Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-20T18:20:38.720544Z
Paper Citation Record · LEDGER
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning
As of 3 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 0 inbound Pith citation observations for arXiv:2605.15997.
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
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
60 of 60 outbound references displayed
- verified exact13
- verified fuzzy46
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation b6f33f5e-a91f-43eb-bf00-ebe1f33466fe · outbound
This paper cites Lisa: Reasoning segmentation via large language model.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Lisa: Reasoning segmentation via large language model
Reference 1
- Resolution
- verified fuzzy
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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 d306c783-74b9-4d74-b984-148207d0c29b · outbound
This paper cites Glamm: Pixel grounding large multimodal model.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Glamm: Pixel grounding large multimodal model
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.988161Z
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 411752e3-67f6-455c-b08d-85f2b65a8edb · outbound
This paper cites Region-Aware Multimodal Large Language Model via SlowFast Tokenization and Pseudo-Mask Guidance for 3D CT Report Generation.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Region-Aware Multimodal Large Language Model via SlowFast Tokenization and Pseudo-Mask Guidance for 3D CT Report Generation
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T01:17:10.160901Z
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 8fd9d9ca-aac9-4b7c-96a1-47313bae96f2 · outbound
This paper cites A comprehensive review of performance metrics for computer- aided detection systems.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning A comprehensive review of performance metrics for computer- aided detection systems
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.969379Z
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 506e80c4-a807-47ab-880b-70acf930ec4d · outbound
This paper cites Ai-powered object detection in radiology: Current models, challenges, and future direction.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Ai-powered object detection in radiology: Current models, challenges, and future direction
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.000499Z
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 042e339f-73b2-409f-a8a3-561beed6f8e7 · outbound
This paper cites A systematic review of yolo-based object detection in medical imaging: Advances, challenges, and future direc- tions.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning A systematic review of yolo-based object detection in medical imaging: Advances, challenges, and future direc- tions
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.983826Z
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 3eb79dd3-86ab-4135-b23e-8bc1680867b1 · outbound
This paper cites Focal loss for dense object detection.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Focal loss for dense object detection
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.040478Z
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 ee7633a4-0995-48b3-9c1b-a658f3e4ef0f · outbound
This paper cites Retina u-net: Embarrassingly simple exploitation of segmentation supervision for medical object detection.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Retina u-net: Embarrassingly simple exploitation of segmentation supervision for medical object detection
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.020655Z
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 48c1eb9a-7ced-40b7-813b-a519dfc7f4b3 · outbound
This paper cites Towards a holistic framework for multimodal llm in 3d brain ct radiology report generation.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Towards a holistic framework for multimodal llm in 3d brain ct radiology report generation
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.022818Z
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 083d9297-c569-4a4c-847c-2f9c6c62fc2a · outbound
This paper cites Automatic medical report generation based on deep learning: A state of the art survey.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Automatic medical report generation based on deep learning: A state of the art survey
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.025242Z
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 75c7b145-702c-4cff-95c6-ff1423177ffc · outbound
This paper cites Ai in proton therapy treatment planning: A review.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Ai in proton therapy treatment planning: A review
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T18:23:37.681869Z
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 90d604bd-5aa6-49fb-ac44-45578603bfe8 · outbound
This paper cites Computer-extracted global radiomic features can predict the radiolo- gists’ first impression about the abnormality of a screening mammo- gram.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Computer-extracted global radiomic features can predict the radiolo- gists’ first impression about the abnormality of a screening mammo- gram
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.014295Z
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 52a26682-43e5-4b78-9133-c63ade713f58 · outbound
This paper cites Visual search in breast imaging.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Visual search in breast imaging
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.004082Z
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 47c62ccc-361a-485f-874e-0a15335561ba · outbound
This paper cites Re- liability of radiologists’ first impression when interpreting a screening mammogram.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Re- liability of radiologists’ first impression when interpreting a screening mammogram
