Papers with Code 아카이브

Question Answering

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법 전체 데이터셋

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/Eric-Wallace/trickme-interface

공식 코드

Trick Me If You Can: Human-in-the-loop Generation of Adversarial Examples for Question Answering

https://github.com/Erutan-pku/LCN-for-Chinese-QA

공식 코드

Lattice CNNs for Matching Based Chinese Question Answering

https://github.com/Evan-Gao/conversational-QG

공식 코드

Interconnected Question Generation with Coreference Alignment and Conversation Flow Modeling

https://github.com/Evanwu1125/ChartCards

공식 코드

ChartCards: A Chart-Metadata Generation Framework for Multi-Task Chart Understanding

https://github.com/Exploration-Lab/COLD

공식 코드

COLD: Causal reasOning in cLosed Daily activities

https://github.com/FBzzh/CACDD

공식 코드

A Claim Decomposition Benchmark for Long-form Answer Verification

https://github.com/FabienRoger/lm-game-analysis-main

공식 코드

Language models are better than humans at next-token prediction

https://github.com/FairyFali/SLMs-Survey

공식 코드

A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness

https://github.com/Fantabulous-J/FSMODQA

공식 코드

Few-Shot Multilingual Open-Domain QA from 5 Examples

https://github.com/FerdiantJoshua/question-generator

공식 코드

Sequence-to-Sequence Learning for Indonesian Automatic Question Generator

https://github.com/FightingFighting/cross-modal-information-flow-in-MLLM

공식 코드

Cross-modal Information Flow in Multimodal Large Language Models

https://github.com/FilipMiscevic/random_walk

공식 코드

Simple Search Algorithms on Semantic Networks Learned from Language Use

https://github.com/FlamingHorizon/CMM-VR

공식 코드

Cascaded Mutual Modulation for Visual Reasoning

https://github.com/Flitternie/FMProgramming

공식 코드

Resource-efficient Inference with Foundation Model Programs

https://github.com/Franck-Dernoncourt/model-theoretic

공식 코드

Mapping distributional to model-theoretic semantic spaces: a baseline

https://github.com/Francois-Aubet/EQuANt

공식 코드

EQuANt (Enhanced Question Answer Network)

https://github.com/FrankZxShen/ATS

공식 코드

Adversarial Training with OCR Modality Perturbation for Scene-Text Visual Question Answering

https://github.com/FudanDNN-NLP/RAG

공식 코드

Searching for Best Practices in Retrieval-Augmented Generation

https://github.com/GRAAL-Research/quebec-insurance-rag-corpora

공식 코드

Quebec Automobile Insurance Question-Answering With Retrieval-Augmented Generation

https://github.com/GSidiropoulos/kgsqa_for_unseen_domains

공식 코드

Knowledge Graph Simple Question Answering for Unseen Domains

https://github.com/GabrielBena/specialization-dynamics

공식 코드

Dynamics of specialization in neural modules under resource constraints

https://github.com/GanjinZero/RAMM

공식 코드

RAMM: Retrieval-augmented Biomedical Visual Question Answering with Multi-modal Pre-training

https://github.com/GauriNaik826/PUMA-PLASMA-ACL

공식 코드

No perspective, no perception!! Perspective-aware Healthcare Answer Summarization

https://github.com/GeWu-Lab/MUSIC-AVQA

공식 코드

Learning to Answer Questions in Dynamic Audio-Visual Scenarios

https://github.com/GemsLab/KGist

공식 코드

What is Normal, What is Strange, and What is Missing in a Knowledge Graph: Unified Characterization via Inductive Summarization

https://github.com/GeondoPark/MHSAN

공식 코드

MHSAN: Multi-Head Self-Attention Network for Visual Semantic Embedding

https://github.com/Georgetown-IR-Lab/prettr-neural-ir

공식 코드

Efficient Document Re-Ranking for Transformers by Precomputing Term Representations

https://github.com/GeraldHan/GGD

공식 코드

General Greedy De-bias Learning

https://github.com/GeraldHan/GGE

공식 코드

Greedy Gradient Ensemble for Robust Visual Question Answering

https://github.com/Graph-and-Geometric-Learning/MTBench

공식 코드

MTBench: A Multimodal Time Series Benchmark for Temporal Reasoning and Question Answering

https://github.com/Grenzlinie/MatTools

공식 코드

MatTools: Benchmarking Large Language Models for Materials Science Tools

https://github.com/GuessWhatGame/referit

공식 코드

Visual Reasoning with Multi-hop Feature Modulation

https://github.com/HAWLYQ/Qc-TextCap

공식 코드

Question-controlled Text-aware Image Captioning

https://github.com/HELL-TO-HEAVEN/KGE-CL

공식 코드

KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings

https://github.com/HITsz-TMG/SKURG

공식 코드

Enhancing Multi-modal and Multi-hop Question Answering via Structured Knowledge and Unified Retrieval-Generation

https://github.com/HKUNLP/zerogen

공식 코드

ZeroGen: Efficient Zero-shot Learning via Dataset Generation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.