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20232026
most citedLinRec: Linear Attention Mechanism for Long-term Sequential Recommender Systems

86 citations · 252 across the 39 of their papers we have counts for

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8 papers · 1 filter

cs.LG2026

GCPO: Diagnosing and Constraining Subspace Geometry in Rollout RL for LLMs

Kai Yang, Jingwei Xu, Wanyu Wang +4

On-policy rollout methods such as GRPO are central to post-training of large language models, yet they frequently suffer from training instabilities, cross-task capability degradat…

cs.LG2026

T-GINEE: A Tensor-Based Multilayer Graph Representation Learning

Maolin Wang, Ziting Mai, Xuhui Chen +9

Traditional network analysis focuses on single-layer networks, real-world systems often form multilayer networks with multiple relationship types. However, existing methods typical…

cs.LG2026

SubFlow: Sub-mode Conditioned Flow Matching for Diverse One-Step Generation

Yexiong Lin, Jia Shi, Shanshan Ye +3

Flow matching has emerged as a powerful generative framework, with recent few-step methods achieving remarkable inference acceleration. However, we identify a critical yet overlook…

cs.LG2026

BRIDGE: Bridging Reasoning In Distillation Gap Elimination via Structure-Aware Masking

Bowen Yu, Sheng Zhang, Binhao Wang +8

Chain-of-Thought (CoT) reasoning has significantly improved LLMs' mathematical problem-solving capabilities, but distilling such capabilities into smaller models remains challengin…

cs.LG2025

PAINET: A Principled Efficient Transformer for 3D Dynamics Modeling

Kai Yang, Yuqi Huang, Junheng Tao +2

Modeling 3D dynamics is a fundamental problem in multi-body systems across scientific and engineering domains and has important practical implications in object trajectory predicti…

cs.LG2025

DANCE: Resource-Efficient Neural Architecture Search with Data-Aware and Continuous Adaptation

Maolin Wang, Tianshuo Wei, Sheng Zhang +6

Neural Architecture Search (NAS) has emerged as a powerful approach for automating neural network design. However, existing NAS methods face critical limitations in real-world depl…