43 citations · 77 across the 9 of their papers we have counts for
10 papers
TaxPraBen: A Scalable Benchmark for Structured Evaluation of LLMs in Chinese Real-World Tax Practice
Gang Hu, Yating Chen, Haiyan Ding +5
While Large Language Models (LLMs) excel in various general domains, they exhibit notable gaps in the highly specialized, knowledge-intensive, and legally regulated Chinese tax dom…
SiMing-Bench: Evaluating Procedural Correctness from Continuous Interactions in Clinical Skill Videos
Xiyang Huang, Jiawei Lin, Keying Wu +9
Current video benchmarks for multimodal large language models (MLLMs) focus on event recognition, temporal ordering, and long-context recall, but overlook a harder capability requi…
PIXIU: A Large Language Model, Instruction Data and Evaluation Benchmark for Finance
Qianqian Xie, Weiguang Han, Xiao Zhang +4
Although large language models (LLMs) has shown great performance on natural language processing (NLP) in the financial domain, there are no publicly available financial tailtored…
Pre-trained Language Model with Prompts for Temporal Knowledge Graph Completion
Wenjie Xu, Ben Liu, Miao Peng +2
Temporal Knowledge graph completion (TKGC) is a crucial task that involves reasoning at known timestamps to complete the missing part of facts and has attracted more and more atten…
The Wall Street Neophyte: A Zero-Shot Analysis of ChatGPT Over MultiModal Stock Movement Prediction Challenges
Qianqian Xie, Weiguang Han, Yanzhao Lai +2
Recently, large language models (LLMs) like ChatGPT have demonstrated remarkable performance across a variety of natural language processing tasks. However, their effectiveness in…
Mastering Pair Trading with Risk-Aware Recurrent Reinforcement Learning
Weiguang Han, Jimin Huang, Qianqian Xie +3
Although pair trading is the simplest hedging strategy for an investor to eliminate market risk, it is still a great challenge for reinforcement learning (RL) methods to perform pa…
Select and Trade: Towards Unified Pair Trading with Hierarchical Reinforcement Learning
Weiguang Han, Boyi Zhang, Qianqian Xie +3
Pair trading is one of the most effective statistical arbitrage strategies which seeks a neutral profit by hedging a pair of selected assets. Existing methods generally decompose t…
SMiLE: Schema-augmented Multi-level Contrastive Learning for Knowledge Graph Link Prediction
Miao Peng, Ben Liu, Qianqian Xie +3
Link prediction is the task of inferring missing links between entities in knowledge graphs. Embedding-based methods have shown effectiveness in addressing this problem by modeling…
Mention-centered Graph Neural Network for Document-level Relation Extraction
Jiaxin Pan, Min Peng, Yiyan Zhang
Document-level relation extraction aims to discover relations between entities across a whole document. How to build the dependency of entities from different sentences in a docume…
RDSGAN: Rank-based Distant Supervision Relation Extraction with Generative Adversarial Framework
Guoqing Luo, Jiaxin Pan, Min Peng
Distant supervision has been widely used for relation extraction but suffers from noise labeling problem. Neural network models are proposed to denoise with attention mechanism but…