paper-conference

Rethinking the Development of Large Language Models from the Causal Perspective: A Legal Text Prediction Case Study
While large language models (LLMs) exhibit impressive performance on a wide range of NLP tasks, most of them fail to learn the …
Haotian Chen, Lingwei Zhang, Yiran Liu, Yang Yu
PDF Cite Code DOI
OODREB: Benchmarking State-of-the-Art Methods for Out-Of-Distribution Generalization on Relation Extraction
Relation extraction (RE) methods have achieved striking performance when training and test data are independently and identically …
Haotian Chen, Houjing Guo, Bingsheng Chen, Xiangdong Zhou
PDF Cite Code DOI
RD2Bench: Toward Data-Centric Automatic R&D
The progress of humanity is driven by those successful discoveries accompanied by countless failed experiments. Researchers often seek …
Haotian Chen, Xinjie Shen, Zeqi Ye, Xiao Yang, Xu Yang, Weiqing Liu, Jiang Bian
PDF Cite
Did the Models Understand Documents? Benchmarking Models for Language Understanding in Document-Level Relation Extraction
Document-level relation extraction (DocRE) attracts more research interest recently. While models achieve consistent performance gains …
Haotian Chen, Bingsheng Chen, Xiangdong Zhou
PDF Cite Code Dataset Video DOI
SALAS: Supervised Aspect Learning Improves Abstractive Multi-document Summarization Through Aspect Information Loss
Abstractive multi-document summarization (MDS) aims at summarizing and paraphrasing the salient key information in multiple documents. …
Haotian Chen, Han Zhang, Houjing Guo, Shuchang Yi, Bingsheng Chen, Xiangdong Zhou
PDF Cite Code DOI