CORTEXA
← Browse

Xu Chen

5 papers indexed

arxivcs.DBcs.AIcs.CLcs.LG2026-07-24

DBA-Bench: A Production-Fidelity Benchmark for LLM-Based Database Operations Agents

Junming Chen, Junyang Jiang, Xu Chen, Zibo Liang, Kai Zheng

LLM-based database agents show promise, but differing task scopes, testbeds, and metrics hinder comparison. We identify four gaps between evaluation and production operations: live-environment fidelity (multi-turn read-write interaction with a running database); observation-space…

View free PDFSource page
arxivcs.AI2026-07-20

Pailitao-MMSearch: Building Native E-Commerce Multimodal Search Foundation

Xiaohan Ye, Xu Chen, Zihan Gong, Jian Ding, Lianyu Du, Baicheng Chen, et al.

The evolution of e-commerce has fundamentally transformed how users search for products, shifting from simple text-based keyword queries to complex multimodal interactions that seamlessly combine product images, natural language descriptions, and mixed-intent instructions. Howeve…

View free PDFSource page
arxivcs.RO2026-07-07

Clustering-Embedded Model Predictive Path Integral Control: Avoiding Averaging-Induced Failure and Enabling Efficient Cluster Selection for Dynamic Obstacles

Zidong Liu, Kaixin Chang, Xu Chen

With the widespread availability of parallel computing hardware, sampling-based motion planning methods such as Model Predictive Path Integral (MPPI) control have become increasingly powerful for complex nonlinear systems in non-smooth task spaces. However, the sampling and forwa…

View free PDFSource page
arxiveess.SY2026-07-06

Model-Guided Local Bayesian Optimization for Tuning of Interpretable Controllers in Injection Molding

Jens Ahlers, Robert Göllinger, Xu Chen, Heike Vallery, Sebastian Stemmler

Advanced control methods have proven effective for controlling cavity pressure, a key determinant of part-quality attributes, in the plastics injection molding process. However, the abstract nature of the resulting control laws makes them difficult to interpret in a production en…

View free PDFSource page
arxivcs.CLcs.AI2026-07-02

Gemma 4 Technical Report

Gemma Team, Sherif El Abd, Vaibhav Aggarwal, Robin Algayres, Alek Andreev, Olivier Bachem, et al.

We introduce Gemma 4, a new generation of open-weight, natively multimodal language models in the Gemma model family. Designed to advance compute efficiency and reasoning, the Gemma 4 model suite features dense and Mixture-of-Experts architectures, ranging from 2.3B to 31B parame…

View free PDFSource page