Papers with Code 아카이브

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/jungokasai/XOR_QA_MTPipeline

XOR QA: Cross-lingual Open-Retrieval Question Answering

https://github.com/jungomi/swiss-language-model

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/junhahyung/bert_finetune

Attention Is All You Need

https://github.com/junhahyung/bert_transfer

Attention Is All You Need

https://github.com/junnyu/dpr_paddle

Dense Passage Retrieval for Open-Domain Question Answering

https://github.com/junnyu/paddle_reformer

Reformer: The Efficient Transformer

https://github.com/junnyu/paddle_t5

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

https://github.com/juruobenruo/DexVLA

Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution

https://github.com/jxbz/fromage

Large Batch Optimization for Deep Learning: Training BERT in 76 minutes

https://github.com/jxwuyi/House3D

Embodied Question Answering

https://github.com/jxz542189/dmn_plus

Ask Me Anything: Dynamic Memory Networks for Natural Language Processing

https://github.com/jy0205/lavit

Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization

https://github.com/jzhang38/EasyContext

Long Context Transfer from Language to Vision

https://github.com/jzhang38/longmamba

Lost in the Middle: How Language Models Use Long Contexts

https://github.com/jzhang38/tinyllama

Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling

https://github.com/kafura-kafiri/tf2-elmo

Deep contextualized word representations

https://github.com/kahnchana/locvlm

Learning to Localize Objects Improves Spatial Reasoning in Visual-LLMs

https://github.com/kaihe-better/llm-for-healthcare

BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs

https://github.com/kaist-dmlab/BioNER

Deep contextualized word representations

https://github.com/kaistai/semiparametric_token-sequence_co-supervision

Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection

https://github.com/kaituoxu/Speech-Transformer

Attention Is All You Need

https://github.com/kaituoxu/SpeechTransformer

Attention Is All You Need

https://github.com/kaiyuhe998/rulearn_idea

Representation Engineering: A Top-Down Approach to AI Transparency

https://github.com/kakao/DAFT

GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering

https://github.com/kaleab-k/VideoAT

Would Mega-scale Datasets Further Enhance Spatiotemporal 3D CNNs?

https://github.com/kamalkraj/ALBERT-TF2.0

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

https://github.com/kamalkraj/BERT-SQuAD

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/kamalkraj/BERT_NER

BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

https://github.com/kamalkraj/BioELECTRA

https://github.com/kamalkraj/TAPAS-TF2

TAPAS: Weakly Supervised Table Parsing via Pre-training

https://github.com/kamanphoebe/look-into-moes

Mixtral of Experts

https://github.com/kamichanw/mimic

LIVE: Learnable In-Context Vector for Visual Question Answering

https://github.com/kapilnchauhan77/Disfluency-Detection

Disfl-QA: A Benchmark Dataset for Understanding Disfluencies in Question Answering

https://github.com/kapllan/zeroshot_lexglue

Scaling Instruction-Finetuned Language Models

https://github.com/karanchahal/play-with-vcr

From Recognition to Cognition: Visual Commonsense Reasoning

https://github.com/karandesaiii/CheXNet

ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases

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