Vision Transformer Adapter for Dense Predictions | Paper Citation Record

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Uncertainty in Real-Time Semantic Segmentation on Embedded Systems cites this paper.

Uncertainty in Real-Time Semantic Segmentation on Embedded Systems Vision Transformer Adapter for Dense Predictions

Reference 13

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T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models cites this paper.

T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for Text-to-Image Diffusion Models Vision Transformer Adapter for Dense Predictions

Reference 3

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Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey cites this paper.

Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey Vision Transformer Adapter for Dense Predictions

Reference 189

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Self-Supervised Monocular 4D Scene Reconstruction for Egocentric Videos cites this paper.

Self-Supervised Monocular 4D Scene Reconstruction for Egocentric Videos Vision Transformer Adapter for Dense Predictions

Reference 9

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Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation cites this paper.

Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation Vision Transformer Adapter for Dense Predictions

Reference 10

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BiDense: Binarization for Dense Prediction cites this paper.

BiDense: Binarization for Dense Prediction Vision Transformer Adapter for Dense Predictions

Reference 6

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Video-to-Task Learning via Motion-Guided Attention for Few-Shot Action Recognition cites this paper.

Video-to-Task Learning via Motion-Guided Attention for Few-Shot Action Recognition Vision Transformer Adapter for Dense Predictions

Reference 32

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Enhancing Parameter-Efficient Fine-Tuning of Vision Transformers through Frequency-Based Adaptation cites this paper.

Enhancing Parameter-Efficient Fine-Tuning of Vision Transformers through Frequency-Based Adaptation Vision Transformer Adapter for Dense Predictions

Reference 10

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LQ-Adapter: ViT-Adapter with Learnable Queries for Gallbladder Cancer Detection from Ultrasound Image cites this paper.

LQ-Adapter: ViT-Adapter with Learnable Queries for Gallbladder Cancer Detection from Ultrasound Image Vision Transformer Adapter for Dense Predictions

Reference 10

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PETALface: Parameter Efficient Transfer Learning for Low-resolution Face Recognition cites this paper.

PETALface: Parameter Efficient Transfer Learning for Low-resolution Face Recognition Vision Transformer Adapter for Dense Predictions

Reference 6

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SAFIRE: Segment Any Forged Image Region cites this paper.

SAFIRE: Segment Any Forged Image Region Vision Transformer Adapter for Dense Predictions

Reference 5

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SAM-Mamba: Mamba Guided SAM Architecture for Generalized Zero-Shot Polyp Segmentation cites this paper.

SAM-Mamba: Mamba Guided SAM Architecture for Generalized Zero-Shot Polyp Segmentation Vision Transformer Adapter for Dense Predictions

Reference 5

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VELoRA: A Low-Rank Adaptation Approach for Efficient RGB-Event based Recognition cites this paper.

VELoRA: A Low-Rank Adaptation Approach for Efficient RGB-Event based Recognition Vision Transformer Adapter for Dense Predictions

Reference 17

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STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes cites this paper.

STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes Vision Transformer Adapter for Dense Predictions

Reference 3

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FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection cites this paper.

FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection Vision Transformer Adapter for Dense Predictions

Reference 9

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MADation: Face Morphing Attack Detection with Foundation Models cites this paper.

MADation: Face Morphing Attack Detection with Foundation Models Vision Transformer Adapter for Dense Predictions

Reference 10

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SELMA3D challenge: Self-supervised learning for 3D light-sheet microscopy image segmentation cites this paper.

SELMA3D challenge: Self-supervised learning for 3D light-sheet microscopy image segmentation Vision Transformer Adapter for Dense Predictions

Reference 52

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Enhancing Low-Cost Video Editing with Lightweight Adaptors and Temporal-Aware Inversion cites this paper.

Enhancing Low-Cost Video Editing with Lightweight Adaptors and Temporal-Aware Inversion Vision Transformer Adapter for Dense Predictions

Reference 7

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SAM-DA: Decoder Adapter for Efficient Medical Domain Adaptation cites this paper.

SAM-DA: Decoder Adapter for Efficient Medical Domain Adaptation Vision Transformer Adapter for Dense Predictions

Reference 5

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Densely Connected Parameter-Efficient Tuning for Referring Image Segmentation cites this paper.

Densely Connected Parameter-Efficient Tuning for Referring Image Segmentation Vision Transformer Adapter for Dense Predictions

Reference 3

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ASCENT-ViT: Attention-based Scale-aware Concept Learning Framework for Enhanced Alignment in Vision Transformers cites this paper.

