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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…
Physics as the label for measuring and correcting materials reasoning in multimodal models
Hasan Kurban, Rasul Khanbayov, Mustafa Kurban
Vision-language and language models increasingly interpret materials data, yet benchmarks report that they hallucinate invalid properties and violate physical law. Evaluation match…
A Low Grounding Score Is Not an Ungrounded Judge: Identifying the Perceptibility Confound in Multimodal Oversight
Rasul Khanbayov, Hasan Kurban
Model judges now supervise multimodal systems at scale, filtering training data, selecting outputs, and supplying the reward that shapes multimodal reasoning models. Trusting one m…
PhysWeep: Does a Video Generator Realize the Physics You Ask For?
Rasul Khanbayov, Hasan Kurban
Image-to-video generators are often credited with absorbing physical dynamics as implicit world models, a claim the community currently checks with plausibility scores that ask whe…
One Perturbation Is Not Enough: Identifiability and Blind Baselines for Behavioral AI Evaluation
Rasul Khanbayov, Mariam Sohail, Ahmed Abdala +1
Behavioral evaluations perturb an input and read the induced change in the output in order to certify that a system uses that input. We show that the number of perturbations such a…
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…
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…
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:…
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…
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…
It's the Decoding Format, Not the Perturbation: Auditing Consistency-Based Selection for Vision-Language Test-Time Scaling
Puzhuo Zheng, Hasan Kurban
Test-time scaling lifts large language model reasoning by sampling many candidate solutions and selecting among them, yet the same recipe transfers poorly to vision-language models…
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…
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…
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…
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…
QuantumCanvas: A Multimodal Benchmark for Visual Learning of Atomic Interactions
Can Polat, Erchin Serpedin, Mustafa Kurban +1
Despite rapid advances in molecular and materials machine learning, most models still lack physical transferability: they fit correlations across whole molecules or crystals rather…
PhysicsNeRF: Physics-Guided 3D Reconstruction from Sparse Views
Mohamed Rayan Barhdadi, Hasan Kurban, Hussein Alnuweiri
PhysicsNeRF is a physically grounded framework for 3D reconstruction from sparse views, extending Neural Radiance Fields with four complementary constraints: depth ranking, RegNeRF…