activity
20232026
most citedCradle: Empowering Foundation Agents Towards General Computer Control

3 citations · 5 across the 3 of their papers we have counts for

collaborators

6 papers

cs.AI2026

From Memory to Guide: Spatio-Temporal Composer for Procedural Coding Memory

Zhixuan Tan, Pengjie Gu, Zhao Li +4

Memory-augmented agents typically integrate procedural knowledge by injecting retrieved skills directly into text prompts. This approach dangerously equates readable text with reli…

cs.SE2026

EngramBench: A Capability-Grounded Benchmark for Skill-Evolution Harnesses

Zhixuan Tan, Pengjie Gu, Zhao Li +4

While large language models have achieved remarkable success in isolated code generation, authentic software engineering requires sustained reasoning, complex state management, and…

cs.IR2025

MTRec: Learning to Align with User Preferences via Mental Reward Models

Mengchen Zhao, Yifan Gao, Yaqing Hou +5

Recommendation models are predominantly trained using implicit user feedback, since explicit feedback is often costly to obtain. However, implicit feedback, such as clicks, does no…

cs.LG2024

Resisting Stochastic Risks in Diffusion Planners with the Trajectory Aggregation Tree

Lang Feng, Pengjie Gu, Bo An +1

Diffusion planners have shown promise in handling long-horizon and sparse-reward tasks due to the non-autoregressive plan generation. However, their inherent stochastic risk of gen…

cs.AI2024★ 3 cited

Cradle: Empowering Foundation Agents Towards General Computer Control

Weihao Tan, Wentao Zhang, Xinrun Xu +25

Despite the success in specific scenarios, existing foundation agents still struggle to generalize across various virtual scenarios, mainly due to the dramatically different encaps…

cs.MA2023★ 2 cited

Controlling Type Confounding in Ad Hoc Teamwork with Instance-wise Teammate Feedback Rectification

Dong Xing, Pengjie Gu, Qian Zheng +5

Ad hoc teamwork requires an agent to cooperate with unknown teammates without prior coordination. Many works propose to abstract teammate instances into high-level representation o…