activity
20232026
most citedOptimizing Storage Overhead of User Behavior Log for ML-embedded Mobile Apps

1 citations · 2 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CL2026

Local-First Intelligence via Proactive SLM Collaborating with Feedback-Providing LLM

Hang Zeng, Xiangyu Liu, Yong Hu +5

Personal intelligence requires strong capabilities under strict privacy and efficiency constraints. Unlike cloud-first intelligence, which relies on powerful but costly and privacy…

cs.LG2025★ 1 cited

Optimizing Storage Overhead of User Behavior Log for ML-embedded Mobile Apps

Chen Gong, Yan Zhuang, Zhenzhe Zheng +4

Machine learning (ML) models are increasingly integrated into modern mobile apps to enable personalized and intelligent services. These models typically rely on rich input features…

cs.IR2025

TSRec: Enhancing Repeat-Aware Recommendation from a Temporal-Sequential Perspective

Shigang Quan, Shui Liu, Zhenzhe Zheng +1

Repeat consumption, such as repurchasing items and relistening songs, is a common scenario in daily life. To model repeat consumption, the repeat-aware recommendation has been prop…

cs.IR2025

MERIT: A Merchant Incentive Ranking Model for Hotel Search & Ranking

Shigang Quan, Hailong Tan, Shui Liu +5

Online Travel Platforms (OTPs) have been working on improving their hotel Search & Ranking (S&R) systems that facilitate efficient matching between consumers and hotels. Existing O…

cs.CL2025

Pre: Enabling Deterministic Pushdown Automata for Faster Structured LLM Generation

Junyi Chen, Shihao Bai, Zaijun Wang +7

Extensive LLM applications demand efficient structured generations, particularly for LR(1) grammars, to produce outputs in specified formats (e.g., JSON). Existing methods primaril…

cs.DB2025

FeatInsight: An Online ML Feature Management System on 4Paradigm Sage-Studio Platform

Xin Tong, Xuanhe Zhou, Bingsheng He +6

Feature management is essential for many online machine learning applications and can often become the performance bottleneck (e.g., taking up to 70% of the overall latency in sale…

cs.GT2024

MEBS: Multi-task End-to-end Bid Shading for Multi-slot Display Advertising

Zhen Gong, Lvyin Niu, Yang Zhao +9

Online bidding and auction are crucial aspects of the online advertising industry. Conventionally, there is only one slot for ad display and most current studies focus on it. Nowad…

cs.LG2024

Trajectory-wise Iterative Reinforcement Learning Framework for Auto-bidding

Haoming Li, Yusen Huo, Shuai Dou +5

In online advertising, advertisers participate in ad auctions to acquire ad opportunities, often by utilizing auto-bidding tools provided by demand-side platforms (DSPs). The curre…

cs.GT2023★ 1 cited

Auction Design for Bidders with Ex Post ROI Constraints

Hongtao Lv, Xiaohui Bei, Zhenzhe Zheng +1

Motivated by practical constraints in online advertising, we investigate single-parameter auction design for bidders with constraints on their Return On Investment (ROI) -- a targe…