7 citations · 12 across the 20 of their papers we have counts for
9 papers · 1 filter
Graph World Model
Tao Feng, Yexin Wu, Guanyu Lin +1
World models (WMs) demonstrate strong capabilities in prediction, generation, and planning tasks. Existing WMs primarily focus on unstructured data and cannot leverage the ubiquito…
FusionFactory: Fusing LLM Capabilities with Multi-LLM Log Data
Tao Feng, Haozhen Zhang, Zijie Lei +5
The rapid advancement of large language models (LLMs) has created a diverse landscape of models, each excelling at different tasks. This diversity drives researchers to employ mult…
R1-Ranker: Teaching LLM Rankers to Reason
Tao Feng, Zhigang Hua, Zijie Lei +4
Large language models (LLMs) have recently shown strong reasoning abilities in domains like mathematics, coding, and scientific problem-solving, yet their potential for ranking tas…
Router-R1: Teaching LLMs Multi-Round Routing and Aggregation via Reinforcement Learning
Haozhen Zhang, Tao Feng, Jiaxuan You
The rapid emergence of diverse large language models (LLMs) has spurred the development of LLM routers that assign user queries to the most suitable model. However, existing LLM ro…
Causality Enhanced Origin-Destination Flow Prediction in Data-Scarce Cities
Tao Feng, Yunke Zhang, Huandong Wang +1
Accurate origin-destination (OD) flow prediction is of great importance to developing cities, as it can contribute to optimize urban structures and layouts. However, with the commo…
Causal Discovery and Inference towards Urban Elements and Associated Factors
Tao Feng, Yunke Zhang, Xiaochen Fan +2
To uncover the city's fundamental functioning mechanisms, it is important to acquire a deep understanding of complicated relationships among citizens, location, and mobility behavi…
EPR-GAIL: An EPR-Enhanced Hierarchical Imitation Learning Framework to Simulate Complex User Consumption Behaviors
Tao Feng, Yunke Zhang, Huandong Wang +1
User consumption behavior data, which records individuals' online spending history at various types of stores, has been widely used in various applications, such as store recommend…
GraphEval: A Lightweight Graph-Based LLM Framework for Idea Evaluation
Tao Feng, Yihang Sun, Jiaxuan You
The powerful capabilities of Large Language Models (LLMs) have led to their growing use in evaluating human-generated content, particularly in evaluating research ideas within acad…
Unified Semantic and ID Representation Learning for Deep Recommenders
Guanyu Lin, Zhigang Hua, Tao Feng +3
Effective recommendation is crucial for large-scale online platforms. Traditional recommendation systems primarily rely on ID tokens to uniquely identify items, which can effective…