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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/xiye17/textualexplincontext

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The Unreliability of Explanations in Few-shot Prompting for Textual Reasoning

https://github.com/xli04/cvqa

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MM-Prompt: Cross-Modal Prompt Tuning for Continual Visual Question Answering

https://github.com/xliu443/tem-adapter

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Tem-adapter: Adapting Image-Text Pretraining for Video Question Answer

https://github.com/xnhyacinth/iag

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Awakening Augmented Generation: Learning to Awaken Internal Knowledge of Large Language Models for Question Answering

https://github.com/xptree/BlockBERT

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Blockwise Self-Attention for Long Document Understanding

https://github.com/xsc1234/info-rag

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Unsupervised Information Refinement Training of Large Language Models for Retrieval-Augmented Generation

https://github.com/xsc1234/match-prompt

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Match-Prompt: Improving Multi-task Generalization Ability for Neural Text Matching via Prompt Learning

https://github.com/xsc1234/nir-prompt

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NIR-Prompt: A Multi-task Generalized Neural Information Retrieval Training Framework

https://github.com/xsc1234/search-in-the-chain

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Search-in-the-Chain: Interactively Enhancing Large Language Models with Search for Knowledge-intensive Tasks

https://github.com/xsysigma/tencentllmeval

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TencentLLMEval: A Hierarchical Evaluation of Real-World Capabilities for Human-Aligned LLMs

https://github.com/xuehy/TreeAttention

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A Better Way to Attend: Attention with Trees for Video Question Answering

https://github.com/xufangzhi/taco

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Mind Reasoning Manners: Enhancing Type Perception for Generalized Zero-shot Logical Reasoning over Text

https://github.com/xuliu-cyber/rsunivlm

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RSUniVLM: A Unified Vision Language Model for Remote Sensing via Granularity-oriented Mixture of Experts

https://github.com/xuzhao0/model-selection-reasoning

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Automatic Model Selection with Large Language Models for Reasoning

https://github.com/xwhan/Knowledge-Aware-Reader

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Improving Question Answering over Incomplete KBs with Knowledge-Aware Reader

https://github.com/xwhan/ProQA

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Progressively Pretrained Dense Corpus Index for Open-Domain Question Answering

https://github.com/xy-always/genequery

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GeneQuery: A General QA-based Framework for Spatial Gene Expression Predictions from Histology Images

https://github.com/xy-showing/amqa

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AMQA: An Adversarial Dataset for Benchmarking Bias of LLMs in Medicine and Healthcare

https://github.com/xycforgithub/MultiTask-MRC

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Multi-task Learning with Sample Re-weighting for Machine Reading Comprehension

https://github.com/y-d-wang/rsadapter

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RSAdapter: Adapting Multimodal Models for Remote Sensing Visual Question Answering

https://github.com/yachuan/exante

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ExAnte: A Benchmark for Ex-Ante Inference in Large Language Models

https://github.com/yairf11/MUPPET

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Multi-Hop Paragraph Retrieval for Open-Domain Question Answering

https://github.com/yajun-zhou/linguae-naturalis-principia-mathematica

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A mathematical model for universal semantics

https://github.com/yakazimir/Code-Datasets

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A Language for Function Signature Representations

https://github.com/yale-lily/ascle

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Ascle: A Python Natural Language Processing Toolkit for Medical Text Generation

https://github.com/yale-lily/medgen

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Ascle: A Python Natural Language Processing Toolkit for Medical Text Generation

https://github.com/yale-lily/reastap

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ReasTAP: Injecting Table Reasoning Skills During Pre-training via Synthetic Reasoning Examples

https://github.com/yale-nlp/knowledgemath

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FinanceMath: Knowledge-Intensive Math Reasoning in Finance Domains

https://github.com/yale-nlp/mdcure

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MDCure: A Scalable Pipeline for Multi-Document Instruction-Following

https://github.com/yale-nlp/scidqa

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SciDQA: A Deep Reading Comprehension Dataset over Scientific Papers

https://github.com/yale-sys/prompt-cache

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Prompt Cache: Modular Attention Reuse for Low-Latency Inference

https://github.com/yandachen/explanation-consistency-finetuning

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Towards Consistent Natural-Language Explanations via Explanation-Consistency Finetuning

https://github.com/yanglinyi/fine-grained-causal-reasoning

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Towards Fine-grained Causal Reasoning and QA

https://github.com/yanglinyi/supervised-knowledge-makes-large-language-models-better-in-context-learners

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Supervised Knowledge Makes Large Language Models Better In-context Learners

https://github.com/yangliu9208/cmcir

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Cross-Modal Causal Relational Reasoning for Event-Level Visual Question Answering

https://github.com/yangliu9208/vcsr

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Visual Causal Scene Refinement for Video Question Answering

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