ASCENT-ViT: Attention-based Scale-aware Concept Learning Framework for Enhanced Alignment in Vision Transformers Vision Transformer Adapter for Dense Predictions

Reference 2019

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Maximizing the Position Embedding for Vision Transformers with Global Average Pooling cites this paper.

Maximizing the Position Embedding for Vision Transformers with Global Average Pooling Vision Transformer Adapter for Dense Predictions

Reference 6

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From Visuals to Vocabulary: Establishing Equivalence Between Image and Text Token Through Autoregressive Pre-training in MLLMs cites this paper.

From Visuals to Vocabulary: Establishing Equivalence Between Image and Text Token Through Autoregressive Pre-training in MLLMs Vision Transformer Adapter for Dense Predictions

Reference 7

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Radar-Guided Polynomial Fitting for Metric Depth Estimation cites this paper.

Radar-Guided Polynomial Fitting for Metric Depth Estimation Vision Transformer Adapter for Dense Predictions

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:37:12.799127Z

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PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models cites this paper.

PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models Vision Transformer Adapter for Dense Predictions

Reference 90

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CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive Survey cites this paper.

CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive Survey Vision Transformer Adapter for Dense Predictions

Reference 20

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Hyb-KAN ViT: Hybrid Kolmogorov-Arnold Networks Augmented Vision Transformer cites this paper.

Hyb-KAN ViT: Hybrid Kolmogorov-Arnold Networks Augmented Vision Transformer Vision Transformer Adapter for Dense Predictions

Reference 55

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Locality-Aware Zero-Shot Human-Object Interaction Detection cites this paper.

Locality-Aware Zero-Shot Human-Object Interaction Detection Vision Transformer Adapter for Dense Predictions

Reference 4

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Data-Efficient Challenges in Visual Inductive Priors: A Retrospective cites this paper.

Data-Efficient Challenges in Visual Inductive Priors: A Retrospective Vision Transformer Adapter for Dense Predictions

Reference 28

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Efficient Medical Vision-Language Alignment Through Adapting Masked Vision Models cites this paper.

Efficient Medical Vision-Language Alignment Through Adapting Masked Vision Models Vision Transformer Adapter for Dense Predictions

Reference 41

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Learning to Adapt Frozen CLIP for Few-Shot Test-Time Domain Adaptation cites this paper.

Learning to Adapt Frozen CLIP for Few-Shot Test-Time Domain Adaptation Vision Transformer Adapter for Dense Predictions

Reference 3

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Mamba Guided Boundary Prior Matters: A New Perspective for Generalized Polyp Segmentation cites this paper.

Mamba Guided Boundary Prior Matters: A New Perspective for Generalized Polyp Segmentation Vision Transformer Adapter for Dense Predictions

Reference 5

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SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement cites this paper.

SAILViT: Towards Robust and Generalizable Visual Backbones for MLLMs via Gradual Feature Refinement Vision Transformer Adapter for Dense Predictions

Reference 13

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Colorectal Cancer Tumor Grade Segmentation in Digital Histopathology Images: From Giga to Mini Challenge cites this paper.

Colorectal Cancer Tumor Grade Segmentation in Digital Histopathology Images: From Giga to Mini Challenge Vision Transformer Adapter for Dense Predictions

Reference 31

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Beyond Appearance: Geometric Cues for Robust Video Instance Segmentation cites this paper.

Beyond Appearance: Geometric Cues for Robust Video Instance Segmentation Vision Transformer Adapter for Dense Predictions

Reference 7

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Latest Object Memory Management for Temporally Consistent Video Instance Segmentation cites this paper.

Latest Object Memory Management for Temporally Consistent Video Instance Segmentation Vision Transformer Adapter for Dense Predictions

Reference 4

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MPT: Motion Prompt Tuning for Micro-Expression Recognition cites this paper.

MPT: Motion Prompt Tuning for Micro-Expression Recognition Vision Transformer Adapter for Dense Predictions

Reference 44

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Neural Proteomics Fields for Super-resolved Spatial Proteomics Prediction cites this paper.

Neural Proteomics Fields for Super-resolved Spatial Proteomics Prediction Vision Transformer Adapter for Dense Predictions

Reference 7

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AI-driven Remote Facial Skin Hydration and TEWL Assessment from Selfie Images: A Systematic Solution cites this paper.

AI-driven Remote Facial Skin Hydration and TEWL Assessment from Selfie Images: A Systematic Solution Vision Transformer Adapter for Dense Predictions

Reference 10

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FoMo4Wheat: Toward reliable crop vision foundation models with globally curated data cites this paper.

