activity
20162026
most citedMCNE: An End-to-End Framework for Learning Multiple Conditional Network Representations of Social Network

133 citations · 522 across the 131 of their papers we have counts for

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22 papers · 1 filter

cs.AI2026

Repo-To-Skill: Distilling GitHub Repositories Into AI4AI Skills

Jianlyu Chen, Yuyang Hu, Hongjin Qian +8

Autonomous agents are beginning to carry out machine-learning (ML) research end to end. These agents combine a model backbone with a harness for planning, execution, memory, and ve…

cs.AI2026

Rethinking Heterogeneous LLM Merging: A Weighted Model Averaging Perspective

Jiahe Fan, Yinghao Hou, Si Chen +3

Can large language models with substantially different parameter spaces be merged by direct weighted averaging, without training or semantic alignment? Existing heterogeneous fusio…

cs.AI2026

Learning from Emptiness: De-biasing Listwise Rerankers with Content-Agnostic Probability Calibration

Hang Lv, Hongchao Gu, Ruiqing Yang +5

Generative listwise reranking leverages global context for superior retrieval but is plagued by intrinsic position bias, where models exhibit structural sensitivity to input order…

cs.AI2026

SPARD: Self-Paced Curriculum for RL Alignment via Integrating Reward Dynamics and Data Utility

Xuyang Zhi, Peilun zhou, Chengqiang Lu +10

The evolution of Large Language Models (LLMs) is shifting the focus from single, verifiable tasks toward complex, open-ended real-world scenarios, imposing significant challenges o…

cs.AI2026

CeProAgents: A Hierarchical Agents System for Automated Chemical Process Development

Yuhang Yang, Ruikang Li, Jifei Ma +8

The development of chemical processes, a cornerstone of chemical engineering, presents formidable challenges due to its multi-faceted nature, integrating specialized knowledge, con…

cs.AI2026

Efficient and Stable Reinforcement Learning for Diffusion Language Models

Jiawei Liu, Xiting Wang, Yuanyuan Zhong +2

Reinforcement Learning (RL) is crucial for unlocking the complex reasoning capabilities of Diffusion-based Large Language Models (dLLMs). However, applying RL to dLLMs faces unique…