 · outbound
This paper cites Dreamvla: a vision-language-action model dreamed with comprehen- sive world knowledge.
VLANeXt: Recipes for Building Strong VLA Models Dreamvla: a vision-language-action model dreamed with comprehen- sive world knowledge
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T13:00:09.962649Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 563fcdf1-8af8-4374-a347-18814a6f7153 · outbound
This paper cites Flowvla: Visual chain of thought-based motion reason- ing for vision-language-action models.arXiv preprint arXiv:2508.18269.
VLANeXt: Recipes for Building Strong VLA Models Flowvla: Visual chain of thought-based motion reason- ing for vision-language-action models.arXiv preprint arXiv:2508.18269
Reference 39
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T13:00:09.858979Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 65c5a765-12b4-45d2-82a8-53d1723e8c90 · outbound
This paper cites More Experimental Results A.1.
VLANeXt: Recipes for Building Strong VLA Models More Experimental Results A.1
Reference 40
- Resolution
- malformed identifier
- raw_fallback, observed 2026-05-21T13:00:10.452298Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation bc88e369-620b-4fa8-a040-c67ca39c56a0 · outbound
This paper cites primordial soup.
VLANeXt: Recipes for Building Strong VLA Models primordial soup
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T13:00:10.455299Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Pith citing papers
Observation c136c42d-0514-483d-8f53-d9fc1928c427 · inbound
VLA-GSE: Boosting Parameter-Efficient Fine-Tuning in VLA with Generalized and Specialized Experts cites this paper.
VLA-GSE: Boosting Parameter-Efficient Fine-Tuning in VLA with Generalized and Specialized Experts VLANeXt: Recipes for Building Strong VLA Models
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T02:04:11.439936Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 54fbf5b6-c48d-4a25-815b-fedfe200d0ce · inbound
VLA-GSE: Boosting Parameter-Efficient Fine-Tuning in VLA with Generalized and Specialized Experts cites this paper.
VLA-GSE: Boosting Parameter-Efficient Fine-Tuning in VLA with Generalized and Specialized Experts VLANeXt: Recipes for Building Strong VLA Models
Reference 29
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T02:04:11.439936Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 102eb8f3-cd5d-49f3-a700-c087586b9b1f · inbound
Rethinking Muon Beyond Pretraining: Spectral Failures and High-Pass Remedies for VLA and RLVR cites this paper.
Rethinking Muon Beyond Pretraining: Spectral Failures and High-Pass Remedies for VLA and RLVR VLANeXt: Recipes for Building Strong VLA Models
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T02:04:11.439936Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 20be91d9-bff0-49eb-a1b7-848a0b41da9a · inbound
Hide-and-Seek in Trajectories: Discovering Failure Signals for VLA Runtime Monitoring cites this paper.
Hide-and-Seek in Trajectories: Discovering Failure Signals for VLA Runtime Monitoring VLANeXt: Recipes for Building Strong VLA Models
Reference 5
- Resolution
- verified exact
- local_arxiv, observed 2026-06-28T22:42:46.568474Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 94d4f7ab-fae3-4fa6-b308-181e2d207902 · inbound
PearlVLA: Progressive Embodied Action-Plan Refinement in Latent Space cites this paper.
PearlVLA: Progressive Embodied Action-Plan Refinement in Latent Space VLANeXt: Recipes for Building Strong VLA Models
Reference 13
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T20:58:58.543012Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.
Observation 5e853214-c132-47ed-87d7-1375423f15f7 · inbound
RouterVLA: Turning Smoke Tests into Supervision for Heterogeneous VLA Selection cites this paper.
RouterVLA: Turning Smoke Tests into Supervision for Heterogeneous VLA Selection VLANeXt: Recipes for Building Strong VLA Models
Reference 30
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T14:09:53.719676Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-03T06:30:56.289259+00:00.