FoMo4Wheat: Toward reliable crop vision foundation models with globally curated data Vision Transformer Adapter for Dense Predictions

Reference 72

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Live(r) Die: Predicting Survival in Colorectal Liver Metastasis cites this paper.

Live(r) Die: Predicting Survival in Colorectal Liver Metastasis Vision Transformer Adapter for Dense Predictions

Reference 2019

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Delineate Anything Flow: Fast, Country-Level Field Boundary Detection from Any Source cites this paper.

Delineate Anything Flow: Fast, Country-Level Field Boundary Detection from Any Source Vision Transformer Adapter for Dense Predictions

Reference 1

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Exploring the Rashomon Set for Concept-Based Models cites this paper.

Exploring the Rashomon Set for Concept-Based Models Vision Transformer Adapter for Dense Predictions

Reference 8

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Foundation Model-Driven Semantic Change Detection in Remote Sensing Imagery cites this paper.

Foundation Model-Driven Semantic Change Detection in Remote Sensing Imagery Vision Transformer Adapter for Dense Predictions

Reference 37

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Foundation Model-Driven Semantic Change Detection in Remote Sensing Imagery cites this paper.

Foundation Model-Driven Semantic Change Detection in Remote Sensing Imagery Vision Transformer Adapter for Dense Predictions

Reference 37

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DinoRADE: Full Spectral Radar-Camera Fusion with Vision Foundation Model Features for Multi-class Object Detection in Adverse Weather cites this paper.

DinoRADE: Full Spectral Radar-Camera Fusion with Vision Foundation Model Features for Multi-class Object Detection in Adverse Weather Vision Transformer Adapter for Dense Predictions

Reference 3

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Frequency-Enhanced Diffusion Models: Curriculum-Guided Semantic Alignment for Zero-Shot Skeleton Action Recognition cites this paper.

Frequency-Enhanced Diffusion Models: Curriculum-Guided Semantic Alignment for Zero-Shot Skeleton Action Recognition Vision Transformer Adapter for Dense Predictions

Reference 68

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Memory-Efficient Transfer Learning with Fading Side Networks via Masked Dual Path Distillation cites this paper.

Memory-Efficient Transfer Learning with Fading Side Networks via Masked Dual Path Distillation Vision Transformer Adapter for Dense Predictions

Reference 13

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HAMSA: Scanning-Free Vision State Space Models via SpectralPulseNet cites this paper.

HAMSA: Scanning-Free Vision State Space Models via SpectralPulseNet Vision Transformer Adapter for Dense Predictions

Reference 3

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VFM$^{4}$SDG: Unveiling the Power of VFMs for Single-Domain Generalized Object Detection cites this paper.

VFM$^{4}$SDG: Unveiling the Power of VFMs for Single-Domain Generalized Object Detection Vision Transformer Adapter for Dense Predictions

Reference 47

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VFM$^{4}$SDG: Unveiling the Power of VFMs for Single-Domain Generalized Object Detection cites this paper.

VFM$^{4}$SDG: Unveiling the Power of VFMs for Single-Domain Generalized Object Detection Vision Transformer Adapter for Dense Predictions

Reference 47

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MP-ISMoE: Mixed-Precision Interactive Side Mixture-of-Experts for Efficient Transfer Learning cites this paper.

MP-ISMoE: Mixed-Precision Interactive Side Mixture-of-Experts for Efficient Transfer Learning Vision Transformer Adapter for Dense Predictions

Reference 57

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Beyond ViT Tokens: Masked-Diffusion Pretrained Convolutional Pathology Foundation Model for Cell-Level Dense Prediction cites this paper.

Beyond ViT Tokens: Masked-Diffusion Pretrained Convolutional Pathology Foundation Model for Cell-Level Dense Prediction Vision Transformer Adapter for Dense Predictions

Reference 28

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Unleashing Vision Transformer Potential In Image Quality Assessment via Global-Local Adaptive Interaction cites this paper.

Unleashing Vision Transformer Potential In Image Quality Assessment via Global-Local Adaptive Interaction Vision Transformer Adapter for Dense Predictions

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-20T12:53:17.737755Z

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Selective, Regularized, and Calibrated: Harnessing Vision Foundation Models for Cross-Domain Few-Shot Semantic Segmentation cites this paper.

Selective, Regularized, and Calibrated: Harnessing Vision Foundation Models for Cross-Domain Few-Shot Semantic Segmentation Vision Transformer Adapter for Dense Predictions

Reference 6

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Adapting Prithvi-EO for Fallow Detection for Food-Water Nexus: ViT-Adapter Necks and Parameter-Efficient Backbone tuning of Geospatial Foundation Model cites this paper.

