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Question Answering

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하위 태스크: 19
평가표: 153
보존된 평가 기록: 1,781

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 )

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/aletcher/impossibility-global-convergence

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On the Impossibility of Global Convergence in Multi-Loss Optimization

https://github.com/alex-fabbri/answersumm

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AnswerSumm: A Manually-Curated Dataset and Pipeline for Answer Summarization

https://github.com/alex-gurung/chiron

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CHIRON: Rich Character Representations in Long-Form Narratives

https://github.com/alexa/dstqa

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Multi-domain Dialogue State Tracking as Dynamic Knowledge Graph Enhanced Question Answering

https://github.com/alexa/wqa-cascade-transformers

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The Cascade Transformer: an Application for Efficient Answer Sentence Selection

https://github.com/alexa/wqa_tanda

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TANDA: Transfer and Adapt Pre-Trained Transformer Models for Answer Sentence Selection

https://github.com/alexanderswerdlow/unidisc

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Unified Multimodal Discrete Diffusion

https://github.com/alexdelitzas/3d-vqa

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CLIP-Guided Vision-Language Pre-training for Question Answering in 3D Scenes

https://github.com/alexwarstadt/data_generation

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Investigating BERT's Knowledge of Language: Five Analysis Methods with NPIs

https://github.com/algoprog/syntod

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Simulating Task-Oriented Dialogues with State Transition Graphs and Large Language Models

https://github.com/alibaba-nlp/cdqa

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Let LLMs Take on the Latest Challenges! A Chinese Dynamic Question Answering Benchmark

https://github.com/alibaba-nlp/masksearch

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MASKSEARCH: A Universal Pre-Training Framework to Enhance Agentic Search Capability

https://github.com/alibaba-nlp/omnisearch

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Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning Agent

https://github.com/alibaba-nlp/vec-ra-odqa

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Improving Retrieval Augmented Open-Domain Question-Answering with Vectorized Contexts

https://github.com/alibaba-nlp/webwalker

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WebWalker: Benchmarking LLMs in Web Traversal

https://github.com/alibaba/AliceMind

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VECO: Variable and Flexible Cross-lingual Pre-training for Language Understanding and Generation

https://github.com/alibaba/AliceMind/tree/main/PALM

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PALM: Pre-training an Autoencoding&Autoregressive Language Model for Context-conditioned Generation

https://github.com/alibaba/AliceMind/tree/main/StructBERT

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Multi-granularity hierarchical attention fusion networks for reading comprehension and question answering

https://github.com/alibaba/AliceMind/tree/main/mPLUG

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mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections

https://github.com/alibaba/EasyNLP

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EasyTransfer -- A Simple and Scalable Deep Transfer Learning Platform for NLP Applications

https://github.com/alibaba/eigenscore

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INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection

https://github.com/alibaba/graphtranslator

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GraphTranslator: Aligning Graph Model to Large Language Model for Open-ended Tasks

https://github.com/alibaba/struxgpt

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Enhancing LLM's Cognition via Structurization

https://github.com/alibabaresearch/advancedliteratemachinery

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ProcTag: Process Tagging for Assessing the Efficacy of Document Instruction Data

https://github.com/alibabaresearch/damo-convai

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Long-Tailed Question Answering in an Open World

https://github.com/aliborji/binaryvqa

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BinaryVQA: A Versatile Test Set to Evaluate the Out-of-Distribution Generalization of VQA Models

https://github.com/alipay/PainlessInferenceAcceleration

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Lookahead: An Inference Acceleration Framework for Large Language Model with Lossless Generation Accuracy

https://github.com/alipay/agentuniverse

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PEER: Expertizing Domain-Specific Tasks with a Multi-Agent Framework and Tuning Methods

https://github.com/alipay/rju_ant_qa

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RJUA-QA: A Comprehensive QA Dataset for Urology

https://github.com/alirezamshi/rquge

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RQUGE: Reference-Free Metric for Evaluating Question Generation by Answering the Question

https://github.com/alirezasalemi7/arman

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ARMAN: Pre-training with Semantically Selecting and Reordering of Sentences for Persian Abstractive Summarization

https://github.com/alirezasalemi7/dedr-mm-fid

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A Symmetric Dual Encoding Dense Retrieval Framework for Knowledge-Intensive Visual Question Answering

https://github.com/alirezasalemi7/pr-rag

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Plan-and-Refine: Diverse and Comprehensive Retrieval-Augmented Generation

https://github.com/alirezasalemi7/pretraining-multimodal-dense-retriever-for-okvqa

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Pre-Training Multi-Modal Dense Retrievers for Outside-Knowledge Visual Question Answering

https://github.com/alirezasalemi7/urag

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Towards a Search Engine for Machines: Unified Ranking for Multiple Retrieval-Augmented Large Language Models

https://github.com/alisafaya/neurocache

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Neurocache: Efficient Vector Retrieval for Long-range Language Modeling

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