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Published Date

Publication

An Empirical Study of Issues in Large Language Model Training Systems

Yanjie Gao, Ruiming Lu, Haoxiang Lin, Yueguo Chen

FSE 2025 | June 2025

The ACM International Conference on the Foundations of Software Engineering, Industry Track

Project

Publication

Ownership, Not Just Happy Talk: Co-Designing a Participatory Large Language Model for Journalism

Emily Tseng, Meg Young, Marianne Aubin Le Quéré, Aimee Rinehart, Harini Suresh

FAccT | June 2025

Publication

Autotuning Systems: Techniques, Challenges, and Opportunities

Brian Kroth, Sergiy Matusevych, Yiwen Zhu

SIGMOD 2025 | June 2025

Publication

Controllable diffusion-based generation for multi-channel biological data

Haoran Zhang, Mingyuan Zhou, Wesley Tansey

ICLR 2026 | June 2025

Publication

First Workshop Connecting Academia and Industry on Modern Integrated Database and AI Systems (MIDAS)

Avrilia Floratou, Subru Krishnan, Jignesh M. Patel

2025 International Conference on Management of Data | June 2025

Publication

Routing Mamba: Scaling State Space Models with Mixture-of-Experts Projection

Zheng Zhan, Liliang Ren, Shuohang Wang, Liyuan Liu, Yang Liu, Yeyun Gong, Yanzhi Wang, Yelong Shen

NeurIPS 2025 | June 2025

Publication

Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment

Yiwen Zhu, Rathijit Sen, Brian Kroth, Sergiy Matusevych, Andreas Mueller, Tengfei Huang, Rahul Challapalli, Weihan Tang, Xin He, Mo Liu, Estera Kot, Sule Kahraman, Arshdeep Sekhon, Dario Bernal, Aditya Lakra, Shaily Fozdar, Dhruv Relwani, Rui Fang, Long Tian, Karuna Sagar Krishna, Ashit Gosalia, Carlo Curino, Subru Krishnan

Companion of the 2025 International Conference on Management of Data | June 2025

Tool

Science Foundation Model

We develop the Science Foundation Model to empower natural scientists and accelerate breakthroughs in scientific discovery. As part of this effort, we introduce the sequence-based model, Nature Language Model (NatureLM). NatureLM is designed to span…

GitHub

Publication

Detecting Functionality-Specific Vulnerabilities via Retrieving Individual Functionality-Equivalent APIs in Open-Source Repositories

Tianyu Chen, Zeyu Wang, Lin Li, Ding Li, Zongyang Li, Xiaoning Chang, Pan Bian, Guangtai Liang, Qianxiang Wang, Tao Xie

ECOOP 2025 | June 2025

Tool

EfficientXLang

This codebase is the official implementation of “EfficientXLang: Towards Improving Token Efficiency Through Cross-Lingual Reasoning.”

GitHub Publication

Artificial Intelligence

Highlights