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20212026
most citedAdvanced Deep Learning and Large Language Models: Comprehensive Insights for Cancer Detection

27 citations · 48 across the 44 of their papers we have counts for

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Showing 2026 · cs.CVShow all

11 papers · 2 filters

cs.CV2026

VISTA: A Multimodal Egocentric Benchmark for Goal-Oriented Perception and Assistance to Blind and Low-Vision Users

Noé Mosca, Mohamed Rayan Barhdadi, Muhammad Hamza +11

Blindness and low vision limit many people's ability to complete daily tasks, motivating AI assistants that provide useful guidance. Yet, existing benchmarks do not adequately test…

cs.CV2026

Separating perception from reasoning in vision-language models: a model-free render ceiling for crystal structures

Can Polat, Mustafa Kurban, Erchin Serpedin +1

Multimodal evaluations cannot say whether a vision-language model misread an image or misreasoned about it, because every existing method for separating the two places a second mod…

cs.CV2026

Accuracy and Cost Claims Do Not Survive Re-Execution in Agentic VideoQA

Rama AlHamidi, Aseel Mohamed, Rasul Khanbayov +3

Agentic Video Question Answering (VideoQA) systems produce answers through adaptive reasoning and tool-use trajectories, yet standard practice evaluates each system once and estima…

cs.CV2026

Prompt-Conditioned Channel Attention for Hierarchical Feature Modulation toward Anatomy-Agnostic Segmentation

Mosharof Hossain, Md Rabiul Islam, Limon Halder +2

Anatomically plausible segmentation remains challenging because of low contrast, ambiguous boundaries, and modality-specific artifacts. Interactive segmentation has emerged as a pr…

cs.CV2026

Counterfactual Sensitivity Is Not Repairability: Auditing Replay Probes for Video Evidence

Rama AlHamidi, Rasul Khanbayov, Erchin Serpedin +1

Tool-using video agents retrieve visual evidence before answering, but the final answer is not forced to depend on what was retrieved. The natural black box test is counterfactual:…

cs.CV2026

ConfTriage: A Calibration-Aware LLM Triage Framework for Pulmonary Nodule Malignancy with Selective Specialist Deferral

Md Rabiul Islam, Samir Abdaljalil, Erchin Serpedin +1

Pulmonary nodule malignancy prediction typically depends on image-trained specialist deep learning (DL) models that require substantial annotated imaging data and task-specific tra…

cs.CV2026

Conformal Coverage Guarantees for Any Video Temporal Grounder

Aseel Mohamed, Rasul Khanbayov, Erchin Serpedin +1

Event boundaries in continuous video are ambiguous: re-annotate the same query-video pair and independent annotators mark moments that overlap by less than half on a large fraction…

cs.CV2026

GRAPE: Graph-Augmented Prototype Explanations for Interactive Medical Image Diagnosis

Rasul Khanbayov, Erchin Serpedin, Hasan Kurban

Prototype-based medical image classifiers present three clinical limitations: they treat findings as independent, silently amplify unsafe physician feedback, and require full retra…

cs.CV2026

Do Gaussian Scenes Contain Enough Structure for Intrinsic Segmentation?

Hasan Yazar, Mohamed Rayan Barhdadi, Erchin Serpedin +2

Gaussian segmentation is usually posed as transferring object knowledge from 2D foundation models into a 3D representation. This leaves a fundamental question unanswered: how much…

cs.CV2026

4D Synchronized Fields: Motion-Language Gaussian Splatting for Temporal Scene Understanding

Mohamed Rayan Barhdadi, Samir Abdaljalil, Rasul Khanbayov +2

Current 4D representations decouple geometry, motion, and semantics: reconstruction methods discard interpretable motion structure; language-grounded methods attach semantics after…

cs.CV2026

IRIS: A Real-World Benchmark for Inverse Recovery and Identification of Physical Dynamic Systems from Monocular Video

Rasul Khanbayov, Mohamed Rayan Barhdadi, Erchin Serpedin +1

Unsupervised physical parameter estimation from video lacks a common benchmark: existing methods evaluate on non-overlapping synthetic data, the sole real-world dataset is restrict…