Paper-Conference

Towards a Mechanistic Understanding of Large Reasoning Models: A Survey of Training, Inference, and Failures

Y. Hu, J. Gu, R. Wang, Z. Yao, H. Peng, X. Wu, J. Chen, M. Zhang, L. Pan

VecMol: Vector-Field Representations for 3D Molecule Generation

Y. Hua, X. Peng, J. Ma, M. Zhang

TPLA: Tensor Parallel Latent Attention for Efficient Disaggregated Prefill & Decode Inference

X. Tang, F. Meng, P. Tang, Y. Wang, D. Yin, X. Sun, M. Zhang

Efficient Neural Common Neighbor for Temporal Graph Link Prediction

X. Zhang, Y. Wang, X. Wang, M. Zhang

FLORA: GNNs as Predictors of Agentic Workflow Performances

Y. Zhang, Y. Hou, B. Tang, M. Zhang, X. Dong, S. Chen

Beyond Single-Task: Robust Multi-Task Length Generalization for LLMs

Length generalization, the ability to solve problems longer than those seen during training, remains a critical challenge for large …

Y. Hu, S. Kang, H. Yang, H. Xu, M. Zhang

LooGLE v2: Are LLMs Ready for Real World Long Dependency Challenges?

Z. He, Y. Wang, J. Li, K. Liang, M. Zhang

LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgrades

As Large Language Models (LLMs) are frequently updated, LoRA weights trained on earlier versions quickly become obsolete. The …

Y. Li, F. Meng, M. Zhang, S. Zhu, S. Wang, M. Xu

OCN: Effectively Utilizing Higher-Order Common Neighbors for Better Link Prediction

Common Neighbors (CNs) and their higher-order variants are important pairwise features widely used in state-of-the-art link prediction …

J. Wang, X. Wang, M. Zhang

PHYBench: Holistic Evaluation of Physical Perception and Reasoning in Large Language Models

Current benchmarks for evaluating the reasoning capabilities of Large Language Models (LLMs) face significant limitations: task …

S. Qiu, S. Guo, Z. Song, .Et El, M. Zhang, H. X. Zhu