Results 251 to 260 of about 168,099 (309)

GPTRC: A large-scale dataset for evaluating question-answering capabilities and limitations of large language models. [PDF]

Data Brief
Tripathi A, Gupta T, Dubey AK, Chahar R.
europepmc   +1 more source

<i>LongHealth</i>: A Question Answering Benchmark with Long Clinical Documents. [PDF]

J Healthc Inform Res
Adams L, Busch F, Han T, Excoffier JB, Ortala M, Löser A, Aerts HJWL, Kather JN, Truhn D, Bressem K.   +9 more
europepmc   +1 more source

Comparative performance of GPT-4, GPT-o3, GPT-5, Gemini-3-Flash, and DeepSeek-R1 in ophthalmology question answering. [PDF]

Front Cell Dev Biol
Zhang P, Wang J, Hu X, Wang X, Fan X, Chi W, Yang W.   +6 more
europepmc   +1 more source

Construction and evaluation of the knowledge graph and large model question-answering system for Jin San Zhen therapy: a tool study for primary care and general practice. [PDF]

Front Med (Lausanne)
Chen J, Luo M, Chen J, Luo G, Li G, Lei C, Chen D, Yu J, Gu K.   +8 more
europepmc   +1 more source

Dataset for legal question answering system in the Indian judiciary context. [PDF]

Data Brief
K V, Mishra A.
europepmc   +1 more source

Nursing Retrieval-Augmented Generation: Retrieval augmented generation for nursing question answering with large language models. [PDF]

Int J Nurs Sci
Xiong L, Zeng Q, Luo W, Liu R.
europepmc   +1 more source

Retraction of: Advancing Question-Answering in Ophthalmology With Retrieval-Augmented Generation: Benchmarking Open-Source and Proprietary Large Language Models. [PDF]

Transl Vis Sci Technol
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Questioning the Question -- Addressing the Answerability of Questions in Community Question-Answering

2014 47th Hawaii International Conference on System Sciences, 2014
In this paper, we investigate question quality among questions posted in Yahoo! Answers to assess what factors contribute to the goodness of a question and determine if we can flag poor quality questions. Using human assessments of whether a question is good or bad and extracted textual features from the questions, we built an SVM classifier that ...
Chirag Shah 0001, Vanessa Kitzie, Erik Choi   +2 more
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Questions to Answers

2023
The University of Queensland Abstract Questions to Answers by Yaron Lifschitz The thesis, Questions to Answers, comprises two parts: a book-length collection of poems by the same title and a critical essay entitled “Behind the Verse: the Critical Prose of Poets” which examines critical prose written by three contemporary poets – Louise Glück, Anne ...
openaire   +2 more sources