activity
20232026
most citedAGIEval: A Human-Centric Benchmark for Evaluating Foundation Models

62 citations · 72 across the 13 of their papers we have counts for

collaborators
Showing 2023Show all

8 papers · 1 filter

cs.CL2023

PPTC Benchmark: Evaluating Large Language Models for PowerPoint Task Completion

Yiduo Guo, Zekai Zhang, Yaobo Liang +2

Recent evaluations of Large Language Models (LLMs) have centered around testing their zero-shot/few-shot capabilities for basic natural language tasks and their ability to translat…

cs.CL2023★ 2 cited

EIPE-text: Evaluation-Guided Iterative Plan Extraction for Long-Form Narrative Text Generation

Wang You, Wenshan Wu, Yaobo Liang +8

Plan-and-Write is a common hierarchical approach in long-form narrative text generation, which first creates a plan to guide the narrative writing. Following this approach, several…

cs.LG2023★ 1 cited

Class Incremental Learning via Likelihood Ratio Based Task Prediction

Haowei Lin, Yijia Shao, Weinan Qian +3

Class incremental learning (CIL) is a challenging setting of continual learning, which learns a series of tasks sequentially. Each task consists of a set of unique classes. The key…

cs.CL2023

Class-Incremental Learning based on Label Generation

Yijia Shao, Yiduo Guo, Dongyan Zhao +1

Despite the great success of pre-trained language models, it is still a challenge to use these models for continual learning, especially for the class-incremental learning (CIL) se…

cs.LG2023★ 2 cited

Dealing with Cross-Task Class Discrimination in Online Continual Learning

Yiduo Guo, Bing Liu, Dongyan Zhao

Existing continual learning (CL) research regards catastrophic forgetting (CF) as almost the only challenge. This paper argues for another challenge in class-incremental learning (…

cs.CL2023

Analyzing and Reducing the Performance Gap in Cross-Lingual Transfer with Fine-tuning Slow and Fast

Yiduo Guo, Yaobo Liang, Dongyan Zhao +2

Existing research has shown that a multilingual pre-trained language model fine-tuned with one (source) language also performs well on downstream tasks for non-source languages, ev…

cs.CL2023★ 2 cited

Learning to Plan with Natural Language

Yiduo Guo, Yaobo Liang, Chenfei Wu +3

Large Language Models (LLMs) have shown remarkable performance in various basic natural language tasks. For completing the complex task, we still need a plan for the task to guide…

cs.CL2023★ 62 cited

AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models

Wanjun Zhong, Ruixiang Cui, Yiduo Guo +6

Evaluating the general abilities of foundation models to tackle human-level tasks is a vital aspect of their development and application in the pursuit of Artificial General Intell…