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.046886Z
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 bfcee155-14b6-4bca-aa0c-b1edd47d973f · outbound
This paper cites Interpreting chest radiographs without visual search.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Interpreting chest radiographs without visual search
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.946926Z
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 af8652b1-8dc0-410e-871a-ea554757e550 · outbound
This paper cites Holistic component of image perception in mammogram interpretation: gaze- tracking study.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Holistic component of image perception in mammogram interpretation: gaze- tracking study
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.006160Z
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 bda29d03-e445-46df-9362-9ca261c3660d · outbound
This paper cites Miccai multi-atlas labeling beyond the cranial vault–workshop and challenge.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Miccai multi-atlas labeling beyond the cranial vault–workshop and challenge
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.012325Z
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 209fc70b-6edf-46be-8787-038f7a0beeac · outbound
This paper cites MosMedData: Chest CT Scans With COVID-19 Related Findings Dataset.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning MosMedData: Chest CT Scans With COVID-19 Related Findings Dataset
Reference 18
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-20T18:23:37.686143Z
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 477e8e5d-5704-467f-bd1f-dd0239c5a838 · outbound
This paper cites A comparison of pre-trained vision- and-language models for multimodal representation learning across medical images and reports.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning A comparison of pre-trained vision- and-language models for multimodal representation learning across medical images and reports
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.018704Z
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 dee38c91-f420-42e6-b9ec-a603ac3c224c · outbound
This paper cites A Survey of Medical Vision-and-Language Applications and Their Techniques.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning A Survey of Medical Vision-and-Language Applications and Their Techniques
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T18:23:37.665916Z
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 0e271516-51b5-4932-8227-fd5551a02f08 · outbound
This paper cites Bridging the pathology domain gap: Efficiently adapting clip for pathology image analysis with limited labeled data.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Bridging the pathology domain gap: Efficiently adapting clip for pathology image analysis with limited labeled data
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.042527Z
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 fb11ad3c-df6a-41c1-a086-87315f068d10 · outbound
This paper cites Medi- clip: Adapting clip for few-shot medical image anomaly detection.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Medi- clip: Adapting clip for few-shot medical image anomaly detection
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.027147Z
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 d4f61ef6-531e-465c-b163-d4d48b5c0dd8 · outbound
This paper cites Clip-driven universal model for organ segmentation and tumor detection.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Clip-driven universal model for organ segmentation and tumor detection
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.035346Z
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 6db47c24-0692-4ab0-b836-02c1e53b55c3 · outbound
This paper cites Medclip-sam: Bridging text and image towards universal medical image segmentation.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Medclip-sam: Bridging text and image towards universal medical image segmentation
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.990251Z
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 5d6ad924-c316-468c-bdc1-dce6d9c317a8 · outbound
This paper cites Cp-clip: Core-periphery feature alignment clip for zero-shot medical image analysis.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Cp-clip: Core-periphery feature alignment clip for zero-shot medical image analysis
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.033274Z
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 26367381-2345-4e01-9f8e-846020158aa9 · outbound
This paper cites Causalclipseg: Unlocking clip’s potential in referring medical image segmentation with causal intervention.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Causalclipseg: Unlocking clip’s potential in referring medical image segmentation with causal intervention
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.038658Z
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 da6c14eb-7aeb-4c47-8ac5-4ab18423b4e1 · outbound
This paper cites Learning transferable visual models from natural language supervision.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Learning transferable visual models from natural language supervision
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.016194Z
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 ffdd7125-7339-4f2a-a604-08c6d61f6018 · outbound
This paper cites Align before fuse: Vision and language representation learning with momentum distillation.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Align before fuse: Vision and language representation learning with momentum distillation
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.002301Z
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 74835a6c-0dbb-4b7a-8f1e-5df12c7f75af · outbound
