5 citations · 11 across the 7 of their papers we have counts for
11 papers
SWE-Clar: Can Coding Agents Clarify Incomplete Client Requirements and Deliver Greenfield Software?
Jialei Li, Dingxian Wang, Xiaoyan Zhao +11
Greenfield software development in freelance settings requires coding agents to turn incomplete client requests into working software. This makes requirement clarification essentia…
Structural properties of admissible subgraphs and the depth of symbolic powers of cover ideals
Nguyen Thu Hang, Nguyen Thi Thanh Tam, Thanh Vu
Let be a simple graph with cover ideal in a polynomial ring $S = \k[x_1, \ldots, x_n]$. For each integer , let denote the maximum size of an ordered ma…
Humanity's Sixth Sense: Benchmarking Intuitive Visual Reasoning in Multimodal Models
Xingang Guo, Jing Gu, Brian Jang +26
Humans perceive far more in a scene than what is explicitly depicted: a single glance captures past causes and future trajectories; a quick peek determines if a vehicle can fit bet…
Root-Cause Attribution Is a Search Problem: Continual Search for Long-Horizon Agent Failures
Harsh Raj, David Lee, Anas Mahmoud +7
The increasing deployment of AI agents in long-horizon tasks yields massive execution logs. Diagnosing failures within these records is crucial for reliability, as it transforms ou…
Model or Harness? An Interaction-Centric Taxonomy for Localizing Agent Failures
Harsh Raj, Vipul Gupta, Anas Mahmoud +4
Existing evaluations often reduce agent failures to system-level outcomes, obscuring where the fault originated and which intervention would improve the agent system. This creates…
UpBench: A Dynamically Evolving Real-World Labor-Market Agentic Benchmark Framework Built for Human-Centric AI
Darvin Yi, Teng Liu, Mattie Terzolo +4
As large language model (LLM) agents increasingly undertake digital work, reliable frameworks are needed to evaluate their real-world competence, adaptability, and capacity for hum…
Glorbit: A Modular, Web-Based Platform for AI Based Periorbital Measurement in Low-Resource Settings
George R. Nahass, Jacob van der Ende, Sasha Hubschman +9
Periorbital measurements such as margin reflex distances (MRD1/2), palpebral fissure height, and scleral show are essential in diagnosing and managing conditions like ptosis and ey…
Targeted Unlearning Using Perturbed Sign Gradient Methods With Applications On Medical Images
George R. Nahass, Zhu Wang, Homa Rashidisabet +8
Machine unlearning aims to remove the influence of specific training samples from a trained model without full retraining. While prior work has largely focused on privacy-motivated…
Trends, Challenges, and Future Directions in Deep Learning for Glaucoma: A Systematic Review
Mahtab Faraji, Homa Rashidisabet, George R. Nahass +3
Here, we examine the latest advances in glaucoma detection through Deep Learning (DL) algorithms using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).…
Open-Source Periorbital Segmentation Dataset for Ophthalmic Applications
George R. Nahass, Emma Koehler, Nicholas Tomaras +10
Periorbital segmentation and distance prediction using deep learning allows for the objective quantification of disease state, treatment monitoring, and remote medicine. However, t…
State-of-the-Art Periorbital Distance Prediction and Disease Classification Using Periorbital Features
George R. Nahass, Sasha Hubschman, Jeffrey C. Peterson +9
Periorbital distances are critical markers for diagnosing and monitoring a range of oculoplastic and craniofacial conditions. Manual measurement, however, is subjective and prone t…