61 citations · 115 across the 11 of their papers we have counts for
13 papers
Long Context Alignment with Short Instructions and Synthesized Positions
Wenhao Wu, Yizhong Wang, Yao Fu +3
Effectively handling instructions with extremely long context remains a challenge for Large Language Models (LLMs), typically necessitating high-quality long data and substantial c…
CoUDA: Coherence Evaluation via Unified Data Augmentation
Dawei Zhu, Wenhao Wu, Yifan Song +3
Coherence evaluation aims to assess the organization and structure of a discourse, which remains challenging even in the era of large language models. Due to the scarcity of annota…
Rationale-Enhanced Language Models are Better Continual Relation Learners
Weimin Xiong, Yifan Song, Peiyi Wang +1
Continual relation extraction (CRE) aims to solve the problem of catastrophic forgetting when learning a sequence of newly emerging relations. Recent CRE studies have found that ca…
InfoCL: Alleviating Catastrophic Forgetting in Continual Text Classification from An Information Theoretic Perspective
Yifan Song, Peiyi Wang, Weimin Xiong +4
Continual learning (CL) aims to constantly learn new knowledge over time while avoiding catastrophic forgetting on old tasks. We focus on continual text classification under the cl…
Contrastive Bootstrapping for Label Refinement
Shudi Hou, Yu Xia, Muhao Chen +1
Traditional text classification typically categorizes texts into pre-defined coarse-grained classes, from which the produced models cannot handle the real-world scenario where fine…
RepCL: Exploring Effective Representation for Continual Text Classification
Yifan Song, Peiyi Wang, Dawei Zhu +3
Continual learning (CL) aims to constantly learn new knowledge over time while avoiding catastrophic forgetting on old tasks. In this work, we focus on continual text classificatio…