most citedTowards Personalized Evaluation of Large Language Models with An Anonymous Crowd-Sourcing Platform

8 citations · 25 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CL2024

End-to-End Graph Flattening Method for Large Language Models

Bin Hong, Jinze Wu, Jiayu Liu +5

In recent years, the breakthrough of Large Language Models (LLMs) offers new ideas for achieving universal methods on graph data. The common practice of converting graphs into natu…

cs.SE2024

RePair: Automated Program Repair with Process-based Feedback

Yuze Zhao, Zhenya Huang, Yixiao Ma +6

The gap between the trepidation of program reliability and the expense of repairs underscores the indispensability of Automated Program Repair (APR). APR is instrumental in transfo…

cs.CL20248 cited

Towards Personalized Evaluation of Large Language Models with An Anonymous Crowd-Sourcing Platform

Mingyue Cheng, Hao Zhang, Jiqian Yang +7

Large language model evaluation plays a pivotal role in the enhancement of its capacity. Previously, numerous methods for evaluating large language models have been proposed in thi…

cs.CL20242 cited

A Knowledge-Injected Curriculum Pretraining Framework for Question Answering

Xin Lin, Tianhuang Su, Zhenya Huang +3

Knowledge-based question answering (KBQA) is a key task in NLP research, and also an approach to access the web data and knowledge, which requires exploiting knowledge graphs (KGs)…

cs.HC2024

A Dataset for the Validation of Truth Inference Algorithms Suitable for Online Deployment

Fei Wang, Haoyu Liu, Haoyang Bi +9

For the purpose of efficient and cost-effective large-scale data labeling, crowdsourcing is increasingly being utilized. To guarantee the quality of data labeling, multiple annotat…

cs.CV2024

Bit-mask Robust Contrastive Knowledge Distillation for Unsupervised Semantic Hashing

Liyang He, Zhenya Huang, Jiayu Liu +4

Unsupervised semantic hashing has emerged as an indispensable technique for fast image search, which aims to convert images into binary hash codes without relying on labels. Recent…