collaborators

7 papers

cs.AI2026

MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents

Kaichao Liang, Yuqi Cui, Hao Kong +13

Memory is a core component of AI agents, enabling them to accumulate experience, maintain personalization, and adapt over long-term interactions. However, existing memory systems o…

cs.AI2026

Retain or Consolidate? Budget-Dependent Operator Selection for Language Agent Memory

Qingcan Kang, Mingyang Liu, Shixiong Kai +5

Language agents depend on memory across interactions. However, the limited context windows of large language models (LLMs) and their inference costs constrain how much memory can b…

cs.AI2026

Learning What to Remember: Observability-Safe Memory Retention via Constrained Optimization for Long-Horizon Language Agents

Qingcan Kang, Liu Mingyang, Shixiong Kai +3

Long-horizon language agents accumulate observations, reasoning traces, and retrieved facts exceeding context windows, making memory retention a fundamental resource-allocation pro…

cs.CL2026

YouZhi: Towards High-Concurrency Financial LLMs via Adaptive GQA-to-MLA Transition

PSBC LLM Team, Huawei LLM Team, Ruihan Long +56

Large language models (LLMs) drive significant financial innovations, yet their high-concurrency deployment is severely bottlenecked by KV cache memory overhead, which inflates inf…

cs.AI2026

From Long News to Accurate Forecast: Importance-Aware Fusion and PRM-Guided Reflection for Time Series Forecasting

Mingyang Liu, Qingcan Kang, Yuke Wang +6

Incorporating news into time series forecasting is appealing because news can reveal abrupt exogenous events that historical values alone cannot recover. However, existing LLM-base…

cs.AR2026

SegSEM: Enabling and Enhancing SAM2 for SEM Contour Extraction

Da Chen, Guangyu Hu, Kaihong Xu +5

Extracting high-fidelity 2D contours from Scanning Electron Microscope (SEM) images is critical for calibrating Optical Proximity Correction (OPC) models. While foundation models l…