Adapting Prithvi-EO for Fallow Detection for Food-Water Nexus: ViT-Adapter Necks and Parameter-Efficient Backbone tuning of Geospatial Foundation Model Vision Transformer Adapter for Dense Predictions

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-07-03T11:18:03.458026Z

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Timage: A Generative Text-in-Image Paradigm for Fine-Tuning Vision-Language Models cites this paper.

Timage: A Generative Text-in-Image Paradigm for Fine-Tuning Vision-Language Models Vision Transformer Adapter for Dense Predictions

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T03:39:29.883567Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9f390e78-9dcf-43ab-90a8-8c91f4f4b9e9 · inbound

UNITY: Attention Flow Networks for Adaptive Conditioning in Diffusion cites this paper.

UNITY: Attention Flow Networks for Adaptive Conditioning in Diffusion Vision Transformer Adapter for Dense Predictions

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T03:49:31.034417Z

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Observation bc2df1f0-09f7-4b92-b95e-eace0f4bbb29 · inbound

UNITY: Attention Flow Networks for Adaptive Conditioning in Diffusion cites this paper.

UNITY: Attention Flow Networks for Adaptive Conditioning in Diffusion Vision Transformer Adapter for Dense Predictions

Reference 1

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State Space Models Meet Remote Sensing: A Survey cites this paper.

State Space Models Meet Remote Sensing: A Survey Vision Transformer Adapter for Dense Predictions

Reference 197

Resolution: verified exact; arxiv_id, observed 2026-07-04T19:30:07.544420Z

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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REAL-OW: Rehearsal-free Open World Object Detection with Low-Rank Adaptation and Dual-Stage Objectness Modeling cites this paper.

REAL-OW: Rehearsal-free Open World Object Detection with Low-Rank Adaptation and Dual-Stage Objectness Modeling Vision Transformer Adapter for Dense Predictions

Reference 5

Resolution: unresolved; no resolver link, observed 2026-07-12T05:31:12.070781Z

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Unavailable: canonical work link unavailable.

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FBLayout: Optimizing Memory Layout for Efficient LLM Finetuning on Mobile GPUs cites this paper.

FBLayout: Optimizing Memory Layout for Efficient LLM Finetuning on Mobile GPUs Vision Transformer Adapter for Dense Predictions

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T08:23:07.456234Z

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Unavailable: canonical work link unavailable.

Observation cb3d0ccc-9a1e-4929-8d21-5ef66be8553e · inbound

iFAN: Inference-Aware Learning for Plain Mask Transformers cites this paper.

iFAN: Inference-Aware Learning for Plain Mask Transformers Vision Transformer Adapter for Dense Predictions

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T23:22:24.597250Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98e7f7e2-ac2f-46f5-8959-c96b09874528 · inbound

iFAN: Inference-Aware Learning for Plain Mask Transformers cites this paper.

iFAN: Inference-Aware Learning for Plain Mask Transformers Vision Transformer Adapter for Dense Predictions

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-15T14:57:49.518642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eb2548a9-2396-4638-ae4d-dc7f8104e90a · inbound

From Multi-Resolution Cells to Gigapixel Whole Slide Images Foundation Model for Computational Pathology cites this paper.

From Multi-Resolution Cells to Gigapixel Whole Slide Images Foundation Model for Computational Pathology Vision Transformer Adapter for Dense Predictions

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-05T17:47:37.173107Z

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Observation 7ae84642-e6d8-421c-bdeb-4647fbafa78d · inbound

LiLa-WAM: Lightweight Latent Reasoning World-Action Model for Robotic Manipulation cites this paper.

LiLa-WAM: Lightweight Latent Reasoning World-Action Model for Robotic Manipulation Vision Transformer Adapter for Dense Predictions

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-05T14:32:59.260963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63349b71-df1e-410d-9f4f-4ec79ba12302 · inbound

Understand Before Detect: Vision--Language Learning for Omni-Domain Infrared Small Target Detection cites this paper.

Understand Before Detect: Vision--Language Learning for Omni-Domain Infrared Small Target Detection Vision Transformer Adapter for Dense Predictions

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T16:39:26.295012Z

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Observation a38fb863-5643-4c92-9225-110d62a92119 · inbound

Static in Frames, Dynamic in Events: Rethinking Features in Event Cameras as Motion Cues cites this paper.

Static in Frames, Dynamic in Events: Rethinking Features in Event Cameras as Motion Cues Vision Transformer Adapter for Dense Predictions

Reference 131

Resolution: unresolved; no resolver link, observed 2026-08-12T10:52:49.118532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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