This paper cites Mm- llms: Recent advances in multimodal large language models.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Mm- llms: Recent advances in multimodal large language models
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.029371Z
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 093a6bb6-2bc5-4321-8d54-a68a5e6a10fb · outbound
This paper cites Gsva: Generalized segmentation via multimodal large language models.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Gsva: Generalized segmentation via multimodal large language models
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.008102Z
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 e7fe8012-2a0e-49c1-a754-0a91c54f80b6 · outbound
This paper cites SAM 2: Segment Anything in Images and Videos.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning SAM 2: Segment Anything in Images and Videos
Reference 31
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T18:23:37.671578Z
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 8caa7d05-7ba3-453c-8269-5193e1074f32 · outbound
This paper cites Segment anything.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Segment anything
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.935536Z
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 8eb46f7e-5f49-4aef-9311-4c5ae542773f · outbound
This paper cites VisionLLM v2: An End-to-End Generalist Multimodal Large Language Model for Hundreds of Vision-Language Tasks.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning VisionLLM v2: An End-to-End Generalist Multimodal Large Language Model for Hundreds of Vision-Language Tasks
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T18:23:37.692557Z
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 261357bf-bda1-418d-a56f-e2b9ecbac014 · outbound
This paper cites Regularized Stokeslet Surfaces.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Regularized Stokeslet Surfaces
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T18:23:37.675445Z
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 731488ef-65ad-4fbd-bcd0-e7c287d69dda · outbound
This paper cites Magic-Me: Identity-Specific Video Customized Diffusion.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Magic-Me: Identity-Specific Video Customized Diffusion
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T18:23:37.695727Z
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 3a91140d-dcf7-44fd-9f5c-29f0a24cb0e5 · outbound
This paper cites Mimo: A medical vision language model with visual referring multimodal input and pixel grounding multimodal out- put.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Mimo: A medical vision language model with visual referring multimodal input and pixel grounding multimodal out- put
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.986449Z
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 9d3c9cbb-ecde-4fb4-a6df-a3eaeb18f26f · outbound
This paper cites M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning M3D: Advancing 3D Medical Image Analysis with Multi-Modal Large Language Models
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T18:23:37.668034Z
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 fe690395-08d1-4053-8aeb-e9c1045f7b77 · outbound
This paper cites Ct2rep: Automated radiology report generation for 3d medical imaging.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Ct2rep: Automated radiology report generation for 3d medical imaging
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.991279Z
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 b8426ea3-5aa1-459c-a96b-1fea29030d61 · outbound
This paper cites Artificial intelligence in radiology.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Artificial intelligence in radiology
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.998192Z
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 70e588c7-6138-4efe-a4f9-cebdd4e19afb · outbound
This paper cites Explainable ai in medical imaging: An overview for clinical practitioners–beyond saliency-based xai ap- proaches.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Explainable ai in medical imaging: An overview for clinical practitioners–beyond saliency-based xai ap- proaches
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.010426Z
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 fe703f78-ca86-4d17-8136-8f51ca587026 · outbound
This paper cites Vip-llava: Making large multimodal models understand 10 IEEE TRANSACTIONS ON MEDICAL IMAGING.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Vip-llava: Making large multimodal models understand 10 IEEE TRANSACTIONS ON MEDICAL IMAGING
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.993351Z
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 6d2089e9-74ca-4f76-801f-e0c3b3565e8e · outbound
This paper cites VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model
Reference 42
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T18:23:37.672397Z
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 489a09f3-9bb5-482a-b6b4-de8ce2865161 · outbound
This paper cites nnu-net: a self-configuring method for deep learning-based biomedical image segmentation.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning nnu-net: a self-configuring method for deep learning-based biomedical image segmentation
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.996357Z
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 1e9a05b5-c80a-4215-a502-258fd2b7694b · outbound
This paper cites TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation
Reference 44
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T18:23:37.674713Z
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 8aecdb90-a06c-46e6-9cef-8de1d3c1ee80 · outbound
This paper cites Encoder- decoder with atrous separable convolution for semantic image segmen- tation.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Encoder- decoder with atrous separable convolution for semantic image segmen- tation
