collaborators

11 papers

cs.CR2026

ASTELD: A Six-Axis Classification Framework for Autonomous AI Agents - Design, Evaluation, and an OpenClaw Case Study

Siyuan Li, Peng Shu, Churan Yu +19

Autonomous AI agent platforms differ substantially in architecture, security, tool integration, execution, autonomy, and deployment, yet the field lacks a common classification sch…

quant-ph2026

Absent, Not Faint: Fisher-Information Limits and a Logarithmic Measurement-Design Cure for Passive Characterization of Coherent Qubit Noise

Yi Pan, Meng Hsiu Tsai, Weihang You +6

Calibrating a quantum processor means estimating error parameters, and estimation theory usually assumes a parameter hard to estimate is faint: its signal is weak but present, so m…

cs.LG2026

World Models: A Comprehensive Survey of Architectures, Methodologies, Reasoning Paradigms, and Applications

Arif Hassan Zidan, Yi Pan, Hanqi Jiang +23

World models, internal simulators that learn the structure and dynamics of an environment, have emerged as a central paradigm in the pursuit of artificial general intelligence, ena…

cs.CL2026

SYNAPSE: Empowering LLM Agents with Episodic-Semantic Memory via Spreading Activation

Hanqi Jiang, Junhao Chen, Yi Pan +8

While Large Language Models (LLMs) excel at generalized reasoning, standard retrieval-augmented approaches fail to address the disconnected nature of long-term agentic memory. To b…

cs.AI2026

Empirical Analysis of Decoding Biases in Masked Diffusion Models

Pengcheng Huang, Tianming Liu, Zhenghao Liu +5

Masked diffusion models (MDMs), which leverage bidirectional attention and a denoising process, are narrowing the performance gap with autoregressive models (ARMs). However, their…

cs.CV2026

Achieving Fine-grained Cross-modal Understanding through Brain-inspired Hierarchical Representation Learning

Weihang You, Hanqi Jiang, Yi Pan +3

Understanding neural responses to visual stimuli remains challenging due to the inherent complexity of brain representations and the modality gap between neural data and visual inp…