collaborators

10 papers

cs.CV2026

HumanCLAW: Can Vision-Language Models Act Through a Body?

Siyao Li, Li Siyao, Jiawei Gu +16

The paper introduces HumanCLAW, a framework that separates decision making of vision‑language models from low‑level motor execution, allowing evaluation of a model's action intelli…

cs.CL2026

Beyond Local Edits: Embedding-Virtualized Knowledge for Broader Evaluation and Preservation of Model Editing

Shuainan Liu, Xuanang Chen, Ben He +1

Knowledge editing methods for large language models are commonly evaluated using predefined benchmarks that assess edited facts together with a limited set of related or neighborin…

cs.CV2026

FileGram: Grounding Agent Personalization in File-System Behavioral Traces

Shuai Liu, Shulin Tian, Kairui Hu +6

Coworking AI agents operating within local file systems are rapidly emerging as a paradigm in human-AI interaction; however, effective personalization remains limited by severe dat…

cs.AI2026

HippoCamp: Benchmarking Contextual Agents on Personal Computers

Zhe Yang, Shulin Tian, Kairui Hu +9

We present HippoCamp, a new benchmark designed to evaluate agents' capabilities on multimodal file management. Unlike existing agent benchmarks that focus on tasks like web interac…

cs.CV2026

Residual Decoding: Mitigating Hallucinations in Large Vision-Language Models via History-Aware Residual Guidance

Xinrong Chen, Xu Chu, Yingmin Qiu +8

Large Vision-Language Models (LVLMs) can reason from image-text inputs and perform well in various multimodal tasks. Despite this success, they are affected by language priors and…

cs.CV2026

Demo-ICL: In-Context Learning for Procedural Video Knowledge Acquisition

Yuhao Dong, Shulin Tian, Shuai Liu +6

Despite the growing video understanding capabilities of recent Multimodal Large Language Models (MLLMs), existing video benchmarks primarily assess understanding based on models' s…