17 citations · 21 across the 11 of their papers we have counts for
11 papers
RoboLineage: Agent-Native Data Lifecycle Governance Across Robot Policy Iterations
Qian Luo, Wentao Guo, Zhennan Qin +4
We present RoboLineage, an agent-native data lifecycle governance system for robot policy iteration. Modern robot policies improve through repeated data collection, review, retrain…
FLUID: From Ephemeral IDs to Multimodal Semantic Codes for Industrial-Scale Livestreaming Recommendation
Xinhang Yuan, Zexi Huang, Anjia Cao +6
Modern recommender systems rely heavily on ID-based collaborative filtering: each item is represented by a unique ID embedding that accumulates collaborative signals from user inte…
Uncertainty-Calibrated Recommendations for Low-Active Users
Bob Junyi Zou, Sai Li, Tianyun Sun +2
A fundamental challenge in recommender systems is balancing reliability for Low-Active Users (LAUs) with diversity for High-Active Users (HAUs). The key to this balance lies in qua…
TwinRouterBench: Fast Static and Live Dynamic Evaluation for Realistic Agentic LLM Routing
Pei Yang, Wanyi Chen, Tongyun Yang +15
LLM routing matters most in long-horizon applications such as coding agents, deep research systems, and computer-use agents, where a single user request triggers many model calls.…
PEARL: Unbiased Percentile Estimation via Contrastive Learning for Industrial-Scale Livestream Recommendation
Blake Gella, Wei Wu, Yuhao Yin +6
Recommender systems trained on user interaction data are susceptible to behavioral intensity imbalance--a systematic distortion arising from heterogeneous engagement patterns acros…
Social-JEPA: Emergent Geometric Isomorphism
Haoran Zhang, Youjin Wang, Yi Duan +6
World models compress rich sensory streams into compact latent codes that anticipate future observations. We let separate agents acquire such models from distinct viewpoints of the…
Assessing the efficacy of large language models in generating accurate teacher responses
Yann Hicke, Abhishek Masand, Wentao Guo +1
(Tack et al., 2023) organized the shared task hosted by the 18th Workshop on Innovative Use of NLP for Building Educational Applications on generation of teacher language in educat…
Coordinating Distributed Example Orders for Provably Accelerated Training
A. Feder Cooper, Wentao Guo, Khiem Pham +4
Recent research on online Gradient Balancing (GraB) has revealed that there exist permutation-based example orderings for SGD that are guaranteed to outperform random reshuffling (…
Photo Rater: Photographs Auto-Selector with Deep Learning
Wentao Guo, Charlie Ruan, Claire Zhou
Photo Rater is a computer vision project that uses neural networks to help photographers select the best photo among those that are taken based on the same scene. This process is u…
GraB: Finding Provably Better Data Permutations than Random Reshuffling
Yucheng Lu, Wentao Guo, Christopher De Sa
Random reshuffling, which randomly permutes the dataset each epoch, is widely adopted in model training because it yields faster convergence than with-replacement sampling. Recent…
Optimizing Gross Merchandise Volume via DNN-MAB Dynamic Ranking Paradigm
Yan Yan, Wentao Guo, Meng Zhao +2
With the transition from people's traditional `brick-and-mortar' shopping to online mobile shopping patterns in web 2.0 , the recommender system plays a critical role…