3 citations · 7 across the 11 of their papers we have counts for
12 papers
PATH-Bench: Path-Dependent Evaluation of Lifelong Agents
Xidong Yang, Xingyi Zhang, Wenhao Li +7
Lifelong LLM agents increasingly adapt through external learning states that store past interactions as retrievable memories or reusable skills, yet existing benchmarks rarely acco…
HyEvo: Self-Evolving Hybrid Agentic Workflows for Efficient Reasoning
Beibei Xu, Yutong Ye, Chuyun Shen +3
Although agentic workflows have demonstrated strong potential for solving complex tasks, existing automated generation methods remain inefficient and underperform, as they rely on…
AscendOptimizer: Episodic Agent for Ascend NPU Operator Optimization
Jiehao Wu, Zixiao Huang, Wenhao Li +3
Optimizing AscendC (Ascend C) operators for Ascend NPUs is difficult for two reasons. First, unlike CUDA, the ecosystem offers few public kernels to learn from. Second, performance…
TextAtari: 100K Frames Game Playing with Language Agents
Wenhao Li, Wenwu Li, Chuyun Shen +8
We present TextAtari, a benchmark for evaluating language agents on very long-horizon decision-making tasks spanning up to 100,000 steps. By translating the visual state representa…
Agentic Episodic Control
Xidong Yang, Wenhao Li, Junjie Sheng +4
Reinforcement learning (RL) remains fundamentally limited by poor data efficiency and weak generalization. Prior episodic RL methods attempt to alleviate this via external memory m…
GraphThought: Graph Combinatorial Optimization with Thought Generation
Zixiao Huang, Lifeng Guo, Wenhao Li +6
Graph combinatorial optimization (GCO) problems are central to domains like logistics and bioinformatics. While traditional solvers dominate, large language models (LLMs) offer new…
FPPL: An Efficient and Non-IID Robust Federated Continual Learning Framework
Yuchen He, Chuyun Shen, Xiangfeng Wang +1
Federated continual learning (FCL) aims to learn from sequential data stream in the decentralized federated learning setting, while simultaneously mitigating the catastrophic forge…
Interactive 3D Medical Image Segmentation with SAM 2
Chuyun Shen, Wenhao Li, Yuhang Shi +1
Interactive medical image segmentation (IMIS) has shown significant potential in enhancing segmentation accuracy by integrating iterative feedback from medical professionals. Howev…
Complementary Information Mutual Learning for Multimodality Medical Image Segmentation
Chuyun Shen, Wenhao Li, Haoqing Chen +5
Radiologists must utilize multiple modal images for tumor segmentation and diagnosis due to the limitations of medical imaging and the diversity of tumor signals. This leads to the…
Can language agents be alternatives to PPO? A Preliminary Empirical Study On OpenAI Gym
Junjie Sheng, Zixiao Huang, Chuyun Shen +5
The formidable capacity for zero- or few-shot decision-making in language agents encourages us to pose a compelling question: Can language agents be alternatives to PPO agents in t…
Temporally-Extended Prompts Optimization for SAM in Interactive Medical Image Segmentation
Chuyun Shen, Wenhao Li, Ya Zhang +1
The Segmentation Anything Model (SAM) has recently emerged as a foundation model for addressing image segmentation. Owing to the intrinsic complexity of medical images and the high…
Interactive Medical Image Segmentation with Self-Adaptive Confidence Calibration
Wenhao Li, Qisen Xu, Chuyun Shen +5
Medical image segmentation is one of the fundamental problems for artificial intelligence-based clinical decision systems. Current automatic medical image segmentation methods are…