activity
20202026
most citedHeterogeneous Graph Neural Networks for Extractive Document Summarization

37 citations · 38 across the 15 of their papers we have counts for

collaborators

17 papers

cs.AI2026

AgentHPOBench: A Benchmark For Evaluating LLM Agents as Sequential Hyperparameter Optimizers

Tianyu Huai, Tingshuo Fan, Xinchi Chen +5

As LLMs evolve from code completion systems into autonomous scientific agents, evaluating their ability to conduct experiments has become increasingly important. Existing benchmark…

cs.CL2026

Rethinking Scientific Discovery in the Agentic Era

Yining Zheng, Yuxin Wang, Jiahao Lu +27

Artificial intelligence has advanced scientific discovery, but most AI4Science systems remain fragmented tools that rely on humans to coordinate problem formulation, literature gro…

cs.HC20261 cited

Toward Natural and Companionable Virtual Agents via Cross-Temporal Emotional Modeling

Feier Qin, Xiao Li, Yi Zheng +5

Recent advances in foundation models have enabled conversational agents that aim for sustained companionship rather than mere task completion. Yet most still remain unable to suppo…

cs.AI2026

Human-Centric Topic Modeling with Goal-Prompted Contrastive Learning and Optimal Transport

Rui Wang, Yi Zheng, Dongxin Wang +5

Existing topic modeling methods, from LDA to recent neural and LLM-based approaches, which focus mainly on statistical coherence, often produce redundant or off-target topics that…

cs.LG2026

The Past Is Not Past: Memory-Enhanced Dynamic Reward Shaping

Yang Liu, Enxi Wang, Yufei Gao +6

Despite the success of reinforcement learning for large language models, a common failure mode is reduced sampling diversity, where the policy repeatedly generates similar erroneou…

cs.SE2026

Understanding by Reconstruction: Reversing the Software Development Process for LLM Pretraining

Zhiyuan Zeng, Yichi Zhang, Yong Shan +11

While Large Language Models (LLMs) have achieved remarkable success in code generation, they often struggle with the deep, long-horizon reasoning required for complex software engi…