1 citations · 2 across the 9 of their papers we have counts for
5 papers · 1 filter
State Representation Shapes Long-Horizon Agent Learning and Transfer: An Empirical Study
Dong Nie, Rui Lan, Yixin Nie +1
An end-to-end success rate alone cannot distinguish failure to learn an action from failure to apply it as task state changes. We study this distinction in deterministic tool workf…
Knowing When to Trust Images: Reliability-Aware Multi-modal Entity Alignment
Chenxiao Li, Yunhe Feng, Dongfang Liu +3
The visual modality, i.e., images, plays a key role in multi-modal entity alignment (MMEA). Existing approaches often directly fuse the image with other modalities to align differe…
Dual-Layer Agentic Memory with Fast Write Routing and Slow Consolidation
Wenzhi Li, Dong Nie, Rui Lan +7
Large language model (LLM) agents operate in dynamic environments where knowledge continuously evolves. Existing memory systems typically treat external memory as a monotonically g…
Post-Training is About States, Not Tokens: A State Distribution View of SFT, RL, and On-Policy Distillation
Dong Nie
Large language model post-training methods such as supervised fine-tuning (SFT), reinforcement learning (RL), and distillation are often analyzed through their loss functions: maxi…
Sub-JEPA: Subspace Gaussian Regularization for Stable End-to-End World Models
Kai Zhao, Dongliang Nie, Yuchen Lin +4
Joint-Embedding Predictive Architectures (JEPAs) provide a simpleframework for learning world models by predicting future latent representations.However, JEPA training is subject t…