1 citations · 2 across the 6 of their papers we have counts for
6 papers
ECA: Efficient Continual Alignment for Open-Ended Image-to-Text Generation
Jiangtao Kong, Peijun Zhao, Chun-Fu Chen +4
Incremental Learning (IL) for Open-ended Image-to-Text Generation (OpenITG) enables models to continuously generate accurate, contextually relevant text for new images while preser…
WestWorld: A Knowledge-Encoded Scalable Trajectory World Model for Diverse Robotic Systems
Yuchen Wang, Jiangtao Kong, Sizhe Wei +6
Trajectory world models play a crucial role in robotic dynamics learning, planning, and control. While recent works have explored trajectory world models for diverse robotic system…
ODESteer: A Unified ODE-Based Steering Framework for LLM Alignment
Hongjue Zhao, Haosen Sun, Jiangtao Kong +8
Activation steering, or representation engineering, offers a lightweight approach to align large language models (LLMs) by manipulating their internal activations at inference time…
Hybrid Memory Replay: Blending Real and Distilled Data for Class Incremental Learning
Jiangtao Kong, Jiacheng Shi, Ashley Gao +3
Incremental learning (IL) aims to acquire new knowledge from current tasks while retaining knowledge learned from previous tasks. Replay-based IL methods store a set of exemplars f…
Condensed Prototype Replay for Class Incremental Learning
Jiangtao Kong, Zhenyu Zong, Tianyi Zhou +1
Incremental learning (IL) suffers from catastrophic forgetting of old tasks when learning new tasks. This can be addressed by replaying previous tasks' data stored in a memory, whi…
DSAM: A Distance Shrinking with Angular Marginalizing Loss for High Performance Vehicle Re-identificatio
Jiangtao Kong, Yu Cheng, Benjia Zhou +2
Vehicle Re-identification (ReID) is an important yet challenging problem in computer vision. Compared to other visual objects like faces and persons, vehicles simultaneously exhibi…