28 citations · 37 across the 14 of their papers we have counts for
9 papers · 1 filter
ArenaFlow: From Trajectory Ranking to Hierarchical Credit Propagation for Open-Ended Agent RL
Qiang Zhang, Ruixue Ding, Fanrui Zhang +9
Reinforcement learning has substantially improved large language model (LLM) agents in verifiable domains, but remains difficult to apply to open-ended agent tasks, where solutions…
VRAG-RL: Empower Vision-Perception-Based RAG for Visually Rich Information Understanding via Iterative Reasoning with Reinforcement Learning
Qiuchen Wang, Ruixue Ding, Yu Zeng +6
Effectively retrieving, reasoning and understanding visually rich information remains a challenge for RAG methods. Traditional text-based methods cannot handle visual-related infor…
CoFE-RAG: A Comprehensive Full-chain Evaluation Framework for Retrieval-Augmented Generation with Enhanced Data Diversity
Jintao Liu, Ruixue Ding, Linhao Zhang +2
Retrieval-Augmented Generation (RAG) aims to enhance large language models (LLMs) to generate more accurate and reliable answers with the help of the retrieved context from externa…
Let LLMs Take on the Latest Challenges! A Chinese Dynamic Question Answering Benchmark
Zhikun Xu, Yinghui Li, Ruixue Ding +7
How to better evaluate the capabilities of Large Language Models (LLMs) is the focal point and hot topic in current LLMs research. Previous work has noted that due to the extremely…
Geo-Encoder: A Chunk-Argument Bi-Encoder Framework for Chinese Geographic Re-Ranking
Yong Cao, Ruixue Ding, Boli Chen +5
Chinese geographic re-ranking task aims to find the most relevant addresses among retrieved candidates, which is crucial for location-related services such as navigation maps. Unli…
GeoGLUE: A GeoGraphic Language Understanding Evaluation Benchmark
Dongyang Li, Ruixue Ding, Qiang Zhang +8
With a fast developing pace of geographic applications, automatable and intelligent models are essential to be designed to handle the large volume of information. However, few rese…
MGeo: Multi-Modal Geographic Pre-Training Method
Ruixue Ding, Boli Chen, Pengjun Xie +4
As a core task in location-based services (LBS) (e.g., navigation maps), query and point of interest (POI) matching connects users' intent with real-world geographic information. R…
Forging Multiple Training Objectives for Pre-trained Language Models via Meta-Learning
Hongqiu Wu, Ruixue Ding, Hai Zhao +4
Multiple pre-training objectives fill the vacancy of the understanding capability of single-objective language modeling, which serves the ultimate purpose of pre-trained language m…
Adversarial Self-Attention for Language Understanding
Hongqiu Wu, Ruixue Ding, Hai Zhao +3
Deep neural models (e.g. Transformer) naturally learn spurious features, which create a ``shortcut'' between the labels and inputs, thus impairing the generalization and robustness…