activity
20242026
most citedPiCO: Peer Review in LLMs based on the Consistency Optimization

2 citations · 2 across the 4 of their papers we have counts for

collaborators

6 papers

cs.AI2026

OpenAI4S: Code as Action, Science as Sessions

Gongbo Zhang, Hao Li, Yu Wang +15

AI co-scientists could accelerate computational research, but over a long-running study the workflow also has to stay inspectable, resumable and reproducible, which requires persis…

cs.DC2026

TerraceMoE: A Cost Model for Hierarchical MoE All-to-All Communication

Weicheng Xue, Bingqiang Wang, Li Yuan +2

Hierarchical two-hop dispatch can reduce slow-fabric traffic in expert-parallel Mixture-of-Experts training, but it adds a second collective and an arrival-side operator chain. We…

cs.LG2025

GNSP: Gradient Null Space Projection for Preserving Cross-Modal Alignment in VLMs Continual Learning

Tiantian Peng, Yuyang Liu, Shuo Yang +2

Contrastive Language-Image Pretraining has demonstrated remarkable zero-shot generalization by aligning visual and textual modalities in a shared embedding space. However, when con…

cs.LG2024

Sparse Orthogonal Parameters Tuning for Continual Learning

Kun-Peng Ning, Hai-Jian Ke, Yu-Yang Liu +3

Continual learning methods based on pre-trained models (PTM) have recently gained attention which adapt to successive downstream tasks without catastrophic forgetting. These method…

cs.LG2024

Is Parameter Collision Hindering Continual Learning in LLMs?

Shuo Yang, Kun-Peng Ning, Yu-Yang Liu +4

Large Language Models (LLMs) often suffer from catastrophic forgetting when learning multiple tasks sequentially, making continual learning (CL) essential for their dynamic deploym…

cs.CL2024★ 2 cited

PiCO: Peer Review in LLMs based on the Consistency Optimization

Kun-Peng Ning, Shuo Yang, Yu-Yang Liu +5

Existing large language models (LLMs) evaluation methods typically focus on testing the performance on some closed-environment and domain-specific benchmarks with human annotations…