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20232026
most citedDIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee

2 citations · 2 across the 5 of their papers we have counts for

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cs.LG2026

Implicit Turn-Wise Policy Optimization for Proactive User-LLM Interaction

Haoyu Wang, Yuxin Chen, Liang Luo +3

Multi-turn human-AI collaboration is fundamental to deploying interactive services such as adaptive tutoring, conversational recommendation, and professional consultation. However,…

cs.LG2025

Struc-EMB: The Potential of Structure-Aware Encoding in Language Embeddings

Shikun Liu, Haoyu Wang, Mufei Li +1

Text embeddings from Large Language Models (LLMs) have become foundational for numerous applications. However, these models typically operate on raw text, overlooking the rich stru…

cs.LG2025

Model Generalization on Text Attribute Graphs: Principles with Large Language Models

Haoyu Wang, Shikun Liu, Rongzhe Wei +1

Large language models (LLMs) have recently been introduced to graph learning, aiming to extend their zero-shot generalization success to tasks where labeled graph data is scarce. A…

cs.LG2024

Certified Machine Unlearning via Noisy Stochastic Gradient Descent

Eli Chien, Haoyu Wang, Ziang Chen +1

``The right to be forgotten'' ensured by laws for user data privacy becomes increasingly important. Machine unlearning aims to efficiently remove the effect of certain data points…

cs.LG2024

Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning

Eli Chien, Haoyu Wang, Ziang Chen +1

Machine unlearning has raised significant interest with the adoption of laws ensuring the ``right to be forgotten''. Researchers have provided a probabilistic notion of approximate…

cs.LG20232 cited

DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee

Haoyu Wang, Jialin Liu, Xiaohan Chen +3

Mixed-integer linear programming (MILP) stands as a notable NP-hard problem pivotal to numerous crucial industrial applications. The development of effective algorithms, the tuning…