Zobrazeno 1 - 10
of 750
pro vyhledávání: '"Chen, Wei‐Lin"'
Data annotation refers to the labeling or tagging of textual data with relevant information. A large body of works have reported positive results on leveraging LLMs as an alternative to human annotators. However, existing studies focus on classic NLP
Externí odkaz:
http://arxiv.org/abs/2410.03254
Autor:
Sainz, Oscar, García-Ferrero, Iker, Jacovi, Alon, Campos, Jon Ander, Elazar, Yanai, Agirre, Eneko, Goldberg, Yoav, Chen, Wei-Lin, Chim, Jenny, Choshen, Leshem, D'Amico-Wong, Luca, Dell, Melissa, Fan, Run-Ze, Golchin, Shahriar, Li, Yucheng, Liu, Pengfei, Pahwa, Bhavish, Prabhu, Ameya, Sharma, Suryansh, Silcock, Emily, Solonko, Kateryna, Stap, David, Surdeanu, Mihai, Tseng, Yu-Min, Udandarao, Vishaal, Wang, Zengzhi, Xu, Ruijie, Yang, Jinglin
The 1st Workshop on Data Contamination (CONDA 2024) focuses on all relevant aspects of data contamination in natural language processing, where data contamination is understood as situations where evaluation data is included in pre-training corpora u
Externí odkaz:
http://arxiv.org/abs/2407.21530
Retrieval-augmented generation (RAG) has shown promising potential to enhance the accuracy and factuality of language models (LMs). However, imperfect retrievers or noisy corpora can introduce misleading or even erroneous information to the retrieved
Externí odkaz:
http://arxiv.org/abs/2406.13629
Autor:
Tseng, Yu-Min, Huang, Yu-Chao, Hsiao, Teng-Yun, Chen, Wei-Lin, Huang, Chao-Wei, Meng, Yu, Chen, Yun-Nung
The concept of persona, originally adopted in dialogue literature, has re-surged as a promising framework for tailoring large language models (LLMs) to specific context (e.g., personalized search, LLM-as-a-judge). However, the growing research on lev
Externí odkaz:
http://arxiv.org/abs/2406.01171
The evaluation of large language models (LLMs) has drawn substantial attention in the field recently. This work focuses on evaluating LLMs in a Chinese context, specifically, for Traditional Chinese which has been largely underrepresented in existing
Externí odkaz:
http://arxiv.org/abs/2403.20180
In this paper, we address the hallucination problem commonly found in natural language generation tasks. Language models often generate fluent and convincing content but can lack consistency with the provided source, resulting in potential inaccuraci
Externí odkaz:
http://arxiv.org/abs/2310.14981
We explore the extension of chain-of-thought (CoT) prompting to medical reasoning for the task of automatic diagnosis. Motivated by doctors' underlying reasoning process, we present Diagnostic-Reasoning CoT (DR-CoT). Empirical results demonstrate tha
Externí odkaz:
http://arxiv.org/abs/2307.08922
Large language models (LLMs) have exhibited striking in-context learning (ICL) ability to adapt to target tasks with a few input-output demonstrations. For better ICL, different methods are proposed to select representative demonstrations from existi
Externí odkaz:
http://arxiv.org/abs/2305.15035
Language models (LMs) that jointly generate end-task answers as well as free-text rationales are known as self-rationalization models. Recent works demonstrate great performance gain for self-rationalization by few-shot prompting LMs with rationale-a
Externí odkaz:
http://arxiv.org/abs/2305.07355
Publikováno v:
Atmospheric Environment: X, Vol 23, Iss , Pp 100291- (2024)
Scooters are a popular means of transportation in urban areas. However, studies examining their spatial and temporal features are lacking. This study examined traffic patterns in New Taipei City from September 2021 to June 2023 using real-time survei
Externí odkaz:
https://doaj.org/article/c22328301ea14f90a93679633c8c1e07
