https://github.com/zycdev/aiso
공식 코드Adaptive Information Seeking for Open-Domain Question Answering
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.
( Image credit: SQuAD )
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Adaptive Information Seeking for Open-Domain Question Answering
Powering Comparative Classification with Sentiment Analysis via Domain Adaptive Knowledge Transfer
Large Language Models for Scientific Synthesis, Inference and Explanation
SPARKLE: Enhancing SPARQL Generation with Direct KG Integration in Decoding
Russian Web Tables: A Public Corpus of Web Tables for Russian Language Based on Wikipedia
Russian Web Tables: A Public Corpus of Web Tables for Russian Language Based on Wikipedia
Russian Web Tables: A Public Corpus of Web Tables for Russian Language Based on Wikipedia
Synthetic Dataset Creation and Fine-Tuning of Transformer Models for Question Answering in Serbian
Generative AI Enhanced Financial Risk Management Information Retrieval
Muppet: Massive Multi-task Representations with Pre-Finetuning
Muppet: Massive Multi-task Representations with Pre-Finetuning
XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models
Reinforcement Learning Outperforms Supervised Fine-Tuning: A Case Study on Audio Question Answering
JNLP Team: Deep Learning for Legal Processing in COLIEE 2020
On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks
Evaluating Semantic Parsing against a Simple Web-based Question Answering Model
The price of debiasing automatic metrics in natural language evaluation
Adversarial Examples for Evaluating Reading Comprehension Systems
Question Answering by Reasoning Across Documents with Graph Convolutional Networks
QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
BioBERT: a pre-trained biomedical language representation model for biomedical text mining
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.