10 papers
GameXpert-Bench: How Far Are Coding Agents from Expert Game Development?
Kun Chen, Haorong Hong, Peizhong Gao +7
Recent large language models (LLMs) can operate as coding agents that build complete games from natural language requests. Game development is especially demanding because program…
GameCraft-Bench: Can Agents Build Playable Games End-to-End in a Real Game Engine?
Tongxu Luo, Rongsheng Wang, Jiaxi Bi +22
Game generation is an emerging application of coding agents, requiring models to transform natural-language specifications into playable interactive systems. Unlike traditional cod…
Cut Your Losses! Learning to Prune Paths Early for Efficient Parallel Reasoning
Jiaxi Bi, Tongxu Luo, Wenyu Du +2
Parallel reasoning enhances Large Reasoning Models (LRMs) but incurs prohibitive costs due to futile paths caused by early errors. To mitigate this, path pruning at the prefix leve…
Do Phone-Use Agents Respect Your Privacy?
Zhengyang Tang, Ke Ji, Xidong Wang +19
We study whether phone-use agents respect privacy while completing benign mobile tasks. This question has remained hard to answer because privacy-compliant behavior is not operatio…
Kimi K2.5: Visual Agentic Intelligence
Kimi Team, Tongtong Bai, Yifan Bai +339
We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint optimization of text and vision so that…
Learning from Peers in Reasoning Models
Tongxu Luo, Wenyu Du, Jiaxi Bi +5
Large Reasoning Models (LRMs) have the ability to self-correct even when they make mistakes in their reasoning paths. However, our study reveals that when the reasoning process sta…