4 citations · 11 across the 11 of their papers we have counts for
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cs.AI2026
SHarP: Saliency-based Pruning of Agent Harnesses
Xinyi Gao, Qiucheng Wu, Kaizhi Qian +3
Agent harnesses are systems that coordinate model calls, tool use, and task execution to help large language models complete complex tasks. To meet task requirements and address fa…
cs.AI2026
WorldAuditBench: Interactive 3D World Auditing with Multimodal Agents
Ziyan Jiang, Jingbo Yang, Jiabao Ji +5
As interactive 3D worlds are increasingly used to study intelligent behavior, it becomes important to develop efficient pipelines for identifying anomalies in these simulated envir…
cs.AI2025
Rethinking the Text-Vision Reasoning Imbalance in MLLMs through the Lens of Training Recipes
Guanyu Yao, Qiucheng Wu, Yang Zhang +3
Multimodal large language models (MLLMs) have demonstrated strong capabilities on vision-and-language tasks. However, recent findings reveal an imbalance in their reasoning capabil…