3 citations · 8 across the 7 of their papers we have counts for
4 papers · 1 filter
A Survey on the Honesty of Large Language Models
Siheng Li, Cheng Yang, Taiqiang Wu +12
Honesty is a fundamental principle for aligning large language models (LLMs) with human values, requiring these models to recognize what they know and don't know and be able to fai…
On the Worst Prompt Performance of Large Language Models
Bowen Cao, Deng Cai, Zhisong Zhang +2
The performance of large language models (LLMs) is acutely sensitive to the phrasing of prompts, which raises significant concerns about their reliability in real-world scenarios.…
Consecutive Batch Model Editing with HooK Layers
Shuaiyi Li, Yang Deng, Deng Cai +3
As the typical retraining paradigm is unacceptably time- and resource-consuming, researchers are turning to model editing to find an effective way that supports both consecutive an…
A Thorough Examination of Decoding Methods in the Era of LLMs
Chufan Shi, Haoran Yang, Deng Cai +4
Decoding methods play an indispensable role in converting language models from next-token predictors into practical task solvers. Prior research on decoding methods, primarily focu…