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.044497Z
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 ff999e08-2972-4866-a862-824fa952bac1 · outbound
This paper cites Lvit: language meets vision transformer in medical image segmentation.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Lvit: language meets vision transformer in medical image segmentation
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.989300Z
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 e6b47e71-7297-4403-825d-97152b4ab2e5 · outbound
This paper cites nnde- tection: a self-configuring method for medical object detection.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning nnde- tection: a self-configuring method for medical object detection
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.962830Z
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 56085f53-49af-4bac-a224-d192977d7915 · outbound
This paper cites End-to-end object detection with transformers.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning End-to-end object detection with transformers
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.981293Z
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 2b740a75-161b-49c1-8247-5d406be98206 · outbound
This paper cites Cotr: Efficiently bridging cnn and transformer for 3d medical image segmentation.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Cotr: Efficiently bridging cnn and transformer for 3d medical image segmentation
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.966299Z
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 b2528234-ff8e-4086-a59c-3de3825d6724 · outbound
This paper cites nnFormer: Interleaved Transformer for Volumetric Segmentation.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning nnFormer: Interleaved Transformer for Volumetric Segmentation
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T18:23:37.682200Z
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 94ce57df-aca4-47ae-9755-7ae6cc89f539 · outbound
This paper cites Unetr: Transformers for 3d medical image segmentation.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Unetr: Transformers for 3d medical image segmentation
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.973465Z
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 9e75fc8e-3af8-4783-8467-38979a407462 · outbound
This paper cites Swinunetr-v2: Stronger swin transformers with stagewise convolu- tions for 3d medical image segmentation.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Swinunetr-v2: Stronger swin transformers with stagewise convolu- tions for 3d medical image segmentation
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.952895Z
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 19b2e8f8-a434-4d9d-b22c-859924d6a398 · outbound
This paper cites Contrastive learning of medical visual representations from paired images and text.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Contrastive learning of medical visual representations from paired images and text
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.955326Z
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 886b5920-c65b-4158-b2a7-cd43283d2052 · outbound
This paper cites Tganet: Text-guided attention for improved polyp segmentation.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Tganet: Text-guided attention for improved polyp segmentation
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.957496Z
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 59241e38-7ca2-4047-8590-b8d6e98884de · outbound
This paper cites Gloria: A multimodal global-local representation learning framework for label- efficient medical image recognition.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Gloria: A multimodal global-local representation learning framework for label- efficient medical image recognition
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.958771Z
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 0676fb6d-1151-4319-8d00-62abd167e798 · outbound
This paper cites Vilt: Vision-and-language transformer without convolution or region supervision.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Vilt: Vision-and-language transformer without convolution or region supervision
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.942950Z
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 184cf932-976d-41b4-b50b-7c6c160896cc · outbound
This paper cites Lavt: Language-aware vision transformer for referring image segmentation.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Lavt: Language-aware vision transformer for referring image segmentation
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:37.979164Z
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 dae18cae-298c-4a18-882b-1454e6caa6f1 · outbound
This paper cites Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Janus-Pro: Unified Multimodal Understanding and Generation with Data and Model Scaling
Reference 58
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T18:23:37.689209Z
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 0d41a98e-c220-476d-a7c4-9a44b9a8358d · outbound
This paper cites Qwen2.5-VL Technical Report.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Qwen2.5-VL Technical Report
Reference 59
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T18:23:37.662513Z
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 7c3a7024-6501-48dd-b01b-bdba9bb799ef · outbound
This paper cites Visionreasoner: Unifying vision-language reasoning and perception tasks with large multimodal models.
Segmentation, Detection and Explanation: A Unified Framework for CT Appearance Reasoning Visionreasoner: Unifying vision-language reasoning and perception tasks with large multimodal models
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-20T18:23:38.031484Z
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
No inbound Pith citation observations are available.