activity
20212024
most citedFoRAG: Factuality-optimized Retrieval Augmented Generation for Web-enhanced Long-form Question Answering

16 citations · 35 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2024★ 6 cited

Face4RAG: Factual Consistency Evaluation for Retrieval Augmented Generation in Chinese

Yunqi Xu, Tianchi Cai, Jiyan Jiang +1

The prevailing issue of factual inconsistency errors in conventional Retrieval Augmented Generation (RAG) motivates the study of Factual Consistency Evaluation (FCE). Despite the v…

cs.CL2024★ 16 cited

FoRAG: Factuality-optimized Retrieval Augmented Generation for Web-enhanced Long-form Question Answering

Tianchi Cai, Zhiwen Tan, Xierui Song +5

Retrieval Augmented Generation (RAG) has become prevalent in question-answering (QA) tasks due to its ability of utilizing search engine to enhance the quality of long-form questio…

cs.LG2023

ULMA: Unified Language Model Alignment with Human Demonstration and Point-wise Preference

Tianchi Cai, Xierui Song, Jiyan Jiang +3

Aligning language models to human expectations, e.g., being helpful and harmless, has become a pressing challenge for large language models. A typical alignment procedure consists…

cs.LG2023★ 1 cited

Marketing Budget Allocation with Offline Constrained Deep Reinforcement Learning

Tianchi Cai, Jiyan Jiang, Wenpeng Zhang +7

We study the budget allocation problem in online marketing campaigns that utilize previously collected offline data. We first discuss the long-term effect of optimizing marketing b…

cs.LG2023

Model-free Reinforcement Learning with Stochastic Reward Stabilization for Recommender Systems

Tianchi Cai, Shenliao Bao, Jiyan Jiang +5

Model-free RL-based recommender systems have recently received increasing research attention due to their capability to handle partial feedback and long-term rewards. However, most…

cs.LG2021★ 12 cited

AutoGL: A Library for Automated Graph Learning

Ziwei Zhang, Yijian Qin, Zeyang Zhang +11

Recent years have witnessed an upsurge in research interests and applications of machine learning on graphs. However, manually designing the optimal machine learning algorithms for…