1 citations · 1 across the 3 of their papers we have counts for
7 papers
Loud Failures, Quiet Failures: Fault Detection and Recovery in Tool-Using Language Model Agents
Obada Kraishan
Tool-using agents are usually scored on whether they finish a task while the tools work. Deployments are less forgiving: services time out, endpoints disappear, parameter names cha…
The Long Road to the Same Answer: Cognitive Bias Under Escalating Reasoning Budgets in Large Language Models
Obada Kraishan
Reasoning models allocate extra computation at inference time and present their answers as the product of deliberate thought. If this deliberation works the way dual-process accoun…
Not All Agents Are Equal: Code Quality and Post-Merge Maintenance Across Five Autonomous Coding Agents in the Wild
Obada Kraishan
Autonomous coding agents now open pull requests in public repositories at a scale that was out of reach two years ago, yet little is known about what happens to that code after it…
Plans They Abandon, Reports They Author: The Narrative Layer of Autonomous Agents
Obada Kraishan, Kulsawasd Jitkajornwanich
When a coding agent finishes a task, the developer reviews a summary the agent wrote about itself, not a display someone designed. We ask how much of the agent's work that summary…
Robo-Reporters: Evaluating Autonomous AI Agents as Algorithmic Gatekeepers in Computational Journalism
Obada Kraishan, Kulsawasd Jitkajornwanich, Kerk Kee
Artificial intelligence agents increasingly perform journalism tasks autonomously, searching for sources, evaluating credibility, and producing news content with minimal human over…
The AI Invisibility Effect: Understanding Human-AI Interaction When Users Don't Recognize Artificial Intelligence
Obada Kraishan
The fast integration of artificial intelligence into mobile applications has completely changed the digital landscape; however, the impact of this change on user perception of AI f…
The AI Attribution Paradox: Transparency as Social Strategy in Open-Source Software Development
Obada Kraishan
AI coding assistants have transformed software development, raising questions about transparency and attribution practices. We examine the "AI attribution paradox": how developers…