Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T00:23:34.251478Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2506.14451.
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 2026-08-07T00:23:34.251478Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+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
48 of 48 outbound references displayed
External citation measurements
No source-named external measurement is stored.
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering Ai agriculture: Boost yields with yolo11
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering Open-Ended Medical Visual Question Answering Through Prefix Tuning of Language Models
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering Large language models encode clinical knowledge
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering Medpix 2.0: A comprehensive multimodal biomedical dataset for advanced ai applications,
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering
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Reference 17
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering Scaling Instruction-Finetuned Language Models
Reference 18
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Reference 19
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering Nvidia a100 tensor core gpu, 2020
Reference 20
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering LLaMA: Open and Efficient Foundation Language Models
Reference 21
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering Hewett, Jamie Huynh, Mojan Javaheripi, Xin Jin, Piero Kauffmann, Nikos Karampatziakis, Dongwoo Kim, Mahmoud Khademi, Lev Kurilenko, James R
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering Show and tell: A neural image caption generator
Reference 23
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering Referitgame: Referring to objects in photographs of natural scenes
Reference 24
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering Conceptual captions: A cleaned, hypernymed, image alt-text dataset for automatic image captioning
Reference 25
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering Wit: Wikipedia-based image text dataset for multimodal multilingual machine learning
Reference 26
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering Sigmoid Loss for Language Image Pre-Training
Reference 27
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing
Reference 28
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering Gemma 2: Improving Open Language Models at a Practical Size
Reference 29
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering Unresolved cited work
Reference 30
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering LVLM-Interpret: An Interpretability Tool for Large Vision-Language Models
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering Searching for unintended biases with saliency
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering Explainability for vision transformers
Reference 35
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Reference 36
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering Measuring mathematical problem solving with the math dataset
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering PMC Open Access Subset
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering When scaling meets llm finetuning: The effect of data, model and finetuning method
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Adapting Lightweight Vision Language Models for Radiological Visual Question Answering "" Figure 9: Generate Literature Based Questions Prompt B Evaluation and Saliency Diagnostics def evaluate_generation(generation,ground): prompt = f
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