14 citations · 14 across the 15 of their papers we have counts for
15 papers
Making Reconstruction FID Predictive of Diffusion Generation FID
Tongda Xu, Mingwei He, Shady Abu-Hussein +6
It is well known that the reconstruction FID (rFID) of a VAE is poorly correlated with the generation FID (gFID) of a latent diffusion model. We propose interpolated FID (iFID), a…
Training-Free Vector Quantization via Gaussian VAEs
Tongda Xu, Wendi Zheng, Jiajun He +4
Vector-quantized variational autoencoders (VQ-VAEs) are discrete autoencoders that compress images into discrete tokens. However, they are difficult to train due to discretization.…
MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent
Hongli Yu, Tinghong Chen, Jiangtao Feng +8
Despite improvements by length extrapolation, efficient attention and memory modules, handling infinitely long documents with linear complexity without performance degradation duri…
PICD: Versatile Perceptual Image Compression with Diffusion Rendering
Tongda Xu, Jiahao Li, Bin Li +3
Recently, perceptual image compression has achieved significant advancements, delivering high visual quality at low bitrates for natural images. However, for screen content, existi…
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Qiying Yu, Zheng Zhang, Ruofei Zhu +32
Inference scaling empowers LLMs with unprecedented reasoning ability, with reinforcement learning as the core technique to elicit complex reasoning. However, key technical details…
CoopDETR: A Unified Cooperative Perception Framework for 3D Detection via Object Query
Zhe Wang, Shaocong Xu, Xucai Zhuang +5
Cooperative perception enhances the individual perception capabilities of autonomous vehicles (AVs) by providing a comprehensive view of the environment. However, balancing percept…
IROAM: Improving Roadside Monocular 3D Object Detection Learning from Autonomous Vehicle Data Domain
Zhe Wang, Xiaoliang Huo, Siqi Fan +3
In autonomous driving, The perception capabilities of the ego-vehicle can be improved with roadside sensors, which can provide a holistic view of the environment. However, existing…
Rethinking Diffusion Posterior Sampling: From Conditional Score Estimator to Maximizing a Posterior
Tongda Xu, Xiyan Cai, Xinjie Zhang +7
Recent advancements in diffusion models have been leveraged to address inverse problems without additional training, and Diffusion Posterior Sampling (DPS) (Chung et al., 2022a) is…
Universal Actions for Enhanced Embodied Foundation Models
Jinliang Zheng, Jianxiong Li, Dongxiu Liu +7
Training on diverse, internet-scale data is a key factor in the success of recent large foundation models. Yet, using the same recipe for building embodied agents has faced noticea…
Robo-MUTUAL: Robotic Multimodal Task Specification via Unimodal Learning
Jianxiong Li, Zhihao Wang, Jinliang Zheng +8
Multimodal task specification is essential for enhanced robotic performance, where \textit{Cross-modality Alignment} enables the robot to holistically understand complex task instr…
FuseGen: PLM Fusion for Data-generation based Zero-shot Learning
Tianyuan Zou, Yang Liu, Peng Li +3
Data generation-based zero-shot learning, although effective in training Small Task-specific Models (STMs) via synthetic datasets generated by Pre-trained Language Models (PLMs), i…
Policy Bifurcation in Safe Reinforcement Learning
Wenjun Zou, Yao Lyu, Jie Li +7
Safe reinforcement learning (RL) offers advanced solutions to constrained optimal control problems. Existing studies in safe RL implicitly assume continuity in policy functions, wh…
Consistency Model is an Effective Posterior Sample Approximation for Diffusion Inverse Solvers
Tongda Xu, Ziran Zhu, Jian Li +8
Diffusion Inverse Solvers (DIS) are designed to sample from the conditional distribution , with a predefined diffusion model , an operator , and a m…
EMIFF: Enhanced Multi-scale Image Feature Fusion for Vehicle-Infrastructure Cooperative 3D Object Detection
Zhe Wang, Siqi Fan, Xiaoliang Huo +5
In autonomous driving, cooperative perception makes use of multi-view cameras from both vehicles and infrastructure, providing a global vantage point with rich semantic context of…
DecisionNCE: Embodied Multimodal Representations via Implicit Preference Learning
Jianxiong Li, Jinliang Zheng, Yinan Zheng +9
Multimodal pretraining is an effective strategy for the trinity of goals of representation learning in autonomous robots: 1) extracting both local and global task progressions; 2)…