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cs.AI2026

A2Z GameSpec-Bench: How Faithfully Can Coding Agents Generate Games from Game Design Specifications?

Seonho Lee, Wonryeol Jeong, Alberto Cereser +4

Delegating complete application development to coding agents requires preserving the intended design rather than simply producing plausible outputs through naive prompting. Game de…

eess.AS2026

Raon-OpenTTS: Open Models and Data for Robust Text-to-Speech

Semin Kim, Seungjun Chung, Taehong Moon +8

Recent advances in text-to-speech (TTS) models show impressive speech naturalness and quality, yet the role of large-scale open data in driving this progress remains underexplored.…

cs.MM2026

MMTB: Evaluating Terminal Agents on Multimedia-File Tasks

Chiyeong Heo, Jaechang Kim, Junhyuk Kwon +4

Terminals provide a powerful interface for AI agents by exposing diverse tools for automating complex workflows, yet existing terminal-agent benchmarks largely focus on tasks groun…

cs.CV2026

See and Fix the Flaws: Enabling VLMs and Diffusion Models to Comprehend Visual Artifacts via Agentic Data Synthesis

Jaehyun Park, Minyoung Ahn, Minkyu Kim +3

Despite recent advances in diffusion models, AI generated images still often contain visual artifacts that compromise realism. Although more thorough pre-training and bigger models…

cs.CV2026

VLM-SubtleBench: How Far Are VLMs from Human-Level Subtle Comparative Reasoning?

Minkyu Kim, Sangheon Lee, Dongmin Park

The ability to distinguish subtle differences between visually similar images is essential for diverse domains such as industrial anomaly detection, medical imaging, and aerial sur…